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Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Slack...
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Switch workspaces… (Jiminny Inc) Has new messages
Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
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Nikolay Ivanov
Today at 11:01:50 AM
11:01 AM
Хм, Джейс дали не може да ти помогне?
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Lukas Kovalik
Today at 11:01:52 AM
11:01 AM
ще питам James, предполагам че нямам права
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Today at 11:01:56 AM
11:01
да мерси
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Nikolay Ivanov
Today at 11:01:56 AM
11:01 AM
мда
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Today at 11:01:58 AM
11:01
моля
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Lukas Kovalik
Today at 12:13:43 PM
12:13 PM
Ники сори, още един въпрос имам
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Today at 12:14:12 PM
12:14
когато ги правеше ти FE ли оправя
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Today at 12:15:18 PM
12:15
има vulnerabilities по npm
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Nikolay Ivanov
Today at 12:28:03 PM
12:28 PM
не
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Today at 12:28:17 PM
12:28
тях ги оставям
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Lukas Kovalik
Today at 12:29:00 PM
12:29 PM
аз погледнах твоя тикет и там друго нямаше само FE
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Today at 12:29:32 PM
12:29
как стигна до Worker
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James Graham, Direct Message, 1 of 15 suggestions
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Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
React with white_check_mark
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Nikolay Ivanov
Today at 11:01:50 AM
11:01 AM
Хм, Джейс дали не може да ти помогне?
React with white_check_mark
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Lukas Kovalik
Today at 11:01:52 AM
11:01 AM
ще питам James, предполагам че нямам права
React with white_check_mark
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Today at 11:01:56 AM
11:01
да мерси
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Nikolay Ivanov
Today at 11:01:56 AM
11:01 AM
мда
React with white_check_mark
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Today at 11:01:58 AM
11:01
моля
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Lukas Kovalik
Today at 12:13:43 PM
12:13 PM
Ники сори, още един въпрос имам
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Today at 12:14:12 PM
12:14
когато ги правеше ти FE ли оправя
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Today at 12:15:18 PM
12:15
има vulnerabilities по npm
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Nikolay Ivanov
Today at 12:28:03 PM
12:28 PM
не
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Today at 12:28:17 PM
12:28
тях ги оставям
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Lukas Kovalik
Today at 12:29:00 PM
12:29 PM
аз погледнах твоя тикет и там друго нямаше само FE
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Today at 12:29:32 PM
12:29
как стигна до Worker
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James Graham, Direct Message, 1 of 15 suggestions
Nikolay Ivanov is typing
FirefoxEditVIeWMistorbookmarksProtllesToolsWindowmelpnvd.nist.gov/vuln/detail/cve-2026-24765≥0 lll I Support Daily - in 2h 29 m100% C/3 8• Wed 13 May 12:31:27[JY-19967] Upgrade Python and liDependabot alerts • jiminny/proph# (UY-19958] Upgrade BE ibraries -liminny/app/backend-code - VantaNo NVD - cve-2026-24765Low vulnerabilities identified in paciminnylaop/backend-code - VantalNo NVD -cve-2026-6722fuy-207731 User Pilot not receivin@ JY-19957 | Remove abanded sympTypeError: Leaque\Flysystem\FilesNew Tabu Userpilot | Ask Jiminny Report Gen(SRD-6848] Sidekick SMS issue -[JY-19957] Upgrade BE libraries -JY-19957 | Remove abanded symp{2 Hich vulnerabilities identified in palMedium vulnerabilities identified inLow vulnerabilities identified in pac+ New TabAn official weNISTInformation Technology Laboratory.NATIONAL VULNERABILITY DATABASEENVD MENUNISTÌ(RAONAE WULNERABLTYVUILNERABILMIESX-CVE-2026-24765 Detail$1Slackinstrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage filesfor PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies.Rather than just silently sanitizing the input via '['allowed_classes' => false]*, the maintainer has chosen to make the anomalous stateexplicit by treating pre-existing '.coverage' files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62,9.6.33, when a '.coverage' file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying theanomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeralrunners, code review enforcement, branch protection, artifact isolation, and access control.Source:GitHub, Inc.MetricsWOrCtMMhCVSS Version 3.›CVSS Version 2.0lNVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.CVSS 3.x Severity and Vector Strings:NIST: NVDBase Score.NVD assessment not vet provided.CNA: GitHub. IndBase Score.Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/1:H/A:HReferences to Advisories, Solutions, and Tools...
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Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Slack...
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Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
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Nikolay Ivanov
Today at 11:01:50 AM
11:01 AM
Хм, Джейс дали не може да ти помогне?
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Lukas Kovalik
Today at 11:01:52 AM
11:01 AM
ще питам James, предполагам че нямам права
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Today at 11:01:56 AM
11:01
да мерси
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Nikolay Ivanov
Today at 11:01:56 AM
11:01 AM
мда
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Today at 11:01:58 AM
11:01
моля
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Lukas Kovalik
Today at 12:13:43 PM
12:13 PM
Ники сори, още един въпрос имам
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Today at 12:14:12 PM
12:14
когато ги правеше ти FE ли оправя
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Today at 12:15:18 PM
12:15
има vulnerabilities по npm
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Nikolay Ivanov
Today at 12:28:03 PM
12:28 PM
не
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Today at 12:28:17 PM
12:28
тях ги оставям
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Lukas Kovalik
Today at 12:29:00 PM
12:29 PM
аз погледнах твоя тикет и там друго нямаше само FE
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Today at 12:29:32 PM
12:29
как стигна до Worker
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visual_change
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Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
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Nikolay Ivanov
Today at 11:01:50 AM
11:01 AM
Хм, Джейс дали не може да ти помогне?
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Lukas Kovalik
Today at 11:01:52 AM
11:01 AM
ще питам James, предполагам че нямам права
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Today at 11:01:56 AM
11:01
да мерси
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Nikolay Ivanov
Today at 11:01:56 AM
11:01 AM
мда
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Today at 11:01:58 AM
11:01
моля
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Lukas Kovalik
Today at 12:13:43 PM
12:13 PM
Ники сори, още един въпрос имам
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Today at 12:14:12 PM
12:14
когато ги правеше ти FE ли оправя
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Today at 12:15:18 PM
12:15
има vulnerabilities по npm
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Nikolay Ivanov
Today at 12:28:03 PM
12:28 PM
не
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Today at 12:28:17 PM
12:28
тях ги оставям
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Lukas Kovalik
Today at 12:29:00 PM
12:29 PM
аз погледнах твоя тикет и там друго нямаше само FE
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Today at 12:29:32 PM
12:29
как стигна до Worker
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James Graham, Direct Message, 1 of 15 suggestions
Nikolay Ivanov is typing
SlackFileEditViewGoHistoryWindowHelpDOCKEIDOCKER181DEV (-zsh)O $2APP (-zshX MDOCKER (-zsh)Last login: Tue May 12 17:54:40 on consolePoetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $•HomeDMsActivityFilesLater..•Morelthl§ Support Daily - in 2h 29 m100% (C478•Wed 13 May 12:31:29ED→QDescribe what you are looking forJiminny ...Nikolay Ivanov6 0curoarlylau# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...• Messages+Direct messagesNikolay Ivanovdo James Graham. Stoyan Tanev®. Galya DimitrovaP. Steliyan GeorgievLo Petko Kashinski®. Aneliya Angelovaã. Stefka Stoyanova•. Vasil Vasilev 0!Lukas Kovalik y...AppsAdd canvasO FilesLukas Kovalik 11.Today ~мен все ме праща наhttps://app.vanta.com/c/jiminny.com/employee/onboardingNikolay Ivanov 11:01 AMХм, Джейс дали не може да ти помогне?Lukas Kovalik 11:01 AMще питам James, предполагам че нямам правада мерсиNikolay Ivanov 11:01 AMмдаМОЛЯLukas Kovalik 12:13 PMНики сори, още един въпрос имамкогато ги правеше ти FE ли оправяима vulnerabilities no npmNikolay Ivanov 12:28 PMнетях ги оставямLukas Kovalik 12:29 PMаз погледнах твоя тикет и там друго нямашесамо FEкак стигна до WorkerJira CloudMessage Nikolay IvanovToast...
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
Close tab
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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An official website of the United States government
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National Institute of Standards and Technology
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Information Technology Laboratory
Information Technology Laboratory
Information Technology Laboratory
NATIONAL VULNERABILITY DATABASE
NATIONAL VULNERABILITY DATABASE
NATIONAL VULNERABILITY DATABASE
VULNERABILITIES
VULNERABILITIES
CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
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Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52...
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This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.","depth":15,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Metrics","depth":15,"on_screen":true,"help_text":"CVSS is not a measure of risk","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Metrics","depth":16,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"","depth":15,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"CVSS Version 4.0","depth":16,"on_screen":true,"help_text":"Click here to view CVSS 4.0 data","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"CVSS Version 3.x","depth":16,"on_screen":true,"help_text":"Click here to view CVSS 3.x data","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"CVSS Version 2.0","depth":16,"on_screen":true,"help_text":"Click here to view CVSS 2.0 data","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"NVD enrichment efforts reference publicly available information to associate vector strings. 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We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. 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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52...
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2026-05-13T09:31:31.049256+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664691049_m2.jpg...
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Firefox
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NVD - cve-2026-24765 — Work
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1
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nvd.nist.gov/vuln/detail/cve-2026-24765
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monitor_2
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
Close tab
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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NULL
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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NULL
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32670
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47
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2026-05-13T09:31:32.981890+00:00
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NVD - cve-2026-24765 — Work
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1
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nvd.nist.gov/vuln/detail/cve-2026-24765
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monitor_1
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NULL
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
Close tab
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
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URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
Tag(s)
Patch
Release Notes
Release Notes
Release Notes
Release Notes
Release Notes
Mitigation
Vendor Advisory
Mailing List
Third Party Advisory
Weakness Enumeration
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
CWE-ID
CWE-502
CWE-502
CWE Name
Deserialization of Untrusted Data
Source
GitHub, Inc.
Known Affected Software Configurations Switch to CPE 2.2
Known Affected Software Configurations
Switch to CPE 2.2
Switch to CPE 2.2
Configuration 1
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hide
hide
)
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
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From (including)
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Up to (excluding)
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Up to (excluding)
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-991515859399964159
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-2436674491298530142
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visual_change
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accessibility
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NULL
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
Close tab
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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[SRD-6848] Sidekick SMS issue - Jira
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[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
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Source(s)
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https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
Tag(s)
Patch
Release Notes
Release Notes
Release Notes
Release Notes
Release Notes
Mitigation
Vendor Advisory
Mailing List
Third Party Advisory
Weakness Enumeration
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
CWE-ID
CWE-502
CWE-502
CWE Name
Deserialization of Untrusted Data
Source
GitHub, Inc.
Known Affected Software Configurations Switch to CPE 2.2
Known Affected Software Configurations
Switch to CPE 2.2
Switch to CPE 2.2
Configuration 1
(
hide
hide
)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
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Up to (excluding)
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
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9.0.0
Up to (excluding)
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
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Up to (excluding)
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
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Show Matching CPE(s)
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
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...
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32668
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NULL
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NULL
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NULL
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32671
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1251
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74
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2026-05-13T09:31:33.013247+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664693013_m2.jpg...
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Firefox
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NVD - cve-2026-24765 — Work
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1
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nvd.nist.gov/vuln/detail/cve-2026-24765
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monitor_2
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
Close tab
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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[SRD-6848] Sidekick SMS issue - Jira
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[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
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Patch
Release Notes
Release Notes
Release Notes
Release Notes
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Vendor Advisory
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Weakness Enumeration
CWE-ID...
|
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
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Source(s)
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https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
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https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
Tag(s)
Patch
Release Notes
Release Notes
Release Notes
Release Notes
Release Notes
Mitigation
Vendor Advisory
Mailing List
Third Party Advisory
Weakness Enumeration
Weakness Enumeration
CWE-ID...
|
32669
|
NULL
|
NULL
|
NULL
|
|
32672
|
1250
|
48
|
2026-05-13T09:31:35.998025+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664695998_m1.jpg...
|
Firefox
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NVD - cve-2026-24765 — Work
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1
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nvd.nist.gov/vuln/detail/cve-2026-24765
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monitor_1
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NULL
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NULL
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NULL
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NULL
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
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NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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[SRD-6848] Sidekick SMS issue - Jira
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[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
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URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
Tag(s)
Patch
Release Notes
Release Notes
Release Notes
Release Notes
Release Notes
Mitigation
Vendor Advisory
Mailing List
Third Party Advisory
Weakness Enumeration
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
CWE-ID
CWE-502
CWE-502
CWE Name
Deserialization of Untrusted Data
Source
GitHub, Inc.
Known Affected Software Configurations Switch to CPE 2.2
Known Affected Software Configurations
Switch to CPE 2.2
Switch to CPE 2.2
Configuration 1
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
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Up to (excluding)
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cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
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Up to (excluding)
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From (including)
9.0.0
From (including)
10.0.0
From (including)
11.0.0
From (including)
12.0.0
Up to (excluding)
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Up to (excluding)
10.5.62
Up to (excluding)
11.5.50
Up to (excluding)
12.5.8
Configuration 2
(
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cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:*
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Denotes Vulnerable Software
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Change History
Change History
3 change records found
show changes
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QUICK INFO
QUICK INFO
CVE Dictionary Entry:
CVE-2026-24765
CVE-2026-24765
NVD Published Date:
01/27/2026
NVD Last Modified:
03/03/2026
Source:
GitHub, Inc.
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cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. 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A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. 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We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. 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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
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[JY-19958] Upgrade BE libraries - May - Jira
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NVD - cve-2026-6722
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
Tag(s)
Patch
Release Notes
Release Notes
Release Notes
Release Notes
Release Notes
Mitigation
Vendor Advisory
Mailing List
Third Party Advisory
Weakness Enumeration
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
CWE-ID
CWE-502
CWE-502
CWE Name
Deserialization of Untrusted Data
Source
GitHub, Inc.
Known Affected Software Configurations Switch to CPE 2.2
Known Affected Software Configurations
Switch to CPE 2.2
Switch to CPE 2.2
Configuration 1
(
hide
hide
)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
Up to (excluding)
8.5.52
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
9.0.0
Up to (excluding)
9.6.33
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
10.0.0
Up to (excluding)
10.5.62
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
11.0.0
Up to (excluding)
11.5.50
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
12.0.0
Up to (excluding)
12.5.8
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
Up to (excluding)
8.5.52
From (including)
9.0.0
From (including)
10.0.0
From (including)
11.0.0
From (including)
12.0.0
Up to (excluding)
9.6.33
Up to (excluding)
10.5.62
Up to (excluding)
11.5.50
Up to (excluding)
12.5.8
Configuration 2
(
hide
hide
)
cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:*
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Denotes Vulnerable Software
Are we missing a CPE here? Please let us know
Are we missing a CPE here? Please let us know
.
Change History
Change History
3 change records found
show changes
show changes
QUICK INFO
QUICK INFO
CVE Dictionary Entry:
CVE-2026-24765
CVE-2026-24765
NVD Published Date:
01/27/2026
NVD Last Modified:
03/03/2026
Source:
GitHub, Inc.
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
Tag(s)
Patch
Release Notes
Release Notes
Release Notes
Release Notes
Release Notes
Mitigation
Vendor Advisory
Mailing List
Third Party Advisory
Weakness Enumeration
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
CWE-ID
CWE-502
CWE-502
CWE Name
Deserialization of Untrusted Data
Source
GitHub, Inc.
Known Affected Software Configurations Switch to CPE 2.2
Known Affected Software Configurations
Switch to CPE 2.2
Switch to CPE 2.2
Configuration 1
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I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"bounds":{"left":0.13680187,"top":0.19313647,"width":0.051861703,"height":0.09577015},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"bounds":{"left":0.079288565,"top":0.19393456,"width":0.019946808,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765","depth":23,"bounds":{"left":0.13680187,"top":0.19473264,"width":0.051695477,"height":0.11213089},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Detail","depth":23,"bounds":{"left":0.13680187,"top":0.2905028,"width":0.013796543,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Description","depth":23,"bounds":{"left":0.13680187,"top":0.30965683,"width":0.027759308,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"PHPUnit is a testing framework for PHP. 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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
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the facts presented on these sites. Further, NIST does not
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https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
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Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
Tag(s)
Patch
Release Notes
Release Notes
Release Notes
Release Notes
Release Notes
Mitigation
Vendor Advisory
Mailing List
Third Party Advisory
Weakness Enumeration
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
CWE-ID
CWE-502
CWE-502
CWE Name
Deserialization of Untrusted Data
Source
GitHub, Inc.
Known Affected Software Configurations Switch to CPE 2.2
Known Affected Software Configurations
Switch to CPE 2.2
Switch to CPE 2.2
Configuration 1
(
hide
hide
)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
Up to (excluding)
8.5.52
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
9.0.0
Up to (excluding)
9.6.33
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
10.0.0
Up to (excluding)
10.5.62
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
11.0.0
Up to (excluding)
11.5.50
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
12.0.0
Up to (excluding)
12.5.8
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
Up to (excluding)
8.5.52
From (including)
9.0.0
From (including)
10.0.0
From (including)
11.0.0
From (including)
12.0.0
Up to (excluding)
9.6.33
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10.5.62
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11.5.50...
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NVD - cve-2026-24765 — Work
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
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Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
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Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
,
a popular testing framework for PHP.
The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
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Summarize page
Summarize page
An official website of the United States government
Here's how you know
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National Institute of Standards and Technology
NVD MENU
NVD
MENU
Information Technology Laboratory
Information Technology Laboratory
Information Technology Laboratory
NATIONAL VULNERABILITY DATABASE
NATIONAL VULNERABILITY DATABASE
NATIONAL VULNERABILITY DATABASE
VULNERABILITIES
VULNERABILITIES
CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
Tag(s)
Patch
Release Notes
Release Notes
Release Notes
Release Notes
Release Notes
Mitigation
Vendor Advisory
Mailing List
Third Party Advisory
Weakness Enumeration
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
CWE-ID
CWE-502
CWE-502
CWE Name
Deserialization of Untrusted Data
Source
GitHub, Inc.
Known Affected Software Configurations Switch to CPE 2.2
Known Affected Software Configurations
Switch to CPE 2.2
Switch to CPE 2.2
Configuration 1
(
hide
hide
)
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
Up to (excluding)
8.5.52
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
9.0.0
Up to (excluding)
9.6.33
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
10.0.0
Up to (excluding)
10.5.62
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
11.0.0
Up to (excluding)
11.5.50
cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:*
Show Matching CPE(s)
Show Matching CPE(s)
From (including)
12.0.0
Up to (excluding)
12.5.8
...
|
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A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. 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Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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(excluding)","depth":19,"bounds":{"left":0.6704861,"top":0.9766667,"width":0.083680555,"height":0.023333311},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"12.5.8","depth":19,"bounds":{"left":0.6704861,"top":1.0,"width":0.030208332,"height":-0.0038888454},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"","depth":20,"bounds":{"left":0.24131945,"top":0.75,"width":0.011111111,"height":0.018888889},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
Expand
Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
,
a popular testing framework for PHP.
The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
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Summarize page
Summarize page
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National Institute of Standards and Technology
NVD MENU
NVD
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Information Technology Laboratory
Information Technology Laboratory
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NATIONAL VULNERABILITY DATABASE
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VULNERABILITIES
VULNERABILITIES
CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
Source(s)
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
GitHub, Inc.
CVE
Tag(s)
Patch
Release Notes
Release Notes
Release Notes
Release Notes
Release Notes
Mitigation
Vendor Advisory
Mailing List
Third Party Advisory
Weakness Enumeration
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
CWE-ID
CWE-502
CWE-502
CWE Name
Deserialization of Untrusted Data
Source
GitHub, Inc.
Known Affected Software Configurations Switch to CPE 2.2
Known Affected Software Configurations
Switch to CPE 2.2
Switch to CPE 2.2
Configuration 1
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From (including)
9.0.0
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NVD - cve-2026-24765 — Work
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
Expand
Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
,
a popular testing framework for PHP.
The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled,
it deserializes the malicious file.
If the object contains a
__wakeup()
magic method,
it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.
5.
8
11.x:
Before 11.
5.
50
10.x:
Before 10.
5.
62
9.x:
Before 9.
6.
33
8.x:
Before 8.
5.
52
Risk Assessment
Risk Assessment
CVSS Score:
7.
8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files.
Common threat environments include compromised CI/CD pipelines,
local development machines,
or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD,
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc....
|
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A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
Expand
Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
,
a popular testing framework for PHP.
The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled,
it deserializes the malicious file.
If the object contains a
__wakeup()
magic method,
it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.
5.
8
11.x:
Before 11.
5.
50
10.x:
Before 10.
5.
62
9.x:
Before 9.
6.
33
8.x:
Before 8.
5.
52
Risk Assessment
Risk Assessment
CVSS Score:
7.
8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files.
Common threat environments include compromised CI/CD pipelines,
local development machines,
or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD,
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc....
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NVD - cve-2026-24765 — Work
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
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NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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[SRD-6848] Sidekick SMS issue - Jira
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[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
Expand
Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
,
a popular testing framework for PHP.
The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled,
it deserializes the malicious file.
If the object contains a
__wakeup()
magic method,
it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.
5.
8
11.x:
Before 11.
5.
50
10.x:
Before 10.
5.
62
9.x:
Before 9.
6.
33
8.x:
Before 8.
5.
52
Risk Assessment
Risk Assessment
CVSS Score:
7.
8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files.
Common threat environments include compromised CI/CD pipelines,
local development machines,
or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD,
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said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
Expand
Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
,
a popular testing framework for PHP.
The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled,
it deserializes the malicious file.
If the object contains a
__wakeup()
magic method,
it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.
5.
8
11.x:
Before 11.
5.
50
10.x:
Before 10.
5.
62
9.x:
Before 9.
6.
33
8.x:
Before 8.
5.
52
Risk Assessment
Risk Assessment
CVSS Score:
7.
8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files.
Common threat environments include compromised CI/CD pipelines,
local development machines,
or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD,
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NVD - cve-2026-24765 — Work
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
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Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33...
|
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A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
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sites that are more appropriate for your purpose. NIST does
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the facts presented on these sites. Further, NIST does not
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Source(s)
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https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
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Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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VULNERABILITIES
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
URL
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33...
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NVD - cve-2026-24765 — Work
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nvd.nist.gov/vuln/detail/cve-2026-24765
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
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vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
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URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
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Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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CVE-2026-24765 Detail
CVE-2026-24765
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cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Detail","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Description","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Metrics","depth":23,"bounds":{"left":0.1221742,"top":0.11811652,"width":0.017952127,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"NVD enrichment efforts reference publicly available information to associate","depth":23,"bounds":{"left":0.1221742,"top":0.13727055,"width":0.06582447,"height":0.054668795},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"vector strings. 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Software","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Are we missing a CPE here? Please let us know.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Change History","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3 change records found show changes","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Quick Info","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CVE Dictionary Entry: CVE-2026-24765 NVD","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Published Date: 01/27/2026 NVD","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Last Modified: 03/03/2026","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Source: GitHub, Inc.</selection>” selected.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Please summarize the selection using precise and concise language. 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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
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Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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CVE-2026-24765 Detail
CVE-2026-24765
Detail...
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
Expand
Listen
Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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how can I fix these vulnareabilities in laravel project
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Fixing this vulnerability in a Laravel project is a very straightforward process. In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.
Here is exactly how to secure your project:
1. Check Your Current Version
1. Check Your Current Version
First, verify which version of PHPUnit your Laravel application is currently using. Run this command in your terminal at the root of your project:
Bash
Download code
Copy code
composer show phpunit/phpunit
Look at the
versions
line in the output to see if you are running a vulnerable version (anything lower than 12.5.8, 11.5.50, 10.5.62, 9.6.33, or 8.5.52).
2. Update PHPUnit
2. Update PHPUnit
Tell Composer to update PHPUnit and its associated dependencies to the latest secure versions allowed by your
composer.json
constraints:
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composer update phpunit/phpunit --with-dependencies
Note: If your
composer.json
restricts PHPUnit to an older major version (like
^9.0
), Composer will automatically grab the secure patch for that specific major version (e.g., 9.6.33).
3. Verify the Fix
3. Verify the Fix
Run the
composer show
command from step one again to confirm the version has been bumped. As long as your version is at or above one of the secure releases listed above, you are protected against CVE-2026-24765.
4. Secure Your Environments
4. Secure Your Environments
Because PHPUnit lives in the
require-dev
block of your
composer.json
, this vulnerability does not impact your production environment—
provided you are deploying correctly
.
Always build your production environment using
composer install --no-dev --optimize-autoloader
. This ensures testing frameworks are completely excluded from your live servers.
For your CI/CD pipelines, ensure you are using ephemeral runners (runners that spin up fresh for every job and are destroyed afterward) so that an attacker cannot leave a malicious
.coverage
file behind for a subsequent test run to execute.
Would you like me to walk you through how to verify that your production server is completely free of development dependencies?
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National Institute of Standards and Technology
NVD MENU
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Information Technology Laboratory
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NATIONAL VULNERABILITY DATABASE
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VULNERABILITIES
VULNERABILITIES
CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50...
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cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Detail","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Description","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Metrics","depth":23,"bounds":{"left":0.1221742,"top":0.11811652,"width":0.017952127,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"NVD enrichment efforts reference publicly available information to associate","depth":23,"bounds":{"left":0.1221742,"top":0.13727055,"width":0.06582447,"height":0.054668795},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"vector strings. 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In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.","depth":24,"bounds":{"left":0.08959442,"top":0.32960895,"width":0.11386303,"height":0.12011173},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is exactly how to secure your project:","depth":24,"bounds":{"left":0.08959442,"top":0.46288908,"width":0.102726065,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Check Your Current Version","depth":23,"bounds":{"left":0.08959442,"top":0.50359136,"width":0.11502659,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. 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-5786067871435773185
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-2724759324890939738
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visual_change
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accessibility
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NULL
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
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Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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You said how can I fix these vulnareabilities in laravel project
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how can I fix these vulnareabilities in laravel project
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Gemini said
Fixing this vulnerability in a Laravel project is a very straightforward process. In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.
Here is exactly how to secure your project:
1. Check Your Current Version
1. Check Your Current Version
First, verify which version of PHPUnit your Laravel application is currently using. Run this command in your terminal at the root of your project:
Bash
Download code
Copy code
composer show phpunit/phpunit
Look at the
versions
line in the output to see if you are running a vulnerable version (anything lower than 12.5.8, 11.5.50, 10.5.62, 9.6.33, or 8.5.52).
2. Update PHPUnit
2. Update PHPUnit
Tell Composer to update PHPUnit and its associated dependencies to the latest secure versions allowed by your
composer.json
constraints:
Bash
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composer update phpunit/phpunit --with-dependencies
Note: If your
composer.json
restricts PHPUnit to an older major version (like
^9.0
), Composer will automatically grab the secure patch for that specific major version (e.g., 9.6.33).
3. Verify the Fix
3. Verify the Fix
Run the
composer show
command from step one again to confirm the version has been bumped. As long as your version is at or above one of the secure releases listed above, you are protected against CVE-2026-24765.
4. Secure Your Environments
4. Secure Your Environments
Because PHPUnit lives in the
require-dev
block of your
composer.json
, this vulnerability does not impact your production environment—
provided you are deploying correctly
.
Always build your production environment using
composer install --no-dev --optimize-autoloader
. This ensures testing frameworks are completely excluded from your live servers.
For your CI/CD pipelines, ensure you are using ephemeral runners (runners that spin up fresh for every job and are destroyed afterward) so that an attacker cannot leave a malicious
.coverage
file behind for a subsequent test run to execute.
Would you like me to walk you through how to verify that your production server is completely free of development dependencies?
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CVE-2026-24765 Detail
CVE-2026-24765
Detail
Description
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
Metrics
CVSS Version 4.0
CVSS Version 3.x
CVSS Version 2.0
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 3.x Severity and Vector Strings:
NIST:
NVD
Base Score:
N/A
NVD assessment not yet provided.
CNA:
GitHub, Inc.
Base Score:
7.8 HIGH
7.8 HIGH
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to
[EMAIL]
[EMAIL]
.
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50...
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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You said how can I fix these vulnareabilities in laravel project
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how can I fix these vulnareabilities in laravel project
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Gemini said
Gemini said
Fixing this vulnerability in a Laravel project is a very straightforward process. In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.
Here is exactly how to secure your project:
1. Check Your Current Version
1. Check Your Current Version
First, verify which version of PHPUnit your Laravel application is currently using. Run this command in your terminal at the root of your project:
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cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. 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Software","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Are we missing a CPE here? Please let us know.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Change History","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3 change records found show changes","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Quick Info","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CVE Dictionary Entry: CVE-2026-24765 NVD","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Published Date: 01/27/2026 NVD","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Last Modified: 03/03/2026","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Source: GitHub, Inc.</selection>” selected.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"Gemini said","depth":20,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Summary of CVE-2026-24765: PHPUnit Insecure Deserialization","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Summary of CVE-2026-24765: PHPUnit Insecure Deserialization","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CVE-2026-24765 describes a high-severity security vulnerability in","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"PHPUnit","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", a popular testing framework for PHP. 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said","depth":23,"bounds":{"left":0.079288565,"top":0.028731046,"width":0.019946808,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"how can I fix these vulnareabilities in laravel project","depth":23,"bounds":{"left":0.13680187,"top":0.02952913,"width":0.058843084,"height":0.054668795},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":22,"bounds":{"left":0.1939827,"top":0.11731844,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":25,"bounds":{"left":0.10289229,"top":0.11971269,"width":0.030917553,"height":0.014764565},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini 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In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.","depth":24,"bounds":{"left":0.08959442,"top":0.16440542,"width":0.11386303,"height":0.12011173},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is exactly how to secure your project:","depth":24,"bounds":{"left":0.08959442,"top":0.29768556,"width":0.102726065,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Check Your Current Version","depth":23,"bounds":{"left":0.08959442,"top":0.33838788,"width":0.11502659,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. 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Run this command in your terminal at the root of your project:","depth":24,"bounds":{"left":0.08959442,"top":0.36632082,"width":0.111203454,"height":0.07861133},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Bash","depth":25,"bounds":{"left":0.094913565,"top":0.471668,"width":0.010804521,"height":0.014764565},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Download code","depth":25,"bounds":{"left":0.17536569,"top":0.46288908,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy code","depth":25,"bounds":{"left":0.18866356,"top":0.46288908,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
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[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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You said how can I fix these vulnareabilities in laravel project
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how can I fix these vulnareabilities in laravel project
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Gemini said
Gemini said
Fixing this vulnerability in a Laravel project is a very straightforward process. In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.
Here is exactly how to secure your project:
1. Check Your Current Version
1. Check Your Current Version
First, verify which version of PHPUnit your Laravel application is currently using. Run this command in your terminal at the root of your project:
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
Expand
Listen
Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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You said how can I fix these vulnareabilities in laravel project
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how can I fix these vulnareabilities in laravel project
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Gemini said
Gemini said
Fixing this vulnerability in a Laravel project is a very straightforward process. In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.
Here is exactly how to secure your project:
1. Check Your Current Version
1. Check Your Current Version
First, verify which version of PHPUnit your Laravel application is currently using. Run this command in your terminal at the root of your project:
Bash
Download code
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composer show phpunit/phpunit
Look at the
versions
line in the output to see if you are running a vulnerable version (anything lower than 12.5.8, 11.5.50, 10.5.62, 9.6.33, or 8.5.52).
2. Update PHPUnit
2. Update PHPUnit
Tell Composer to update PHPUnit and its associated dependencies to the latest secure versions allowed by your
composer.json
constraints:
Bash
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composer update phpunit/phpunit --with-dependencies
Note: If your
composer.json
restricts PHPUnit to an older major version (like
^9.0
), Composer will automatically grab the secure patch for that specific major version (e.g., 9.6.33).
3. Verify the Fix
3. Verify the Fix
Run the
composer show
command from step one again to confirm the version has been bumped. As long as your version is at or above one of the secure releases listed above, you are protected against CVE-2026-24765.
4. Secure Your Environments
4. Secure Your Environments
Because PHPUnit lives in the
require-dev
block of your
composer.json
, this vulnerability does not impact your production environment—
provided you are deploying correctly
.
Always build your production environment using
composer install --no-dev --optimize-autoloader
. This ensures testing frameworks are completely excluded from your live servers.
For your CI/CD pipelines, ensure you are using ephemeral runners (runners that spin up fresh for every job and are destroyed afterward) so that an attacker cannot leave a malicious
.coverage
file behind for a subsequent test run to execute.
Would you like me to walk you through how to verify that your production server is completely free of development dependencies?
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A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. 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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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You said how can I fix these vulnareabilities in laravel project
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how can I fix these vulnareabilities in laravel project
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Gemini said
Gemini said
Fixing this vulnerability in a Laravel project is a very straightforward process. In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.
Here is exactly how to secure your project:
1. Check Your Current Version
1. Check Your Current Version
First, verify which version of PHPUnit your Laravel application is currently using. Run this command in your terminal at the root of your project:
Bash
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composer show phpunit/phpunit
Look at the
versions
line in the output to see if you are running a vulnerable version (anything lower than 12.5.8, 11.5.50, 10.5.62, 9.6.33, or 8.5.52).
2. Update PHPUnit
2. Update PHPUnit
Tell Composer to update PHPUnit and its associated dependencies to the latest secure versions allowed by your
composer.json
constraints:
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composer update phpunit/phpunit --with-dependencies
Note: If your
composer.json
restricts PHPUnit to an older major version (like
^9.0
), Composer will automatically grab the secure patch for that specific major version (e.g., 9.6.33).
3. Verify the Fix
3. Verify the Fix
Run the
composer show
command from step one again to confirm the version has been bumped. As long as your version is at or above one of the secure releases listed above, you are protected against CVE-2026-24765.
4. Secure Your Environments
4. Secure Your Environments
Because PHPUnit lives in the
require-dev
block of your
composer.json
, this vulnerability does not impact your production environment—
provided you are deploying correctly
.
Always build your production environment using
composer install --no-dev --optimize-autoloader
. This ensures testing frameworks are completely excluded from your live servers.
For your CI/CD pipelines, ensure you are using ephemeral runners (runners that spin up fresh for every job and are destroyed afterward) so that an attacker cannot leave a malicious
.coverage
file behind for a subsequent test run to execute.
Would you like me to walk you through how to verify that your production server is completely free of development dependencies?
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Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Slack...
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Switch workspaces… (Jiminny Inc) Has new messages
Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на...
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Switch workspaces… (Jiminny Inc) Has new messages
Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
Screenshot 2026-05-13 at 11.01.01.png
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
SlackFileEditViewGoHistoryWindowHelpDOCKEIDOCKER181DEV (-zsh)О 882APP (-zshX MDOCKER (-zsh)Last login: Tue May 12 17:54:40 on consolePoetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $•HomeDMsActivityFilesLater..•Morelhl§ Support Daily - in 2h 28 m100% (C478•Wed 13 May 12:32:26ED→QDescribe what you are looking forJiminny ...Nikolay Ivanov6 0curoarlylau# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...• Messages+Direct messagesNikolay Ivanovdo James Graham. Stoyan Tanev. Galya DimitrovaP. Steliyan GeorgievLo Petko Kashinski®. Aneliya Angelovaã. Stefka Stoyanova•. Vasil Vasilev 0!Lukas Kovalik y...AppsAdd canvasO FilesLukas Kovalik 11.Today ~мен все ме праща наhttps://app.vanta.com/c/jiminny.com/employee/onboardingNikolay Ivanov 11:01 AMХм, Джейс дали не може да ти помогне?Lukas Kovalik 11:01 AMще питам James, предполагам че нямам правада мерсиNikolay Ivanov 11:01 AMмдаМОЛЯLukas Kovalik 12:13 PMНики сори, още един въпрос имамкогато ги правеше ти FE ли оправяима vulnerabilities no npmNikolay Ivanov 12:28 PMнетях ги оставямLukas Kovalik 12:29 PMаз погледнах твоя тикет и там друго нямашесамо FEкак стигна до WorkerJira CloudMessage Nikolay IvanovToast...
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whisper_backend_init_gpu: found GPU device 0: Meta whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)
tip: sign in for higher AI quotas + cloud sync:
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2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted
2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted
2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2
2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)
zsh: terminated npx screenpipe@latest record
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\n2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted\n2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted\n2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2\n2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","depth":4,"on_screen":true,"value":"whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\n2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted\n2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted\n2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2\n2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.19722222,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.19722222,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.2013889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.3940972,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.3982639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.59097224,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.5951389,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.7878472,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.7920139,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"APP (-zsh)","depth":1,"bounds":{"left":0.475,"top":0.033333335,"width":0.05138889,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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5308280150964161241
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-816202909427632672
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visual_change
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accessibility
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NULL
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whisper_backend_init_gpu: found GPU device 0: Meta whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)
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2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted
2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted
2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2
2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)
zsh: terminated npx screenpipe@latest record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $
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Slack
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Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Slack...
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Switch workspaces… (Jiminny Inc) Has new messages
Switch workspaces… (Jiminny Inc) Has new messages
Home
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general
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product_launches
random
releases
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support
thank-yous
the_people_of_jiminny
Nikolay Ivanov
James Graham
Stoyan Tanev
Galya Dimitrova
Steliyan Georgiev
Petko Kashinski
Aneliya Angelova
Stefka Stoyanova
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Jump to date
Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
Screenshot 2026-05-13 at 11.01.01.png
Toggle file
Screenshot 2026-05-13 at 11.01.01.png...
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Kovalik","depth":23,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":23,"on_screen":true,"role_description":"text"},{"role":"AXLink","text":"Today at 11:00:48 AM","depth":23,"on_screen":true,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"11:00 AM","depth":24,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"например това може ли да отвориш","depth":24,"on_screen":true,"role_description":"text"},{"role":"AXLink","text":"https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results","depth":24,"on_screen":true,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results","depth":25,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Nikolay Ivanov","depth":23,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":23,"on_screen":true,"role_description":"text"},{"role":"AXLink","text":"Today at 11:01:07 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Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
Screenshot 2026-05-13 at 11.01.01.png
Toggle file
Screenshot 2026-05-13 at 11.01.01.png
rirerox.• 0[JY-19967] Upgrade Python and liDependabot alerts • jiminny/proph# (UY-19958] Upgrade BE ibraries -liminny/app/backend-code - VantaNo NVD - cve-2026-24765Low vulnerabilities identified in paciminnylaop/backend-code - Vanta1o NVD - cve-2026-6722fuy-207731 User Pilot not receivin@ JY-19957 | Remove abanded sympTypeError: Leaque\Flysystem\FilesNew Tabu Userpilot | Ask Jiminny Report Gen(SRD-68481 Sidekick SMS issue. 1Y-199571 Unarade BE librariesJY-19957 | Remove abanded symp2 Hich vulnerabilities identified in oã(* Medium vulnerabilities identified inLow vulnerabilities identified in pa• Goodle geminiPronllesWindownvd.nist.gov/vuln/detail/cve-2026-24765••• XFixing this vulnerability in a Laravel project is avery straightforward process. In Laravel,PHPUnit is managed as a developmentdependency via Composer, so resolving theissue simply requires updating that package toa patched version.Here is exactiv now to secure vour orolect"Check Your current VersionFirst, verify which version of PHPUnit yourLaravel application is currently using. Run thiscommand in your terminal at the root of yourproject:composer show phpunit/phpunitLook at the versions line in the output to seeif you are running a vulnerable version(anything lower than 12.5.8, 11.5.50, 10.5.62,9633. 0r 85. 5212. Update PHPUnitTell Composer to update PHPUnit and itsassociared derencencies to tne latest secureversions allowed ov vour comooser. isonconstraintsEnter a prompt for GeminiAl lt can make mistakes, so double check it. Your privacy &Summarize page‹ S0 lihl 1 Support Daily- in 2h 28m100% C42 8• Wed 13 May 12:32:27XCVE-2026-24765 DetailDescriptionPHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the 'cleanupForCoverage()* method,which deserializes code coverage files without alidation, potentially allowing remote code execution if malicious ' coverage files arepresent prior to the execution of the PHPT test. The vulnerability occurs when a'.coverage' file, which should not exist before test execution,Is deserialized without the allowed_classes parameter restriction. An attacker with local file write access can place a malicious serializedobiect with a__wakeup()* method into the file system, leading to arbitrary code execution during test runs with code coverageinstrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage filesfor PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies.Rather than just silently sanitizing the input via '['allowed_classes' => false]*, the maintainer has chosen to make the anomalous stateexplicit by treating pre-existing ':coverage* files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62,9.6.33, when a'coverage* file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying theanomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeralrunners, code review enforcement, branch protection, artifact isolation, and access control.MetricsCVSS Version 4.0cuss version 3.›CUss Version 2.01NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displaved.CVSS 3.x Severity and Vector Strings:NIST. NVDBase Score: N/ANVD assessment not yet provided.CNA: GitHub, Inc.Base Score: 7.8 HIGIVector. CVSS'2 1/AV• IAC•UPR•/UI-N/S•U/C•H/IHIA•HIReferences to Advisories, Solutions, and ToolsBy selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may haveinformation that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from thispage. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed,or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned onthese sites. Please address comments about this page to [EMAIL]:/lgithuh.com/sehastianheromann/nhnunit/commit/3141742e00620e2968d3d2e732d320de76685fdahttps://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50ihtins:/loithuh.com/sehastianheromann/nhnunit/releases/tag/12_5.8lhttps://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vj3-c3rp-c85pSource(s)GitHub.IngTag(s)GitHub, Inc.GitHub, Inc.GitHuh.IncGitHub, Inc.GitHub, Inc.GitHub, Inc.Салао ватоVendor AdvisoryQUICK INFOCVE Dictionary Entry:CVE-2026-24765NVD Published Date:01/27/2026NVD Last Modified:03/03/2026Source:GitHub. Ind...
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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $
DOCKER
Close Tab
DEV (-zsh)
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APP (-zsh)
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screenpipe"
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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $
DOCKER
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DEV (-zsh)
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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $
DOCKER
Close Tab
DEV (-zsh)
Close Tab
APP (-zsh)
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-zsh
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screenpipe"
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⌥⌘1
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3477751881059350987
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click
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accessibility
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NULL
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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $
DOCKER
Close Tab
DEV (-zsh)
Close Tab
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-zsh
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screenpipe"
Close Tab
⌥⌘1
DEV (-zsh)...
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32687
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2026-05-13T09:32:34.525287+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664754525_m1.jpg...
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iTerm2
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DOCKER (-zsh)
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monitor_1
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Last login: Tue May 12 17:54:40 on console
Poetry Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $
Menu
⌥1 DOCKER (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥2 PROD (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥3 EU (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥4 STAGE (-zsh)
Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥5 QA (-zsh)
Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥6 FE (-zsh)
Last login: Tue May 12 20:12:05 on ttys005
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥7 EXT (-zsh)
DOCKER
Close Tab
DEV (-zsh)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
⌥⌘1
DOCKER (-zsh)...
|
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accessibility
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Last login: Tue May 12 17:54:40 on console
Poetry Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $
Menu
⌥1 DOCKER (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥2 PROD (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥3 EU (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥4 STAGE (-zsh)
Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥5 QA (-zsh)
Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥6 FE (-zsh)
Last login: Tue May 12 20:12:05 on ttys005
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥7 EXT (-zsh)
DOCKER
Close Tab
DEV (-zsh)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
⌥⌘1
DOCKER (-zsh)...
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NULL
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NULL
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32688
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1253
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0
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2026-05-13T09:32:34.489239+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664754489_m2.jpg...
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iTerm2
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DOCKER (-zsh)
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NULL
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monitor_2
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NULL
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NULL
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NULL
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Last login: Tue May 12 17:54:40 on console
Poetry Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $
Menu
⌥1 DOCKER (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥2 PROD (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥3 EU (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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⌥6 FE (-zsh)
Last login: Tue May 12 20:12:05 on ttys005
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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2543509300103320612
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-3403869541947225071
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click
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accessibility
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NULL
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Last login: Tue May 12 17:54:40 on console
Poetry Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $
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Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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⌥2 PROD (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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⌥4 STAGE (-zsh)
Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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Last login: Tue May 12 20:12:05 on ttys005
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
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32686
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NULL
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NULL
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NULL
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32689
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1252
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1
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2026-05-13T09:32:40.182836+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664760182_m1.jpg...
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iTerm2
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DOCKER (docker-compose)
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1
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NULL
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NULL
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NULL
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Last login: Tue May 12 17:54:40 on console
Poetry Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $ work
WARN[0000] /Users/lukas/jiminny/infrastructure/dev/docker/docker-compose.yml: the attribute `version` is obsolete, it will be ignored, please remove it to avoid potential confusion
Attaching to blackfire-1, datadog-1, jiminny_ext-1, mariadb-1, docker_lamp_1, elasticsearch, kibana, ngrok, redis
mariadb-1 | 2026-05-13 09:32:37+00:00 [Note] [Entrypoint]: Entrypoint script for MariaDB Server 1:11.4.5+maria~ubu2404 started.
redis | 1:C 13 May 2026 09:32:37.565 # oO0OoO0OoO0Oo Redis is starting oO0OoO0OoO0Oo
redis | 1:C 13 May 2026 09:32:37.566 # Redis version=5.0.14, bits=64, commit=00000000, modified=0, pid=1, just started
redis | 1:C 13 May 2026 09:32:37.566 # Configuration loaded
redis | 1:M 13 May 2026 09:32:37.572 * Running mode=standalone, port=6379.
redis | 1:M 13 May 2026 09:32:37.572 # Server initialized
redis | 1:M 13 May 2026 09:32:37.572 # WARNING you have Transparent Huge Pages (THP) support enabled in your kernel. This will create latency and memory usage issues with Redis. To fix this issue run the command 'echo never > /sys/kernel/mm/transparent_hugepage/enabled' as root, and add it to your /etc/rc.local in order to retain the setting after a reboot. Redis must be restarted after THP is disabled.
redis | 1:M 13 May 2026 09:32:37.577 * Reading RDB preamble from AOF file...
redis | 1:M 13 May 2026 09:32:37.584 * Reading the remaining AOF tail...
blackfire-1 | [2026-05-13T09:32:37Z] ERROR: The server ID parameter is not set. Please run 'blackfire-agent -register' to configure it.
blackfire-1 | usage blackfire-agent [options]
blackfire-1 | --collector="[URL_WITH_CREDENTIALS] ~ $
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Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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⌥6 FE (-zsh)
Last login: Tue May 12 20:12:05 on ttys005
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
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⌥7 EXT (-zsh)
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Close Tab
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Tue May 12 17:54:40 on console\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $ work\nWARN[0000] /Users/lukas/jiminny/infrastructure/dev/docker/docker-compose.yml: the attribute `version` is obsolete, it will be ignored, please remove it to avoid potential confusion \nAttaching to blackfire-1, datadog-1, jiminny_ext-1, mariadb-1, docker_lamp_1, elasticsearch, kibana, ngrok, redis\nmariadb-1 | 2026-05-13 09:32:37+00:00 [Note] [Entrypoint]: Entrypoint script for MariaDB Server 1:11.4.5+maria~ubu2404 started.\nredis | 1:C 13 May 2026 09:32:37.565 # oO0OoO0OoO0Oo Redis is starting oO0OoO0OoO0Oo\nredis | 1:C 13 May 2026 09:32:37.566 # Redis version=5.0.14, bits=64, commit=00000000, modified=0, pid=1, just started\nredis | 1:C 13 May 2026 09:32:37.566 # Configuration loaded\nredis | 1:M 13 May 2026 09:32:37.572 * Running mode=standalone, port=6379.\nredis | 1:M 13 May 2026 09:32:37.572 # Server initialized\nredis | 1:M 13 May 2026 09:32:37.572 # WARNING you have Transparent Huge Pages (THP) support enabled in your kernel. This will create latency and memory usage issues with Redis. To fix this issue run the command 'echo never > /sys/kernel/mm/transparent_hugepage/enabled' as root, and add it to your /etc/rc.local in order to retain the setting after a reboot. Redis must be restarted after THP is disabled.\nredis | 1:M 13 May 2026 09:32:37.577 * Reading RDB preamble from AOF file...\nredis | 1:M 13 May 2026 09:32:37.584 * Reading the remaining AOF tail...\nblackfire-1 | [2026-05-13T09:32:37Z] ERROR: The server ID parameter is not set. Please run 'blackfire-agent -register' to configure it.\nblackfire-1 | usage blackfire-agent [options]\nblackfire-1 | --collector=\"https://blackfire.io\": Sets the URL of Blackfire's data collector\nblackfire-1 | --config=\"/etc/blackfire/agent\": Sets the path to the configuration file\nblackfire-1 | -d: Prints the current configuration\nblackfire-1 | --http-proxy=\"\": Sets the HTTP proxy to use\nblackfire-1 | --https-proxy=\"\": Sets the HTTPS proxy to use\nblackfire-1 | --log-file=\"stderr\": Sets the path of the log file. Use stderr to log to stderr\nblackfire-1 | --log-level=\"1\": log verbosity level (4: debug, 3: info, 2: warning, 1: error)\nblackfire-1 | --register: Helps you with registering the agent\nblackfire-1 | --server-id=\"\": Sets the server id used to authenticate with Blackfire API\nblackfire-1 | --server-token=\"\": Sets the server token used to authenticate with Blackfire API. It is unsafe to set this from the command line\nblackfire-1 | --socket=\"unix:///var/run/blackfire/agent.sock\": Sets the socket the agent should read traces from. Possible value can be a unix socket or a TCP address. ie: unix:///var/run/blackfire/agent.sock or tcp://127.0.0.1:8307\nblackfire-1 | --test: Tests the configuration\nblackfire-1 | --timeout=\"15s\": Sets the Blackfire connection timeout\nblackfire-1 | -v: Prints the version number\njiminny_ext-1 exited with code 0\nngrok | t=2026-05-13T09:32:37+0000 lvl=info msg=\"no configuration paths supplied\"\nngrok | t=2026-05-13T09:32:37+0000 lvl=info msg=\"using configuration at default config path\" path=/home/ngrok/.ngrok2/ngrok.yml\nngrok | t=2026-05-13T09:32:37+0000 lvl=info msg=\"open config file\" path=/home/ngrok/.ngrok2/ngrok.yml err=nil\nblackfire-1 exited with code 1\nngrok | t=2026-05-13T09:32:38+0000 lvl=info msg=\"starting web service\" obj=web addr=0.0.0.0:4040\ndocker_lamp_1 | + main\ndocker_lamp_1 | + declare START_DIR\ndocker_lamp_1 | +++ realpath /scripts/init-dev\ndocker_lamp_1 | ++ dirname /scripts/init-dev\ndocker_lamp_1 | + START_DIR=/scripts\ndocker_lamp_1 | + readonly START_DIR\ndocker_lamp_1 | + source /scripts/storage_init.sh\ndocker_lamp_1 | ++ set -o errexit\ndocker_lamp_1 | ++ set -o nounset\ndocker_lamp_1 | ++ set -o pipefail\ndocker_lamp_1 | + create_bind_mount\ndocker_lamp_1 | + [[ 0 == \\1 ]]\ndocker_lamp_1 | + configure_xdebug\ndocker_lamp_1 | + j2 /root/.j2_templates/xdebug/xdebug.ini.j2\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Warn] [Entrypoint]: /sys/fs/cgroup///memory.pressure not writable, functionality unavailable to MariaDB\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Note] [Entrypoint]: Switching to dedicated user 'mysql'\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Note] [Entrypoint]: Entrypoint script for MariaDB Server 1:11.4.5+maria~ubu2404 started.\ndatadog-1 | [s6-init] making user provided files available at /var/run/s6/etc...exited 0.\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Note] [Entrypoint]: MariaDB upgrade information missing, assuming required\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Note] [Entrypoint]: MariaDB upgrade (mariadb-upgrade or creating healthcheck users) required, but skipped due to $MARIADB_AUTO_UPGRADE setting\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Starting MariaDB 11.4.5-MariaDB-ubu2404 source revision 0771110266ff5c04216af4bf1243c65f8c67ccf4 server_uid UT4e/Q7DXxpdxE93lDWrGEmx8k4= as process 1\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"tunnel session started\" obj=tunnels.session\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"client session established\" obj=csess id=d78faaaa34a6\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Compressed tables use zlib 1.3\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Number of transaction pools: 1\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Using ARMv8 crc32 + pmull instructions\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Using liburing\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Initializing buffer pool, total size = 128.000MiB, chunk size = 2.000MiB\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Completed initialization of buffer pool\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: File system buffers for log disabled (block size=512 bytes)\ndocker_lamp_1 | + configure_blackfire\ndocker_lamp_1 | + j2 /root/.j2_templates/blackfire/extension.ini.j2\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Starting crash recovery from checkpoint LSN=7627782077\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"started tunnel\" obj=tunnels name=\"command_line (http)\" addr=http://lamp:3080 url=http://lukask.ngrok.io\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"started tunnel\" obj=tunnels name=command_line addr=http://lamp:3080 url=https://lukask.ngrok.io\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: End of log at LSN=7645587952\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"update available\" obj=updater\ndocker_lamp_1 | + j2 /root/.j2_templates/blackfire/cli.ini.j2\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: To recover: 523 pages\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Last binlog file './mysql-bin.000150', position 6361306\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Opened 3 undo tablespaces\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: 128 rollback segments in 3 undo tablespaces are active.\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Removed temporary tablespace data file: \"./ibtmp1\"\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Setting file './ibtmp1' size to 12.000MiB. Physically writing the file full; Please wait ...\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: File './ibtmp1' size is now 12.000MiB.\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: log sequence number 7645587952; transaction id 11512002\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Loading buffer pool(s) from /var/lib/mysql/ib_buffer_pool\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Plugin 'FEEDBACK' is disabled.\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Plugin 'wsrep-provider' is disabled.\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Recovering after a crash using tc.log\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Starting table crash recovery...\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Crash table recovery finished.\ndocker_lamp_1 | + declare EMPTY_DB\ndocker_lamp_1 | + db_is_empty\ndocker_lamp_1 | ++ find /var/lib/mysql/ -maxdepth 1\ndocker_lamp_1 | ++ wc -l\ndocker_lamp_1 | + [[ 11 -lt 5 ]]\ndocker_lamp_1 | + EMPTY_DB=0\ndocker_lamp_1 | + readonly EMPTY_DB\ndocker_lamp_1 | + [[ 0 -eq 1 ]]\ndocker_lamp_1 | + [[ local == \\l\\o\\c\\a\\l ]]\ndocker_lamp_1 | + set_nginx_domain dev.jiminny.com\ndocker_lamp_1 | + declare -r DOMAIN_NAME=dev.jiminny.com\ndocker_lamp_1 | + cp -f /etc/nginx/nginx_template.conf /etc/nginx/nginx.conf\ndocker_lamp_1 | + sed -i -E s~_JIMINNY_DOMAIN~app.dev.jiminny.com~g /etc/nginx/nginx.conf\ndocker_lamp_1 | + sed -i -E s~_JIMINNY_EXT_DOMAIN~ext.dev.jiminny.com~g /etc/nginx/nginx.conf\ndocker_lamp_1 | + sed -i -E s~_JIMINNY_WEB_DOMAIN~www.dev.jiminny.com~g /etc/nginx/nginx.conf\ndocker_lamp_1 | + [[ -n 3399 ]]\ndocker_lamp_1 | + sed -i -E 's~http:\\/\\/jiminny_ext:8080~http://jiminny_ext:3399~g' /etc/nginx/nginx.conf\ndocker_lamp_1 | + [[ -n host.docker.internal ]]\ndocker_lamp_1 | + sed -i -E 's~http:\\/\\/jiminny_ext~http://host.docker.internal~g' /etc/nginx/nginx.conf\ndocker_lamp_1 | + build_dev\ndocker_lamp_1 | + cd /home/jiminny/\ndocker_lamp_1 | + create_dot_env_local_file\ndocker_lamp_1 | + cp -f /home/jiminny/.env.local /home/jiminny/.env.local.bak\ndocker_lamp_1 | + create_dot_env\ndocker_lamp_1 | + [[ -f /home/jiminny/.env ]]\ndocker_lamp_1 | + return\ndocker_lamp_1 | + declare DB_ADMIN_PASSWORD\ndocker_lamp_1 | + declare DB_ADMIN_USERNAME\ndocker_lamp_1 | + declare DB_DEV_PASSWORD\ndocker_lamp_1 | + declare DB_DEV_USERNAME\ndocker_lamp_1 | + declare DB_ROOT_PASSWORD\ndocker_lamp_1 | + declare DB_ROOT_USERNAME\ndocker_lamp_1 | + declare DB_WEB_PASSWORD\ndocker_lamp_1 | + declare DB_WEB_USERNAME\ndocker_lamp_1 | ++ jq -r .DB_ADMIN_PASSWORD /home/jiminny/dev.json\ndocker_lamp_1 | + DB_ADMIN_PASSWORD='dgyt$rTe21-d'\ndocker_lamp_1 | ++ jq -r .DB_ADMIN_USERNAME /home/jiminny/dev.json\ndocker_lamp_1 | + DB_ADMIN_USERNAME=jmnyadmin\ndocker_lamp_1 | ++ jq -r .DB_DEV_PASSWORD /home/jiminny/dev.json\ndatadog-1 | [s6-init] ensuring user provided files have correct perms...exited 0.\nmariadb-1 | 2026-05-13 9:32:40 0 [Note] InnoDB: Buffer pool(s) load completed at 260513 9:32:40\ndocker_lamp_1 | + DB_DEV_PASSWORD=rTr4sdQA65-Ad\ndocker_lamp_1 | ++ jq -r .DB_DEV_USERNAME /home/jiminny/dev.json\ndocker_lamp_1 | + DB_DEV_USERNAME=jmnydev\ndocker_lamp_1 | ++ jq -r .DB_ROOT_PASSWORD /home/jiminny/dev.json\ndatadog-1 | [fix-attrs.d] applying ownership & permissions fixes...\ndocker_lamp_1 | + DB_ROOT_PASSWORD=b7h5-1fH3e54J\n\n\nv View in Docker Desktop o View Config w Enable Watch","depth":4,"on_screen":true,"value":"Last login: Tue May 12 17:54:40 on console\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $ work\nWARN[0000] /Users/lukas/jiminny/infrastructure/dev/docker/docker-compose.yml: the attribute `version` is obsolete, it will be ignored, please remove it to avoid potential confusion \nAttaching to blackfire-1, datadog-1, jiminny_ext-1, mariadb-1, docker_lamp_1, elasticsearch, kibana, ngrok, redis\nmariadb-1 | 2026-05-13 09:32:37+00:00 [Note] [Entrypoint]: Entrypoint script for MariaDB Server 1:11.4.5+maria~ubu2404 started.\nredis | 1:C 13 May 2026 09:32:37.565 # oO0OoO0OoO0Oo Redis is starting oO0OoO0OoO0Oo\nredis | 1:C 13 May 2026 09:32:37.566 # Redis version=5.0.14, bits=64, commit=00000000, modified=0, pid=1, just started\nredis | 1:C 13 May 2026 09:32:37.566 # Configuration loaded\nredis | 1:M 13 May 2026 09:32:37.572 * Running mode=standalone, port=6379.\nredis | 1:M 13 May 2026 09:32:37.572 # Server initialized\nredis | 1:M 13 May 2026 09:32:37.572 # WARNING you have Transparent Huge Pages (THP) support enabled in your kernel. This will create latency and memory usage issues with Redis. To fix this issue run the command 'echo never > /sys/kernel/mm/transparent_hugepage/enabled' as root, and add it to your /etc/rc.local in order to retain the setting after a reboot. Redis must be restarted after THP is disabled.\nredis | 1:M 13 May 2026 09:32:37.577 * Reading RDB preamble from AOF file...\nredis | 1:M 13 May 2026 09:32:37.584 * Reading the remaining AOF tail...\nblackfire-1 | [2026-05-13T09:32:37Z] ERROR: The server ID parameter is not set. Please run 'blackfire-agent -register' to configure it.\nblackfire-1 | usage blackfire-agent [options]\nblackfire-1 | --collector=\"https://blackfire.io\": Sets the URL of Blackfire's data collector\nblackfire-1 | --config=\"/etc/blackfire/agent\": Sets the path to the configuration file\nblackfire-1 | -d: Prints the current configuration\nblackfire-1 | --http-proxy=\"\": Sets the HTTP proxy to use\nblackfire-1 | --https-proxy=\"\": Sets the HTTPS proxy to use\nblackfire-1 | --log-file=\"stderr\": Sets the path of the log file. Use stderr to log to stderr\nblackfire-1 | --log-level=\"1\": log verbosity level (4: debug, 3: info, 2: warning, 1: error)\nblackfire-1 | --register: Helps you with registering the agent\nblackfire-1 | --server-id=\"\": Sets the server id used to authenticate with Blackfire API\nblackfire-1 | --server-token=\"\": Sets the server token used to authenticate with Blackfire API. It is unsafe to set this from the command line\nblackfire-1 | --socket=\"unix:///var/run/blackfire/agent.sock\": Sets the socket the agent should read traces from. Possible value can be a unix socket or a TCP address. ie: unix:///var/run/blackfire/agent.sock or tcp://127.0.0.1:8307\nblackfire-1 | --test: Tests the configuration\nblackfire-1 | --timeout=\"15s\": Sets the Blackfire connection timeout\nblackfire-1 | -v: Prints the version number\njiminny_ext-1 exited with code 0\nngrok | t=2026-05-13T09:32:37+0000 lvl=info msg=\"no configuration paths supplied\"\nngrok | t=2026-05-13T09:32:37+0000 lvl=info msg=\"using configuration at default config path\" path=/home/ngrok/.ngrok2/ngrok.yml\nngrok | t=2026-05-13T09:32:37+0000 lvl=info msg=\"open config file\" path=/home/ngrok/.ngrok2/ngrok.yml err=nil\nblackfire-1 exited with code 1\nngrok | t=2026-05-13T09:32:38+0000 lvl=info msg=\"starting web service\" obj=web addr=0.0.0.0:4040\ndocker_lamp_1 | + main\ndocker_lamp_1 | + declare START_DIR\ndocker_lamp_1 | +++ realpath /scripts/init-dev\ndocker_lamp_1 | ++ dirname /scripts/init-dev\ndocker_lamp_1 | + START_DIR=/scripts\ndocker_lamp_1 | + readonly START_DIR\ndocker_lamp_1 | + source /scripts/storage_init.sh\ndocker_lamp_1 | ++ set -o errexit\ndocker_lamp_1 | ++ set -o nounset\ndocker_lamp_1 | ++ set -o pipefail\ndocker_lamp_1 | + create_bind_mount\ndocker_lamp_1 | + [[ 0 == \\1 ]]\ndocker_lamp_1 | + configure_xdebug\ndocker_lamp_1 | + j2 /root/.j2_templates/xdebug/xdebug.ini.j2\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Warn] [Entrypoint]: /sys/fs/cgroup///memory.pressure not writable, functionality unavailable to MariaDB\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Note] [Entrypoint]: Switching to dedicated user 'mysql'\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Note] [Entrypoint]: Entrypoint script for MariaDB Server 1:11.4.5+maria~ubu2404 started.\ndatadog-1 | [s6-init] making user provided files available at /var/run/s6/etc...exited 0.\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Note] [Entrypoint]: MariaDB upgrade information missing, assuming required\nmariadb-1 | 2026-05-13 09:32:38+00:00 [Note] [Entrypoint]: MariaDB upgrade (mariadb-upgrade or creating healthcheck users) required, but skipped due to $MARIADB_AUTO_UPGRADE setting\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Starting MariaDB 11.4.5-MariaDB-ubu2404 source revision 0771110266ff5c04216af4bf1243c65f8c67ccf4 server_uid UT4e/Q7DXxpdxE93lDWrGEmx8k4= as process 1\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"tunnel session started\" obj=tunnels.session\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"client session established\" obj=csess id=d78faaaa34a6\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Compressed tables use zlib 1.3\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Number of transaction pools: 1\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Using ARMv8 crc32 + pmull instructions\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Using liburing\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Initializing buffer pool, total size = 128.000MiB, chunk size = 2.000MiB\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Completed initialization of buffer pool\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: File system buffers for log disabled (block size=512 bytes)\ndocker_lamp_1 | + configure_blackfire\ndocker_lamp_1 | + j2 /root/.j2_templates/blackfire/extension.ini.j2\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Starting crash recovery from checkpoint LSN=7627782077\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"started tunnel\" obj=tunnels name=\"command_line (http)\" addr=http://lamp:3080 url=http://lukask.ngrok.io\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"started tunnel\" obj=tunnels name=command_line addr=http://lamp:3080 url=https://lukask.ngrok.io\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: End of log at LSN=7645587952\nngrok | t=2026-05-13T09:32:39+0000 lvl=info msg=\"update available\" obj=updater\ndocker_lamp_1 | + j2 /root/.j2_templates/blackfire/cli.ini.j2\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: To recover: 523 pages\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Last binlog file './mysql-bin.000150', position 6361306\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Opened 3 undo tablespaces\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: 128 rollback segments in 3 undo tablespaces are active.\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Removed temporary tablespace data file: \"./ibtmp1\"\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Setting file './ibtmp1' size to 12.000MiB. Physically writing the file full; Please wait ...\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: File './ibtmp1' size is now 12.000MiB.\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: log sequence number 7645587952; transaction id 11512002\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] InnoDB: Loading buffer pool(s) from /var/lib/mysql/ib_buffer_pool\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Plugin 'FEEDBACK' is disabled.\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Plugin 'wsrep-provider' is disabled.\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Recovering after a crash using tc.log\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Starting table crash recovery...\nmariadb-1 | 2026-05-13 9:32:39 0 [Note] Crash table recovery finished.\ndocker_lamp_1 | + declare EMPTY_DB\ndocker_lamp_1 | + db_is_empty\ndocker_lamp_1 | ++ find /var/lib/mysql/ -maxdepth 1\ndocker_lamp_1 | ++ wc -l\ndocker_lamp_1 | + [[ 11 -lt 5 ]]\ndocker_lamp_1 | + EMPTY_DB=0\ndocker_lamp_1 | + readonly EMPTY_DB\ndocker_lamp_1 | + [[ 0 -eq 1 ]]\ndocker_lamp_1 | + [[ local == \\l\\o\\c\\a\\l ]]\ndocker_lamp_1 | + set_nginx_domain dev.jiminny.com\ndocker_lamp_1 | + declare -r DOMAIN_NAME=dev.jiminny.com\ndocker_lamp_1 | + cp -f /etc/nginx/nginx_template.conf /etc/nginx/nginx.conf\ndocker_lamp_1 | + sed -i -E s~_JIMINNY_DOMAIN~app.dev.jiminny.com~g /etc/nginx/nginx.conf\ndocker_lamp_1 | + sed -i -E s~_JIMINNY_EXT_DOMAIN~ext.dev.jiminny.com~g /etc/nginx/nginx.conf\ndocker_lamp_1 | + sed -i -E s~_JIMINNY_WEB_DOMAIN~www.dev.jiminny.com~g /etc/nginx/nginx.conf\ndocker_lamp_1 | + [[ -n 3399 ]]\ndocker_lamp_1 | + sed -i -E 's~http:\\/\\/jiminny_ext:8080~http://jiminny_ext:3399~g' /etc/nginx/nginx.conf\ndocker_lamp_1 | + [[ -n host.docker.internal ]]\ndocker_lamp_1 | + sed -i -E 's~http:\\/\\/jiminny_ext~http://host.docker.internal~g' /etc/nginx/nginx.conf\ndocker_lamp_1 | + build_dev\ndocker_lamp_1 | + cd /home/jiminny/\ndocker_lamp_1 | + create_dot_env_local_file\ndocker_lamp_1 | + cp -f /home/jiminny/.env.local /home/jiminny/.env.local.bak\ndocker_lamp_1 | + create_dot_env\ndocker_lamp_1 | + [[ -f /home/jiminny/.env ]]\ndocker_lamp_1 | + return\ndocker_lamp_1 | + declare DB_ADMIN_PASSWORD\ndocker_lamp_1 | + declare DB_ADMIN_USERNAME\ndocker_lamp_1 | + declare DB_DEV_PASSWORD\ndocker_lamp_1 | + declare DB_DEV_USERNAME\ndocker_lamp_1 | + declare DB_ROOT_PASSWORD\ndocker_lamp_1 | + declare DB_ROOT_USERNAME\ndocker_lamp_1 | + declare DB_WEB_PASSWORD\ndocker_lamp_1 | + declare DB_WEB_USERNAME\ndocker_lamp_1 | ++ jq -r .DB_ADMIN_PASSWORD /home/jiminny/dev.json\ndocker_lamp_1 | + DB_ADMIN_PASSWORD='dgyt$rTe21-d'\ndocker_lamp_1 | ++ jq -r .DB_ADMIN_USERNAME /home/jiminny/dev.json\ndocker_lamp_1 | + DB_ADMIN_USERNAME=jmnyadmin\ndocker_lamp_1 | ++ jq -r .DB_DEV_PASSWORD /home/jiminny/dev.json\ndatadog-1 | [s6-init] ensuring user provided files have correct perms...exited 0.\nmariadb-1 | 2026-05-13 9:32:40 0 [Note] InnoDB: Buffer pool(s) load completed at 260513 9:32:40\ndocker_lamp_1 | + DB_DEV_PASSWORD=rTr4sdQA65-Ad\ndocker_lamp_1 | ++ jq -r .DB_DEV_USERNAME /home/jiminny/dev.json\ndocker_lamp_1 | + DB_DEV_USERNAME=jmnydev\ndocker_lamp_1 | ++ jq -r .DB_ROOT_PASSWORD /home/jiminny/dev.json\ndatadog-1 | [fix-attrs.d] applying ownership & permissions fixes...\ndocker_lamp_1 | + DB_ROOT_PASSWORD=b7h5-1fH3e54J\n\n\nv View in Docker Desktop o View Config w Enable Watch","is_focused":true},{"role":"AXButton","text":"Menu","depth":3,"bounds":{"left":0.48541668,"top":0.08944444,"width":0.010416667,"height":0.016666668},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false},{"role":"AXStaticText","text":"⌥1 DOCKER (docker-compose)","depth":3,"bounds":{"left":0.01875,"top":0.09,"width":0.46319443,"height":0.015555556},"on_screen":true,"role_description":"text"},{"role":"AXTextArea","text":"Last login: Tue May 12 17:54:40 on console\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml 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its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $","is_focused":true},{"role":"AXButton","text":"Menu","depth":4,"bounds":{"left":0.98680556,"top":0.55277777,"width":0.010416667,"height":0.016666668},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false},{"role":"AXStaticText","text":"⌥5 QA (-zsh)","depth":4,"bounds":{"left":0.51944447,"top":0.55333334,"width":0.46388888,"height":0.015555556},"on_screen":true,"role_description":"text"},{"role":"AXTextArea","text":"Last login: Tue May 12 20:12:05 on ttys001\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ 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its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $","is_focused":true},{"role":"AXButton","text":"Menu","depth":4,"bounds":{"left":0.98680556,"top":0.7027778,"width":0.010416667,"height":0.016666668},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false},{"role":"AXStaticText","text":"⌥6 FE (-zsh)","depth":4,"bounds":{"left":0.51944447,"top":0.7033333,"width":0.46388888,"height":0.015555556},"on_screen":true,"role_description":"text"},{"role":"AXTextArea","text":"Last login: Tue May 12 20:12:05 on ttys005\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ 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parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $","is_focused":true},{"role":"AXButton","text":"Menu","depth":4,"bounds":{"left":0.98680556,"top":0.8572222,"width":0.010416667,"height":0.016666668},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false},{"role":"AXStaticText","text":"⌥7 EXT (-zsh)","depth":4,"bounds":{"left":0.51944447,"top":0.8577778,"width":0.46388888,"height":0.015555556},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.19722222,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close 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(docker-compose)","depth":1,"bounds":{"left":0.43680555,"top":0.033333335,"width":0.12708333,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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2977969990322141976
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-3169896766622397047
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visual_change
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accessibility
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NULL
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Last login: Tue May 12 17:54:40 on console
Poetry Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/infrastructure/dev/docker or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/infrastructure/dev/docker (develop) $ work
WARN[0000] /Users/lukas/jiminny/infrastructure/dev/docker/docker-compose.yml: the attribute `version` is obsolete, it will be ignored, please remove it to avoid potential confusion
Attaching to blackfire-1, datadog-1, jiminny_ext-1, mariadb-1, docker_lamp_1, elasticsearch, kibana, ngrok, redis
mariadb-1 | 2026-05-13 09:32:37+00:00 [Note] [Entrypoint]: Entrypoint script for MariaDB Server 1:11.4.5+maria~ubu2404 started.
redis | 1:C 13 May 2026 09:32:37.565 # oO0OoO0OoO0Oo Redis is starting oO0OoO0OoO0Oo
redis | 1:C 13 May 2026 09:32:37.566 # Redis version=5.0.14, bits=64, commit=00000000, modified=0, pid=1, just started
redis | 1:C 13 May 2026 09:32:37.566 # Configuration loaded
redis | 1:M 13 May 2026 09:32:37.572 * Running mode=standalone, port=6379.
redis | 1:M 13 May 2026 09:32:37.572 # Server initialized
redis | 1:M 13 May 2026 09:32:37.572 # WARNING you have Transparent Huge Pages (THP) support enabled in your kernel. This will create latency and memory usage issues with Redis. To fix this issue run the command 'echo never > /sys/kernel/mm/transparent_hugepage/enabled' as root, and add it to your /etc/rc.local in order to retain the setting after a reboot. Redis must be restarted after THP is disabled.
redis | 1:M 13 May 2026 09:32:37.577 * Reading RDB preamble from AOF file...
redis | 1:M 13 May 2026 09:32:37.584 * Reading the remaining AOF tail...
blackfire-1 | [2026-05-13T09:32:37Z] ERROR: The server ID parameter is not set. Please run 'blackfire-agent -register' to configure it.
blackfire-1 | usage blackfire-agent [options]
blackfire-1 | --collector="[URL_WITH_CREDENTIALS] ~ $
Menu
⌥2 PROD (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥3 EU (-zsh)
Last login: Tue May 12 17:54:40 on console
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥4 STAGE (-zsh)
Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥5 QA (-zsh)
Last login: Tue May 12 20:12:05 on ttys001
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥6 FE (-zsh)
Last login: Tue May 12 20:12:05 on ttys005
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $
Menu
⌥7 EXT (-zsh)
DOCKER
Close Tab
DEV (-zsh)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
⌥⌘1
DOCKER (docker-compose)...
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1252
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2026-05-13T09:32:43.194031+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664763194_m1.jpg...
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iTerm2
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PhpStorm>0 lhl§ Support Daily - in 2h 28 m100% PhpStorm>0 lhl§ Support Daily - in 2h 28 m100% C8•Wed 13 May 12:32:43DOCKER (docker-compose)APP (-zsh)DOCKER181DEV (-zsh)₴82DOCKER (docker-compose)docker_lamp_1docker_lamp_1+ cp -f /home/jiminny/.env /home/jiminny/.env.root+ cp -f /home/jiminny/.env /home/jiminny/.env.migratedocker_lamp_1+ sed-i-E 's~[ENV_SECRET] /home/jiminny/.env.migratedocker_lamp_1I + sed-i-E 's~[ENV_SECRET] /home/jiminny/.env.rootdocker_lamp_1I + sed-i-E 's~DB_USERNAME=. *S~DB_USERNAME=root~g' /home/jiminny/.env.migratedocker_1amp_1I + sed-i -E 's~DB_USERNAME=. *S~DFootdatadog-1datadog-1-zsh84screenpipe"XIPROD (-zsh)Last login: Tue May 12 17:54:40 on consolePoetry could not find a pyproject.toml file in /Users/lukas or its parentsdatadog-1t containerdatadog-1---------0datadog-1docker_lamp_1docker_lamp_1docker_lamp_1docker_lamp_1docker_lamp_1docker_1amp_1docker_lamp_1docker_1amp_1docker_Lamp_1docker_lamp_1docker_Lamp_1docker_lamp_1docker_lamp_1docker_lamp_1datadog-1mariadb-1mariadb-1datadog-1mariadb-1mariadb-1mariadb-1ort: 3306Poetry could notfind a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ||23 EU (-zsh)1aлin:1217•54•40 an cAncolefile in /Users/lukas or its parentsI You must set an DD_API_KEY envir‹PhpStormfile in /Users/lukas or its parents2026.1ole+ cp -f/home/jiminny/.env /home,+ echo..+ echo'[ENV_SECRET] + echo DB_ADMIN_USERNAME=jmnyadmechoDB_DEV_PASSWORD=[PASSWORD] echoDB_DEV_USERNAME=jmnydevechoDB_ROOT_PASSWORD=[PASSWORD] DB_ROOT_USERNAME=root+ echoDB_WEB_PASSWORD=[PASSWORD] JETBRAINS IDESechoDB_WEB_USERNAME=jmnyweb+ [[ false== \f\a\l\s\e ]]+ declare COMPOSER_PARAM=--prefer+ [[ 0 -eq 1 ]]+ composerinstall --prefer-dist[cont-init.d] 01-check-apikey.sh: exited 1.2026-05-13[Note] Server socket created on IP:[IP_ADDRESS]'.2026-05-139:32:41 0 [Note]Server socket createdwith code2026-05-13mariadbd: Event Scheduler: Loaded 0 events2026-05-139:32:41 0 [Note]mariadbd: ready for connections.Version:'11.4.5-MariaDB-ubu2404'socket: '/run/mysqld/mysqld.sock'mariadb.org binary distributionfile in /Users/lukas or its parentsfile in /Users/lukas or its parents$001file in /Users/lukas or its parentsfile in /Users/lukas or its parents~ $ 0Last login: Tue May 12 20:12:05 on ttys001L881О 85PRODSTAGEPoetry could not find a pyproject.toml file in /Users/lukas or its parentsFRONTENDPoetry could notfind a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ lX 27 EXT (-zsh)Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEXTENSIONView in Docker Desktopo View ConfigEnable WatchPoetrycould not find a pyproject.tomlfile in /Users/lukas or its parentsas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I...
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7045211855937872431
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ocr
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PhpStorm>0 lhl§ Support Daily - in 2h 28 m100% PhpStorm>0 lhl§ Support Daily - in 2h 28 m100% C8•Wed 13 May 12:32:43DOCKER (docker-compose)APP (-zsh)DOCKER181DEV (-zsh)₴82DOCKER (docker-compose)docker_lamp_1docker_lamp_1+ cp -f /home/jiminny/.env /home/jiminny/.env.root+ cp -f /home/jiminny/.env /home/jiminny/.env.migratedocker_lamp_1+ sed-i-E 's~[ENV_SECRET] /home/jiminny/.env.migratedocker_lamp_1I + sed-i-E 's~[ENV_SECRET] /home/jiminny/.env.rootdocker_lamp_1I + sed-i-E 's~DB_USERNAME=. *S~DB_USERNAME=root~g' /home/jiminny/.env.migratedocker_1amp_1I + sed-i -E 's~DB_USERNAME=. *S~DFootdatadog-1datadog-1-zsh84screenpipe"XIPROD (-zsh)Last login: Tue May 12 17:54:40 on consolePoetry could not find a pyproject.toml file in /Users/lukas or its parentsdatadog-1t containerdatadog-1---------0datadog-1docker_lamp_1docker_lamp_1docker_lamp_1docker_lamp_1docker_lamp_1docker_1amp_1docker_lamp_1docker_1amp_1docker_Lamp_1docker_lamp_1docker_Lamp_1docker_lamp_1docker_lamp_1docker_lamp_1datadog-1mariadb-1mariadb-1datadog-1mariadb-1mariadb-1mariadb-1ort: 3306Poetry could notfind a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ||23 EU (-zsh)1aлin:1217•54•40 an cAncolefile in /Users/lukas or its parentsI You must set an DD_API_KEY envir‹PhpStormfile in /Users/lukas or its parents2026.1ole+ cp -f/home/jiminny/.env /home,+ echo..+ echo'[ENV_SECRET] + echo DB_ADMIN_USERNAME=jmnyadmechoDB_DEV_PASSWORD=[PASSWORD] echoDB_DEV_USERNAME=jmnydevechoDB_ROOT_PASSWORD=[PASSWORD] DB_ROOT_USERNAME=root+ echoDB_WEB_PASSWORD=[PASSWORD] JETBRAINS IDESechoDB_WEB_USERNAME=jmnyweb+ [[ false== \f\a\l\s\e ]]+ declare COMPOSER_PARAM=--prefer+ [[ 0 -eq 1 ]]+ composerinstall --prefer-dist[cont-init.d] 01-check-apikey.sh: exited 1.2026-05-13[Note] Server socket created on IP:[IP_ADDRESS]'.2026-05-139:32:41 0 [Note]Server socket createdwith code2026-05-13mariadbd: Event Scheduler: Loaded 0 events2026-05-139:32:41 0 [Note]mariadbd: ready for connections.Version:'11.4.5-MariaDB-ubu2404'socket: '/run/mysqld/mysqld.sock'mariadb.org binary distributionfile in /Users/lukas or its parentsfile in /Users/lukas or its parents$001file in /Users/lukas or its parentsfile in /Users/lukas or its parents~ $ 0Last login: Tue May 12 20:12:05 on ttys001L881О 85PRODSTAGEPoetry could not find a pyproject.toml file in /Users/lukas or its parentsFRONTENDPoetry could notfind a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ lX 27 EXT (-zsh)Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEXTENSIONView in Docker Desktopo View ConfigEnable WatchPoetrycould not find a pyproject.tomlfile in /Users/lukas or its parentsas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I...
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32691
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1253
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1
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2026-05-13T09:32:44.381173+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664764381_m2.jpg...
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PhpStorm
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monitor_2
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7119662012421193447
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visual_change
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32692
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1253
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2
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2026-05-13T09:32:47.443824+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664767443_m2.jpg...
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PhpStorm
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1
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PhpStorm30 liil• suppont Dally • In 2n 20m100% LzW PhpStorm30 liil• suppont Dally • In 2n 20m100% LzWed 13 May 12:32:47Search Everywhere DoubleCato Cila 9eDRecent Files 9ENavigation Bar 7KDrop files here to open them...
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8453832789741480669
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PhpStorm30 liil• suppont Dally • In 2n 20m100% LzW PhpStorm30 liil• suppont Dally • In 2n 20m100% LzWed 13 May 12:32:47Search Everywhere DoubleCato Cila 9eDRecent Files 9ENavigation Bar 7KDrop files here to open them...
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32691
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32693
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1252
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3
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2026-05-13T09:32:49.243207+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664769243_m1.jpg...
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PhpStorm
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1
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NULL
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monitor_1
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PhpStormFileEditViewNavigateCodeLaravelRefactorRun PhpStormFileEditViewNavigateCodeLaravelRefactorRunToolsWindowHelp(alol• Support Daily - in 2 h 28 m100% C8• Wed 13 May12:32:49DOCKER (docker-compose)181DOCKER$81DEV (-zsh)₴82APP (-zsh)11DOCKER (docker-compose)docker_lamp_1echodocker_lamp_1DB_ROOT_PASSWORD=[PASSWORD] echo DB_WEB_USERNAME= jmnywebdocker_lamp_1docker_1amp_1+ [[ false == \f\a\l\s\e ]]+ declare COMPOSER_PARAM=--prefer-distCKERdocker_lamp_1+ [[ 0 -eq 1 ]]docker_lamp_1+ composer install --prefer-distdatadog-1[cont-init.d] 01-check-apikey.shmariadb-12026-05-139:32:41 0[Note]Sersmariadb-12026-05-139:32:41 0 [Note]Serdatadog-1exitedwith code 1mariadb-12026-05-139:32:41 0 [Note]mar-mariadb-12026-05-139:32:41[Note]marmariadb-1Version:'11.4.5-MariaDB-ubu2404PhpStormort: 3306mariadb.org binarydistribution2026.1elasticsearchI {"type": "server""timestamp":NFO","component" : "o.e.n.Node", "cluster.name":73a4f","message": "version[7.10.2], pid[6], builr59143c1f785afa92b9/2021-01-13T04:42:47.1572772], ([AdoptOpenJDK/OpenJDK 64-Bit Server VM/15.0.1/15.(elasticsearch1 {"type": "server"., "timestamp":NFO""component" : "o.e.n.Node", "cluster.name":73a4f"', "message": "JVM home [/usr/share/elasticsrelasticsearchNFO",1 {"type": "server", "timestamp" :"component": "o.e.n.Node", "cluster.name":L JETBRAINS IDES73a4f""message": "JVM arguments [-Xshare:auto,networkaddress.cache.negative.ttl=10, -XX:+Alwayslrue, -Dfile.encoding=UTF-8, -Djna.nosys=true, -XXodeDetailsInExceptionMessages,=true, -Dio.netty.recycler.maxCapacityPerThread=0,-UIU.IICLLY•ULLULULUI • RUMIVLICLLMICIIUS--Dlog4j.shutdownHookEnabled=false, -Dlog4j2.disable.jmx=true, -Djava.locale.providers=SPI, COMPAT, -Xms1g, -Xmx1g, -XX:+UseG1GC, -XX:G1ReservePercent=25, -XX:InitiatingHeap0ccupancyPercent=30, -Djava.io.tmpdir=/tmp/elasticsearch-10798175557550719749, -XX:+HeapDumpOnOut0fMemoryError, -XX:HeapDumpPath=data, -XX:ErrorFile=logs/hs_err_pid%p.1og, -Xlog:gc*,gc+age=trace,safepoint:file=logs/gc.log:utctime,pid,tags:filecount=32,filesize=64m,-Des.cgroups.hierarchy.override=/, -Xms700m, -Xmx700m, -XX:MaxDirectMemorySize=367001600, -Des.path.home=/usr/share/elasticsearch, -Des.path.conf=/usr/share/elasticsearch/confi-Des.distribution.flavor=default, -Des.distribution.type=docker, -Des.bundled_jdk=tru*3-zshXIPROD (-zsh)Last login: Tue May 12 17:54:40 on console84screenpipe"Poetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could notfind a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ [X T3 EU (-zsh)waet1aлin:Mav1217•54•40 An cAncolefile in /Users/lukas or its parentsfile in /Users/lukas or its parentsolefile in /Users/lukas or its parentsfile in /Users/lukas or its parents$001file in /Users/lukas or its parentsfile in /Users/lukas or its parents~ $ 0Last login: Tue May 12 20:12:05 on ttys001О 85PRODSTAGEPoetry could not find a pyproject.toml file in /Users/lukas or its parentsFRONTENDPoetry could notfind a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ lX 27 EXT (-zsh)Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEXTENSIONView in Docker Desktop• View Configw Enable WatchPoetrycould not find a pyproject.tomlfile in /Users/lukas or its parentsas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I...
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5979669608414602131
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PhpStormFileEditViewNavigateCodeLaravelRefactorRun PhpStormFileEditViewNavigateCodeLaravelRefactorRunToolsWindowHelp(alol• Support Daily - in 2 h 28 m100% C8• Wed 13 May12:32:49DOCKER (docker-compose)181DOCKER$81DEV (-zsh)₴82APP (-zsh)11DOCKER (docker-compose)docker_lamp_1echodocker_lamp_1DB_ROOT_PASSWORD=[PASSWORD] echo DB_WEB_USERNAME= jmnywebdocker_lamp_1docker_1amp_1+ [[ false == \f\a\l\s\e ]]+ declare COMPOSER_PARAM=--prefer-distCKERdocker_lamp_1+ [[ 0 -eq 1 ]]docker_lamp_1+ composer install --prefer-distdatadog-1[cont-init.d] 01-check-apikey.shmariadb-12026-05-139:32:41 0[Note]Sersmariadb-12026-05-139:32:41 0 [Note]Serdatadog-1exitedwith code 1mariadb-12026-05-139:32:41 0 [Note]mar-mariadb-12026-05-139:32:41[Note]marmariadb-1Version:'11.4.5-MariaDB-ubu2404PhpStormort: 3306mariadb.org binarydistribution2026.1elasticsearchI {"type": "server""timestamp":NFO","component" : "o.e.n.Node", "cluster.name":73a4f","message": "version[7.10.2], pid[6], builr59143c1f785afa92b9/2021-01-13T04:42:47.1572772], ([AdoptOpenJDK/OpenJDK 64-Bit Server VM/15.0.1/15.(elasticsearch1 {"type": "server"., "timestamp":NFO""component" : "o.e.n.Node", "cluster.name":73a4f"', "message": "JVM home [/usr/share/elasticsrelasticsearchNFO",1 {"type": "server", "timestamp" :"component": "o.e.n.Node", "cluster.name":L JETBRAINS IDES73a4f""message": "JVM arguments [-Xshare:auto,networkaddress.cache.negative.ttl=10, -XX:+Alwayslrue, -Dfile.encoding=UTF-8, -Djna.nosys=true, -XXodeDetailsInExceptionMessages,=true, -Dio.netty.recycler.maxCapacityPerThread=0,-UIU.IICLLY•ULLULULUI • RUMIVLICLLMICIIUS--Dlog4j.shutdownHookEnabled=false, -Dlog4j2.disable.jmx=true, -Djava.locale.providers=SPI, COMPAT, -Xms1g, -Xmx1g, -XX:+UseG1GC, -XX:G1ReservePercent=25, -XX:InitiatingHeap0ccupancyPercent=30, -Djava.io.tmpdir=/tmp/elasticsearch-10798175557550719749, -XX:+HeapDumpOnOut0fMemoryError, -XX:HeapDumpPath=data, -XX:ErrorFile=logs/hs_err_pid%p.1og, -Xlog:gc*,gc+age=trace,safepoint:file=logs/gc.log:utctime,pid,tags:filecount=32,filesize=64m,-Des.cgroups.hierarchy.override=/, -Xms700m, -Xmx700m, -XX:MaxDirectMemorySize=367001600, -Des.path.home=/usr/share/elasticsearch, -Des.path.conf=/usr/share/elasticsearch/confi-Des.distribution.flavor=default, -Des.distribution.type=docker, -Des.bundled_jdk=tru*3-zshXIPROD (-zsh)Last login: Tue May 12 17:54:40 on console84screenpipe"Poetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could notfind a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ [X T3 EU (-zsh)waet1aлin:Mav1217•54•40 An cAncolefile in /Users/lukas or its parentsfile in /Users/lukas or its parentsolefile in /Users/lukas or its parentsfile in /Users/lukas or its parents$001file in /Users/lukas or its parentsfile in /Users/lukas or its parents~ $ 0Last login: Tue May 12 20:12:05 on ttys001О 85PRODSTAGEPoetry could not find a pyproject.toml file in /Users/lukas or its parentsFRONTENDPoetry could notfind a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ lX 27 EXT (-zsh)Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEXTENSIONView in Docker Desktop• View Configw Enable WatchPoetrycould not find a pyproject.tomlfile in /Users/lukas or its parentsas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I...
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2026-05-13T09:32:50.444251+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664770444_m2.jpg...
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PhpStormEdiViewNavigateCodeLaravelRefactorRunTools PhpStormEdiViewNavigateCodeLaravelRefactorRunToolsWindowHelpS0 M O"suppont Dally • In zn 20m100% C 8• Wed 13 May 12:32:50faVsco.is• ReportController.php • AutomatedReportGenerated.php• TrackAutomatedReportGeneratedEvent.php • PlaybackController.php• UserAutomatedReportsController.phpFlannatservice.pngD +1...
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2822976974273329942
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visual_change
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ocr
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PhpStormEdiViewNavigateCodeLaravelRefactorRunTools PhpStormEdiViewNavigateCodeLaravelRefactorRunToolsWindowHelpS0 M O"suppont Dally • In zn 20m100% C 8• Wed 13 May 12:32:50faVsco.is• ReportController.php • AutomatedReportGenerated.php• TrackAutomatedReportGeneratedEvent.php • PlaybackController.php• UserAutomatedReportsController.phpFlannatservice.pngD +1...
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32695
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1252
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4
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2026-05-13T09:32:52.252872+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664772252_m1.jpg...
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PhpStorm
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1
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NULL
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monitor_1
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NULL
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NULL
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NULL
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NULL
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PhpStormFileEditViewNavigateCodeLaravelRefactorRun PhpStormFileEditViewNavigateCodeLaravelRefactorRunToolsWindowHelp>•.DOCKER (docker-compose)DEV (-zsh)₴82APP (-zsh)(alol• Support Daily - in 2 h 28 m100% C8• Wed 13 May12:32:51DOCKER11DOCKER (docker-compose)docker_lamp_1docker_lamp_1₴81-zsh84screenpipe"XIPROD (-zsh)Last login:Tue May 12 17:54:40 on console+ composer--prefer-dist[cont-init.d] 01-check-apikey.sh:2026-05-13Server socketcreated on IP: "[IP_ADDRESS]'.2026-05-139:32:41 0 [Note]Server socket created on IP: '::'.with code 1Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEvent Scheduler: Loaded @ events2026-05-13mariadbd: ready for connections:mariadb-1Version:'11.4.5-MariaDB-ubu2404'ort: 3306mariadb.org binary distributionelasticsearch1 {"type":"server""timestamp" :NFO""component":73a4f""o.e.n.Node", "cluster.name":"message":"version[7.10.2], pid[6], buil59143c1f785af92b9/2021-01-13T04:42:47.1572772], ([Adopt0penJDK/OpenJDK 64-Bit Server VM/15.0.1/15.(PhpStormelasticsearch1 {"type":"server""timestamp" :NFO"2026.1"component": "o.e.n.Node""cluster.name":73a4f""message": "JVM home [/usr/share/elasticsrelasticsearchI {"type":"server""timestamp":NFO""component": "o.e.n.Node""cluster.name":73a4f""message":"JVM arguments [-Xshare:auto,networkaddress.cache.negative.ttl=10, -XX:+Alwaysi-Dfile.encoding=UTF-8, -Djna.nosys=true, -XXodeDetailsInExceptionMessages,-Dio.netty.noUnsaft=true, -Dio.netty.recycler.maxCapacityPerThread=0-Dlog4j.shutdownHookEnabled=false,-Dlog4j2.di:L JETBRAINS IDES=SP1, COMPAT,-Xms1g, -Xmx1g,cupancyPercent=30,-XX:+UseG1GC, -XX:G1F-Djava.io.tmpdir=/tmp/elasticsrmpOnOutOfMemoryError,-XX:HeapDumpPath=data,gc*,gc+age=trace, safepoint:file=logs/gc.log:utctir-Des.cgroups.hierarchy.override=/,-MA.PUAULI CELPICHVI YJILC-UUIVULUUL,-Des.path.home=/usr/share/elasticsearch,-Des.path.conf=/usr/share/elasticsearch/confi-Des.distribution.flavor=default, -Des.distribution.type=docker, -Des.bundled_jdk=truPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ 023 EU (-zsh)1anin-Mav1217•54•40 лnconcolefile in /Users/lukas or its parentsfile in /Users/lukas or its parentsolefile in /Users/lukas or its parentsfile in /Users/lukas or its parents$001file in /Users/lukas or its parentsfile in /Users/lukas or its parents~ $ 0Last login: Tue May 12 20:12:05 on ttys001181О 85PRODSTAGEPoetry could not find a pyproject.toml file in /Users/lukas or its parentsFRONTENDdocker_lamp_1I Installingdependencies from lockfile (including require-dev)I Verifying lock file contentsbe installed on current platform.to install,docker_lamp_1doctrine/annotations is abandoned, you shouldavoid using it. No replacement was suggested.docker_lamp_1I Generating optimized autoload filesPoetry could notfind a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ lX t7 EXT (-zsh)Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEXTENSIONView in Docker Desktopo View Configw Enable WatchPoetrycould not find a pyproject.tomlfile in /Users/lukas or its parentsas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I...
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-5277180272992694808
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visual_change
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ocr
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PhpStormFileEditViewNavigateCodeLaravelRefactorRun PhpStormFileEditViewNavigateCodeLaravelRefactorRunToolsWindowHelp>•.DOCKER (docker-compose)DEV (-zsh)₴82APP (-zsh)(alol• Support Daily - in 2 h 28 m100% C8• Wed 13 May12:32:51DOCKER11DOCKER (docker-compose)docker_lamp_1docker_lamp_1₴81-zsh84screenpipe"XIPROD (-zsh)Last login:Tue May 12 17:54:40 on console+ composer--prefer-dist[cont-init.d] 01-check-apikey.sh:2026-05-13Server socketcreated on IP: "[IP_ADDRESS]'.2026-05-139:32:41 0 [Note]Server socket created on IP: '::'.with code 1Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEvent Scheduler: Loaded @ events2026-05-13mariadbd: ready for connections:mariadb-1Version:'11.4.5-MariaDB-ubu2404'ort: 3306mariadb.org binary distributionelasticsearch1 {"type":"server""timestamp" :NFO""component":73a4f""o.e.n.Node", "cluster.name":"message":"version[7.10.2], pid[6], buil59143c1f785af92b9/2021-01-13T04:42:47.1572772], ([Adopt0penJDK/OpenJDK 64-Bit Server VM/15.0.1/15.(PhpStormelasticsearch1 {"type":"server""timestamp" :NFO"2026.1"component": "o.e.n.Node""cluster.name":73a4f""message": "JVM home [/usr/share/elasticsrelasticsearchI {"type":"server""timestamp":NFO""component": "o.e.n.Node""cluster.name":73a4f""message":"JVM arguments [-Xshare:auto,networkaddress.cache.negative.ttl=10, -XX:+Alwaysi-Dfile.encoding=UTF-8, -Djna.nosys=true, -XXodeDetailsInExceptionMessages,-Dio.netty.noUnsaft=true, -Dio.netty.recycler.maxCapacityPerThread=0-Dlog4j.shutdownHookEnabled=false,-Dlog4j2.di:L JETBRAINS IDES=SP1, COMPAT,-Xms1g, -Xmx1g,cupancyPercent=30,-XX:+UseG1GC, -XX:G1F-Djava.io.tmpdir=/tmp/elasticsrmpOnOutOfMemoryError,-XX:HeapDumpPath=data,gc*,gc+age=trace, safepoint:file=logs/gc.log:utctir-Des.cgroups.hierarchy.override=/,-MA.PUAULI CELPICHVI YJILC-UUIVULUUL,-Des.path.home=/usr/share/elasticsearch,-Des.path.conf=/usr/share/elasticsearch/confi-Des.distribution.flavor=default, -Des.distribution.type=docker, -Des.bundled_jdk=truPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ 023 EU (-zsh)1anin-Mav1217•54•40 лnconcolefile in /Users/lukas or its parentsfile in /Users/lukas or its parentsolefile in /Users/lukas or its parentsfile in /Users/lukas or its parents$001file in /Users/lukas or its parentsfile in /Users/lukas or its parents~ $ 0Last login: Tue May 12 20:12:05 on ttys001181О 85PRODSTAGEPoetry could not find a pyproject.toml file in /Users/lukas or its parentsFRONTENDdocker_lamp_1I Installingdependencies from lockfile (including require-dev)I Verifying lock file contentsbe installed on current platform.to install,docker_lamp_1doctrine/annotations is abandoned, you shouldavoid using it. No replacement was suggested.docker_lamp_1I Generating optimized autoload filesPoetry could notfind a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ lX t7 EXT (-zsh)Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEXTENSIONView in Docker Desktopo View Configw Enable WatchPoetrycould not find a pyproject.tomlfile in /Users/lukas or its parentsas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I...
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DOCKER₴81NavigateLaravelRefactorRunToolsWindowHelp DOCKER₴81NavigateLaravelRefactorRunToolsWindowHelpDOCKER (docker-compose)APP (-zsh)>•.DEV (-zsh)₴8211DOCKER (docker-compose)elasticsearch1 {"type""server""timestamp"NFO""2026-05-13709:32:54,789Z""component":"o.e.p.PluginsService""cluster.name" :"docker-cluster""level":"I"node. name":"e802ad473a4f""message":"loadedmodule [x-pack-monitoring]"}elasticsearch1 {"type":"server""timestamp":NFO""2026-05-13T09:32:54,789Z""component":"o.e.p.PluginsService""cluster .name""docker-cluster""level": "I"node.name":"e802ad473a4f""message":"loaded module [x-pack-ql]" }elasticsearchNFO"1 {"type","server""timestamp":"2026-05-13T09:32:54,789Z""component":"e802ad473a4f""o.e.p.PluginsService""cluster.name":"docker-cluster""level":"I"node. name""message" :"loadedmodule [x-pack-rollup]"}elasticsearchNFO"{"type" :"server""timestamp":"2026-05-13T09:32:54,789Z""component":"e802ad473a4f""o.e.p.PluginsService""cluster.name":"docker-cluster""level": "I"node. name""message":"loaded module [x-pack-security]" }elasticsearchI {"type":"server""timestamp":NFO""component" :"o.e.p.PluginsService""2026-05-13T09:32:54,790Z","level": "I"cluster.name":"docker-cluster""node. name""e802ad473a4f""message":"loadedmodule [x-pack-sql]"}elasticsearchI {"type":"server""timestamp"NFO""2026-05-13T09:32:54,790Z""component": "o.e.p.PluginsService""e80Zad473a4f","cluster.name" :"docker-cluster""level":"I"node. name""message": "loaded module [x-pack-stack]" }elasticsearch1 {"type": "server""timestamp":"2026-05-13T09:32:54,790Z"NFO","component": "o.e.p.PluginsService""cluster.name": "docker-cluster""level":"I"node. name": "e802ad473a4f"', "message": "loaded module [x-pack-voting-only-node]" }elasticsearch1 {"type": "server""timestamp":"2026-05-13T09:32:54,790Z"NFO", "component": "o.e.p.PluginsService","cluster. name":"docker-cluster""level":"I"node.name": "e802ad473a4f", "message": "loaded module [x-pack-watcher]" }elasticsearch | {"type": "server""timestamp":"2026-05-13T09:32:54,790Z",NFO", "component": "o.e.p.PluginsService","cluster. name":"docker-cluster""level": "I"node. name": "e802ad473a4f", "message":"no plugins loaded" }elasticsearch1 {"type":"deprecation","timestamp": "2026-05-13T09:32:54,956Z",":"DEPRECATION""component":"o.e.d.c.s.Settings", "cluster.name":"docker-cluster",node.name":"e802ad473a4f", "message":"[node.data] setting was deprecated in Elasticsearch and will be removed in a future release! See the breaking changes documentation forthe next major version."elasticsearch | {"type":"server"NFO""timestamp":"2026-05-13T09:32:54,996Z","level": "I"component": "o.e.e.NodeEnvironment""cluster.name": "docker-cluster""node. name"e802ad473a4f", "message": "using [1] data paths, mounts [[/usr/share/elasticsearch/data (/dev/vda1)]], net usable_space [14.1gb], net total_space [58.3gb], types [ext4]"elasticsearchI {"type": "server""timestamp":"2026-05-13T09:32:54,997Z""level":}"INFO", "component": "o.e.e.NodeEnvironment""cluster.name" :"docker-cluster""node. name"e802ad473a4f", "message": "heap size [700mb], compressed ordinary object pointers [true]" }(wbl• Support Daily - in 2 h 28 m100% <78•Wed 13 May12:32:55181V View in Docker Desktopo View Configw Enable Watch-zsh84screenpipe"XIPROD (-zsh)Last login:Tue May 12 17:54:40 on consolePoetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I23 EU (-zsh)Last login: Tue May 12 17:54:40on consolePoetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.tomlfile in /Users/lukas or its parents@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I|STAGE (-zsh)Last login: Tue May 12 17:54:40 on consolePoetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny|$T5 QA (-zsh)Last login: Tue May 12 20:12:05 on ttys001Poetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentsXI16FE (-zsh)Last login: Tue May 12 20:12:05 on ttys001О 85PRODSTAGEPoetry could not find a pyproject.toml file in /Users/lukas or its parentsFRONTENDPoetry could not find a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ lX Y7 EXT (-zsh)Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEXTENSIONPoetry could not find a pyproject.tomlfile in /Users/lukas or its parentsas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I...
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DOCKER₴81NavigateLaravelRefactorRunToolsWindowHelp DOCKER₴81NavigateLaravelRefactorRunToolsWindowHelpDOCKER (docker-compose)APP (-zsh)>•.DEV (-zsh)₴8211DOCKER (docker-compose)elasticsearch1 {"type""server""timestamp"NFO""2026-05-13709:32:54,789Z""component":"o.e.p.PluginsService""cluster.name" :"docker-cluster""level":"I"node. name":"e802ad473a4f""message":"loadedmodule [x-pack-monitoring]"}elasticsearch1 {"type":"server""timestamp":NFO""2026-05-13T09:32:54,789Z""component":"o.e.p.PluginsService""cluster .name""docker-cluster""level": "I"node.name":"e802ad473a4f""message":"loaded module [x-pack-ql]" }elasticsearchNFO"1 {"type","server""timestamp":"2026-05-13T09:32:54,789Z""component":"e802ad473a4f""o.e.p.PluginsService""cluster.name":"docker-cluster""level":"I"node. name""message" :"loadedmodule [x-pack-rollup]"}elasticsearchNFO"{"type" :"server""timestamp":"2026-05-13T09:32:54,789Z""component":"e802ad473a4f""o.e.p.PluginsService""cluster.name":"docker-cluster""level": "I"node. name""message":"loaded module [x-pack-security]" }elasticsearchI {"type":"server""timestamp":NFO""component" :"o.e.p.PluginsService""2026-05-13T09:32:54,790Z","level": "I"cluster.name":"docker-cluster""node. name""e802ad473a4f""message":"loadedmodule [x-pack-sql]"}elasticsearchI {"type":"server""timestamp"NFO""2026-05-13T09:32:54,790Z""component": "o.e.p.PluginsService""e80Zad473a4f","cluster.name" :"docker-cluster""level":"I"node. name""message": "loaded module [x-pack-stack]" }elasticsearch1 {"type": "server""timestamp":"2026-05-13T09:32:54,790Z"NFO","component": "o.e.p.PluginsService""cluster.name": "docker-cluster""level":"I"node. name": "e802ad473a4f"', "message": "loaded module [x-pack-voting-only-node]" }elasticsearch1 {"type": "server""timestamp":"2026-05-13T09:32:54,790Z"NFO", "component": "o.e.p.PluginsService","cluster. name":"docker-cluster""level":"I"node.name": "e802ad473a4f", "message": "loaded module [x-pack-watcher]" }elasticsearch | {"type": "server""timestamp":"2026-05-13T09:32:54,790Z",NFO", "component": "o.e.p.PluginsService","cluster. name":"docker-cluster""level": "I"node. name": "e802ad473a4f", "message":"no plugins loaded" }elasticsearch1 {"type":"deprecation","timestamp": "2026-05-13T09:32:54,956Z",":"DEPRECATION""component":"o.e.d.c.s.Settings", "cluster.name":"docker-cluster",node.name":"e802ad473a4f", "message":"[node.data] setting was deprecated in Elasticsearch and will be removed in a future release! See the breaking changes documentation forthe next major version."elasticsearch | {"type":"server"NFO""timestamp":"2026-05-13T09:32:54,996Z","level": "I"component": "o.e.e.NodeEnvironment""cluster.name": "docker-cluster""node. name"e802ad473a4f", "message": "using [1] data paths, mounts [[/usr/share/elasticsearch/data (/dev/vda1)]], net usable_space [14.1gb], net total_space [58.3gb], types [ext4]"elasticsearchI {"type": "server""timestamp":"2026-05-13T09:32:54,997Z""level":}"INFO", "component": "o.e.e.NodeEnvironment""cluster.name" :"docker-cluster""node. name"e802ad473a4f", "message": "heap size [700mb], compressed ordinary object pointers [true]" }(wbl• Support Daily - in 2 h 28 m100% <78•Wed 13 May12:32:55181V View in Docker Desktopo View Configw Enable Watch-zsh84screenpipe"XIPROD (-zsh)Last login:Tue May 12 17:54:40 on consolePoetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I23 EU (-zsh)Last login: Tue May 12 17:54:40on consolePoetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.tomlfile in /Users/lukas or its parents@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I|STAGE (-zsh)Last login: Tue May 12 17:54:40 on consolePoetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny|$T5 QA (-zsh)Last login: Tue May 12 20:12:05 on ttys001Poetry could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentsXI16FE (-zsh)Last login: Tue May 12 20:12:05 on ttys001О 85PRODSTAGEPoetry could not find a pyproject.toml file in /Users/lukas or its parentsFRONTENDPoetry could not find a pyproject.toml file in /Users/lukas or its parentsLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ lX Y7 EXT (-zsh)Poetry could not find a pyproject.toml file in /Users/lukas or its parentsEXTENSIONPoetry could not find a pyproject.tomlfile in /Users/lukas or its parentsas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ I...
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664778290_m1.jpg...
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faVsco.js – console [STAGING]
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Downloading plugin 'Windsurf Plugin for Python Downloading plugin 'Windsurf Plugin for Python, JS, Java, Go...'
Project: faVsco.js, menu
Start Listening for PHP Debug Connections
HandleHubspotRateLimitTest
Run 'HandleHubspotRateLimitTest'
Debug 'HandleHubspotRateLimitTest'
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JetBrains AI
Search Everywhere
IDE and Project Settings
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Code changed:
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<?php
declare(strict_types=1);
namespace Jiminny\Http\Controllers\Webhook;
use Carbon\Carbon;
use Illuminate\Contracts\Bus\Dispatcher as BusDispatcher;
use Illuminate\Contracts\Events\Dispatcher as EventDispatcher;
use Illuminate\Http\JsonResponse;
use Illuminate\Http\Request;
use Jiminny\Events\AutomatedReports\AutomatedReportGenerated;
use Jiminny\Exceptions\ModelNotFoundException;
use Jiminny\Http\Controllers\AbstractController;
use Jiminny\Jobs\AutomatedReports\SendReportJob;
use Jiminny\Models\AutomatedReportResult;
use Jiminny\Services\Kiosk\AutomatedReports\AutomatedReportsCallbackService;
use Jiminny\Services\Kiosk\AutomatedReports\AutomatedReportsService;
use Psr\Log\LoggerInterface;
use Throwable;
class ReportController extends AbstractController
{
/**
* Log prefix for all log messages
*/
private const string LOG_PREFIX = '[Report Ready]';
public function __construct(
private readonly AutomatedReportsService $automatedReportsService,
private readonly BusDispatcher $dispatcher,
private readonly LoggerInterface $logger,
private readonly AutomatedReportsCallbackService $callbackService,
private readonly EventDispatcher $eventDispatcher,
) {
}
public function ready(Request $request): JsonResponse
{
$payload = $request->all();
$now = Carbon::now();
$this->logger->info(self::LOG_PREFIX . ' Webhook received', [
'payload' => $payload,
]);
// validate
$reportUuid = $this->callbackService->getResultUuid($payload);
if (empty($reportUuid)) {
return response()->json(['status' => 'error', 'message' => 'Request ID is empty'], status: 400);
}
try {
$report = $this->automatedReportsService->getReportResult($reportUuid);
// validate
if ($this->callbackService->isProcessed($report)) {
$this->logger->warning(self::LOG_PREFIX . ' Report has been already processed', [
'uuid' => $reportUuid,
'currentStatus' => $report->getStatusLabel(),
]);
return response()->json(['status' => 'already_processed']);
}
// always try to get a child podcast cause report configuration cannot be trusted
$reportPodcast = $this->automatedReportsService->findChildResult(
result: $report,
type: AutomatedReportsService::MEDIA_TYPE_PODCAST
);
// update results
$report->update([
'status' => $this->callbackService->getPrimaryStatus($report, $payload),
'response' => $payload,
'generated_at' => $now,
]);
// if a podcast is set, update it
$reportPodcast?->update([
'status' => $this->callbackService->getPodcastStatus($payload),
'response' => $payload,
'generated_at' => $now,
]);
$this->logger->info(self::LOG_PREFIX . ' Report has been processed', [
'uuid' => $reportUuid,
'child_uuid' => $reportPodcast?->getUuid(),
]);
if (! $this->callbackService->isSuccess($payload)) {
$this->logger->warning(self::LOG_PREFIX . ' Error creating report', $payload);
return response()->json(['status' => 'ok']);
}
// If one-off, send the report immediately, if not leave it for the scheduler (automated-reports:send)
if ($report->getReport()->getFrequency() === AutomatedReportsService::FREQUENCY_ONE_OFF) {
// send the primary report
$this->dispatcher->dispatch(new SendReportJob($reportUuid));
// send the podcast report if it set and generated
if ($reportPodcast && $reportPodcast->getStatus() === AutomatedReportResult::STATUS_GENERATED) {
$this->dispatcher->dispatch(new SendReportJob(reportUuid: $reportPodcast->getUuid()));
}
}
// Track Datadog metrics for automated reports
$automatedReport = $report->getReport();
$this->callbackService->pushToDatadog($automatedReport, $report);
if ($reportPodcast) {
$this->callbackService->pushToDatadog($automatedReport, $reportPodcast);
}
$this->logger->info(self::LOG_PREFIX . ' Triggering Event for UserPilot tracking', [
'report_uuid' => $automatedReport->getUuid(),
'result_uuid' => $reportUuid,
]);
$this->eventDispatcher->dispatch(new AutomatedReportGenerated($automatedReport));
} catch (ModelNotFoundException $exception) {
$this->logger->error(self::LOG_PREFIX . ' Report not found', [
'uuid' => $reportUuid,
'error' => $exception->getMessage(),
]);
return response()->json(['status' => 'error', 'message' => 'Report not found'], status: 404);
} catch (Throwable $exception) {
$this->logger->error(self::LOG_PREFIX . ' Failed to update report status', [
'uuid' => $reportUuid,
'error' => $exception->getMessage(),
]);
return response()->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500);
}
return response()->json(['status' => 'ok']);
}
}
Sync Changes
Hide This Notification...
|
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' Webhook received', [\n 'payload' => $payload,\n ]);\n\n // validate\n $reportUuid = $this->callbackService->getResultUuid($payload);\n if (empty($reportUuid)) {\n return response()->json(['status' => 'error', 'message' => 'Request ID is empty'], status: 400);\n }\n\n try {\n $report = $this->automatedReportsService->getReportResult($reportUuid);\n\n // validate\n if ($this->callbackService->isProcessed($report)) {\n $this->logger->warning(self::LOG_PREFIX . ' Report has been already processed', [\n 'uuid' => $reportUuid,\n 'currentStatus' => $report->getStatusLabel(),\n ]);\n\n return response()->json(['status' => 'already_processed']);\n }\n\n // always try to get a child podcast cause report configuration cannot be trusted\n $reportPodcast = $this->automatedReportsService->findChildResult(\n result: $report,\n type: AutomatedReportsService::MEDIA_TYPE_PODCAST\n );\n\n // update results\n $report->update([\n 'status' => $this->callbackService->getPrimaryStatus($report, $payload),\n 'response' => $payload,\n 'generated_at' => $now,\n ]);\n // if a podcast is set, update it\n $reportPodcast?->update([\n 'status' => $this->callbackService->getPodcastStatus($payload),\n 'response' => $payload,\n 'generated_at' => $now,\n ]);\n\n $this->logger->info(self::LOG_PREFIX . ' Report has been processed', [\n 'uuid' => $reportUuid,\n 'child_uuid' => $reportPodcast?->getUuid(),\n ]);\n\n if (! $this->callbackService->isSuccess($payload)) {\n $this->logger->warning(self::LOG_PREFIX . ' Error creating report', $payload);\n\n return response()->json(['status' => 'ok']);\n }\n\n // If one-off, send the report immediately, if not leave it for the scheduler (automated-reports:send)\n if ($report->getReport()->getFrequency() === AutomatedReportsService::FREQUENCY_ONE_OFF) {\n // send the primary report\n $this->dispatcher->dispatch(new SendReportJob($reportUuid));\n\n // send the podcast report if it set and generated\n if ($reportPodcast && $reportPodcast->getStatus() === AutomatedReportResult::STATUS_GENERATED) {\n $this->dispatcher->dispatch(new SendReportJob(reportUuid: $reportPodcast->getUuid()));\n }\n }\n\n // Track Datadog metrics for automated reports\n $automatedReport = $report->getReport();\n $this->callbackService->pushToDatadog($automatedReport, $report);\n\n if ($reportPodcast) {\n $this->callbackService->pushToDatadog($automatedReport, $reportPodcast);\n }\n\n $this->logger->info(self::LOG_PREFIX . ' Triggering Event for UserPilot tracking', [\n 'report_uuid' => $automatedReport->getUuid(),\n 'result_uuid' => $reportUuid,\n ]);\n $this->eventDispatcher->dispatch(new AutomatedReportGenerated($automatedReport));\n } catch (ModelNotFoundException $exception) {\n $this->logger->error(self::LOG_PREFIX . ' Report not found', [\n 'uuid' => $reportUuid,\n 'error' => $exception->getMessage(),\n ]);\n\n return response()->json(['status' => 'error', 'message' => 'Report not found'], status: 404);\n } catch (Throwable $exception) {\n $this->logger->error(self::LOG_PREFIX . ' Failed to update report status', [\n 'uuid' => $reportUuid,\n 'error' => $exception->getMessage(),\n ]);\n\n return response()->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500);\n }\n\n return response()->json(['status' => 'ok']);\n }\n}","depth":4,"on_screen":true,"value":"<?php\n\ndeclare(strict_types=1);\n\nnamespace Jiminny\\Http\\Controllers\\Webhook;\n\nuse Carbon\\Carbon;\nuse Illuminate\\Contracts\\Bus\\Dispatcher as BusDispatcher;\nuse Illuminate\\Contracts\\Events\\Dispatcher as EventDispatcher;\nuse Illuminate\\Http\\JsonResponse;\nuse Illuminate\\Http\\Request;\nuse Jiminny\\Events\\AutomatedReports\\AutomatedReportGenerated;\nuse Jiminny\\Exceptions\\ModelNotFoundException;\nuse Jiminny\\Http\\Controllers\\AbstractController;\nuse Jiminny\\Jobs\\AutomatedReports\\SendReportJob;\nuse Jiminny\\Models\\AutomatedReportResult;\nuse Jiminny\\Services\\Kiosk\\AutomatedReports\\AutomatedReportsCallbackService;\nuse Jiminny\\Services\\Kiosk\\AutomatedReports\\AutomatedReportsService;\nuse Psr\\Log\\LoggerInterface;\nuse Throwable;\n\nclass ReportController extends AbstractController\n{\n /**\n * Log prefix for all log messages\n */\n private const string LOG_PREFIX = '[Report Ready]';\n\n public function __construct(\n private readonly AutomatedReportsService $automatedReportsService,\n private readonly BusDispatcher $dispatcher,\n private readonly LoggerInterface $logger,\n private readonly AutomatedReportsCallbackService $callbackService,\n private readonly EventDispatcher $eventDispatcher,\n ) {\n }\n\n public function ready(Request $request): JsonResponse\n {\n $payload = $request->all();\n $now = Carbon::now();\n\n $this->logger->info(self::LOG_PREFIX . ' Webhook received', [\n 'payload' => $payload,\n ]);\n\n // validate\n $reportUuid = $this->callbackService->getResultUuid($payload);\n if (empty($reportUuid)) {\n return response()->json(['status' => 'error', 'message' => 'Request ID is empty'], status: 400);\n }\n\n try {\n $report = $this->automatedReportsService->getReportResult($reportUuid);\n\n // validate\n if ($this->callbackService->isProcessed($report)) {\n $this->logger->warning(self::LOG_PREFIX . ' Report has been already processed', [\n 'uuid' => $reportUuid,\n 'currentStatus' => $report->getStatusLabel(),\n ]);\n\n return response()->json(['status' => 'already_processed']);\n }\n\n // always try to get a child podcast cause report configuration cannot be trusted\n $reportPodcast = $this->automatedReportsService->findChildResult(\n result: $report,\n type: AutomatedReportsService::MEDIA_TYPE_PODCAST\n );\n\n // update results\n $report->update([\n 'status' => $this->callbackService->getPrimaryStatus($report, $payload),\n 'response' => $payload,\n 'generated_at' => $now,\n ]);\n // if a podcast is set, update it\n $reportPodcast?->update([\n 'status' => $this->callbackService->getPodcastStatus($payload),\n 'response' => $payload,\n 'generated_at' => $now,\n ]);\n\n $this->logger->info(self::LOG_PREFIX . ' Report has been processed', [\n 'uuid' => $reportUuid,\n 'child_uuid' => $reportPodcast?->getUuid(),\n ]);\n\n if (! $this->callbackService->isSuccess($payload)) {\n $this->logger->warning(self::LOG_PREFIX . ' Error creating report', $payload);\n\n return response()->json(['status' => 'ok']);\n }\n\n // If one-off, send the report immediately, if not leave it for the scheduler (automated-reports:send)\n if ($report->getReport()->getFrequency() === AutomatedReportsService::FREQUENCY_ONE_OFF) {\n // send the primary report\n $this->dispatcher->dispatch(new SendReportJob($reportUuid));\n\n // send the podcast report if it set and generated\n if ($reportPodcast && $reportPodcast->getStatus() === AutomatedReportResult::STATUS_GENERATED) {\n $this->dispatcher->dispatch(new SendReportJob(reportUuid: $reportPodcast->getUuid()));\n }\n }\n\n // Track Datadog metrics for automated reports\n $automatedReport = $report->getReport();\n $this->callbackService->pushToDatadog($automatedReport, $report);\n\n if ($reportPodcast) {\n $this->callbackService->pushToDatadog($automatedReport, $reportPodcast);\n }\n\n $this->logger->info(self::LOG_PREFIX . 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' Failed to update report status', [\n 'uuid' => $reportUuid,\n 'error' => $exception->getMessage(),\n ]);\n\n return response()->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500);\n }\n\n return response()->json(['status' => 'ok']);\n }\n}","role_description":"text entry area","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Sync Changes","depth":4,"bounds":{"left":0.0,"top":0.0,"width":0.018055556,"height":0.026666667},"on_screen":false,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Hide This Notification","depth":4,"bounds":{"left":0.0,"top":0.0,"width":0.018055556,"height":0.026666667},"on_screen":false,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false}]...
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Downloading plugin 'Windsurf Plugin for Python Downloading plugin 'Windsurf Plugin for Python, JS, Java, Go...'
Project: faVsco.js, menu
Start Listening for PHP Debug Connections
HandleHubspotRateLimitTest
Run 'HandleHubspotRateLimitTest'
Debug 'HandleHubspotRateLimitTest'
More Actions
JetBrains AI
Search Everywhere
IDE and Project Settings
Sync Changes
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Code changed:
Hide
<?php
declare(strict_types=1);
namespace Jiminny\Http\Controllers\Webhook;
use Carbon\Carbon;
use Illuminate\Contracts\Bus\Dispatcher as BusDispatcher;
use Illuminate\Contracts\Events\Dispatcher as EventDispatcher;
use Illuminate\Http\JsonResponse;
use Illuminate\Http\Request;
use Jiminny\Events\AutomatedReports\AutomatedReportGenerated;
use Jiminny\Exceptions\ModelNotFoundException;
use Jiminny\Http\Controllers\AbstractController;
use Jiminny\Jobs\AutomatedReports\SendReportJob;
use Jiminny\Models\AutomatedReportResult;
use Jiminny\Services\Kiosk\AutomatedReports\AutomatedReportsCallbackService;
use Jiminny\Services\Kiosk\AutomatedReports\AutomatedReportsService;
use Psr\Log\LoggerInterface;
use Throwable;
class ReportController extends AbstractController
{
/**
* Log prefix for all log messages
*/
private const string LOG_PREFIX = '[Report Ready]';
public function __construct(
private readonly AutomatedReportsService $automatedReportsService,
private readonly BusDispatcher $dispatcher,
private readonly LoggerInterface $logger,
private readonly AutomatedReportsCallbackService $callbackService,
private readonly EventDispatcher $eventDispatcher,
) {
}
public function ready(Request $request): JsonResponse
{
$payload = $request->all();
$now = Carbon::now();
$this->logger->info(self::LOG_PREFIX . ' Webhook received', [
'payload' => $payload,
]);
// validate
$reportUuid = $this->callbackService->getResultUuid($payload);
if (empty($reportUuid)) {
return response()->json(['status' => 'error', 'message' => 'Request ID is empty'], status: 400);
}
try {
$report = $this->automatedReportsService->getReportResult($reportUuid);
// validate
if ($this->callbackService->isProcessed($report)) {
$this->logger->warning(self::LOG_PREFIX . ' Report has been already processed', [
'uuid' => $reportUuid,
'currentStatus' => $report->getStatusLabel(),
]);
return response()->json(['status' => 'already_processed']);
}
// always try to get a child podcast cause report configuration cannot be trusted
$reportPodcast = $this->automatedReportsService->findChildResult(
result: $report,
type: AutomatedReportsService::MEDIA_TYPE_PODCAST
);
// update results
$report->update([
'status' => $this->callbackService->getPrimaryStatus($report, $payload),
'response' => $payload,
'generated_at' => $now,
]);
// if a podcast is set, update it
$reportPodcast?->update([
'status' => $this->callbackService->getPodcastStatus($payload),
'response' => $payload,
'generated_at' => $now,
]);
$this->logger->info(self::LOG_PREFIX . ' Report has been processed', [
'uuid' => $reportUuid,
'child_uuid' => $reportPodcast?->getUuid(),
]);
if (! $this->callbackService->isSuccess($payload)) {
$this->logger->warning(self::LOG_PREFIX . ' Error creating report', $payload);
return response()->json(['status' => 'ok']);
}
// If one-off, send the report immediately, if not leave it for the scheduler (automated-reports:send)
if ($report->getReport()->getFrequency() === AutomatedReportsService::FREQUENCY_ONE_OFF) {
// send the primary report
$this->dispatcher->dispatch(new SendReportJob($reportUuid));
// send the podcast report if it set and generated
if ($reportPodcast && $reportPodcast->getStatus() === AutomatedReportResult::STATUS_GENERATED) {
$this->dispatcher->dispatch(new SendReportJob(reportUuid: $reportPodcast->getUuid()));
}
}
// Track Datadog metrics for automated reports
$automatedReport = $report->getReport();
$this->callbackService->pushToDatadog($automatedReport, $report);
if ($reportPodcast) {
$this->callbackService->pushToDatadog($automatedReport, $reportPodcast);
}
$this->logger->info(self::LOG_PREFIX . ' Triggering Event for UserPilot tracking', [
'report_uuid' => $automatedReport->getUuid(),
'result_uuid' => $reportUuid,
]);
$this->eventDispatcher->dispatch(new AutomatedReportGenerated($automatedReport));
} catch (ModelNotFoundException $exception) {
$this->logger->error(self::LOG_PREFIX . ' Report not found', [
'uuid' => $reportUuid,
'error' => $exception->getMessage(),
]);
return response()->json(['status' => 'error', 'message' => 'Report not found'], status: 404);
} catch (Throwable $exception) {
$this->logger->error(self::LOG_PREFIX . ' Failed to update report status', [
'uuid' => $reportUuid,
'error' => $exception->getMessage(),
]);
return response()->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500);
}
return response()->json(['status' => 'ok']);
}
}
Sync Changes
Hide This Notification...
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2026-05-13T09:32:56.505103+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664776505_m2.jpg...
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faVsco.js – console [STAGING]
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PhostormFV faVsco.jsProjectyv Daop>.circleci> PhostormFV faVsco.jsProjectyv Daop>.circleci>W.cursor>Lo-github> O.sonarlint>D.vscode> D.windsurvD app> O Actionsy M Comnonent> DAcleetlelalnte nttD ActivityW AcuviLyAnalyues0 ActivitySearchAIACUVIIY IYO60 AiAutomation• AIcallscoringASKAnything># DtosuEventsASKAnvihinoPromorseHistorvService.ohoAskJiminnvAiD AWSBilllinaManagement2 CacheCountnCustomerAnDatabaseD Datadogm DateTimeDealinsiahtsm DoalPickeM ClacticSoarchM Sioauent|D EncodingD EncryptionCDESu raker0 FeatureFlags0 FFMpeaC FileSystemu GeckoD GondD GuzzleHttoKevPointsb KioskLanquade DetectionM livefeedVIewINavicarecodeLaravelKeractorTOOISWindowc) RevortController.onp©PlaybackController.php© AutomatedReportResult.phpsenakeportJob.onpcLass keporcuontrouler excenas Adstractcontroulerif (Sreport->getReport()->getFrequency === AutomatedReportsService::FREQUENCY_ONE_OFF) %send the primary revortSthis->disoatcher->disoatchtnew SendRenortJob(sreportUuid)s101// send the podcast report if it set and generatedif (SreportPodcast && SreportPodcast->getStatus === AutomatedReportResult::STATUS_GENERATED) ‹Sthis->disnatchen->disnatchinewSendRenont.lohcrenontlluid•SrenontPodcast->aetlluidon%// Track Datadog metrics for automated reportsSautomatedReport = $report->getReport):scnis->caLLbackservice->pushlovaradoe caucomareakeport sreporcif (SreportPodcast) {sch1s->callbackservice->pushlobaradoq sautomatedkeport, sreportroacast^Sthis->logger->info(self::L0G PREFIX ' Triggering Event for UserPilot tracking'. ['report uuid' => SautomatedReport->getUuid@.'result uuid' => Sreportluid.Sthis->eventDispatcher->disoatch.new_AutomatedRenortGeneratedSautomatedRenort:catch ModelNotFoundExcention Sexcention) <Sthis->logger->error(self::L0G PREFIX . " Report not found'. "erron' => sexcention->detMessadeOl.return response()->json(['status' => 'error', 'message' => 'Report not found'], status: 404):catchThrowable Sexcention) ^Sthis->logger->error(self::LOG_PREFIX. ' Failed to update report status', [luuadt => Coenontllundi'error' => $exception->getMessage).return responsed->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500):return response"->json(['status' => 'ok')):40"suppont Dally • In 2n z0h100% S2• Wed 13 May 12:32:56• HandlerubspotkateLimiclest v= custom.log•laravel.log• SF [jiminny@localhost]• HS_ local jiminny@localnost• console [PROD]• console [Eull• console [STAGING] X se lect# id, uuid, type, provider, playbook_category_id, user_id, Lead_id, contact_id, account_id, opportunity_id, stage_id,# crm confiquration id. crm orovider id. transcrintion id. status.from activities where crm_configuration_id = 1 and type = 'conference'# and crm orovider id iS NOT NULLIand provider != 'uploader'and actual start time is NOT NULLORDER by id desc;select * from activities where id = 54747783; # 00U0400000pCzojMACselect p.id, p.activity_type, pc.id, pc.nameFROM playbooks pjoin playbook_categories pc 1<->1..n: on p.id = pc.playbook_idwhere p.team_id = 1 and p.activity_type =SELECT * FROM crm_fields WHERE crm_configuration_id = 1 and object_type = 'event';SELECT * FROM crm field values WHERE crm field id = 4select * from crm layouts cl join playbook layouts pl 1<->1..n: on cl.id = pl.layout idwhere crm_configuration id = 1 and pl.playbook10 = 175:select * from teamssaleur.x rur automatedreoortsrjoin teams t 1.n<->1: on r.team_id = t.idWHERE r.frequency = darlyand r.status =1AND t.status = 'active)AND (r.expires at >= now@) OR r.expires at IS NULL):select * from automated renort results where renort 1d IN (08, 3594select * from activity_searches where id = 10932;select * from activity search filters where activitv search id = 10932.select * from automated_reports order by id desc;select * from automated_report_results order by id desc;select * from automated_reports where id IN (55);celect * from automated nenont noculte whene id TN (81).select * from users where id IN (10633, 13987, 11985);select * from users where group id IN (3710):SELECT * FROM automated reports WHERE uuid to bin('18a06a75-afd2-476f-aadc-14d4057bdda2') = uuidSELECT * FROM automated report results WHERE uuid to bin('582d4b50-8cd3-42a9-9819-d676ff8f3b43') = uuid;select * from automated_report_results where media_type = 'pdf' and status = 2;SELECT * FROM automated report results WHERE uuid to bin('82e74956-6144-4cd1-a3d3-af985c3070a4') = uuid:...
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-5867753338191057479
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visual_change
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ocr
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PhostormFV faVsco.jsProjectyv Daop>.circleci> PhostormFV faVsco.jsProjectyv Daop>.circleci>W.cursor>Lo-github> O.sonarlint>D.vscode> D.windsurvD app> O Actionsy M Comnonent> DAcleetlelalnte nttD ActivityW AcuviLyAnalyues0 ActivitySearchAIACUVIIY IYO60 AiAutomation• AIcallscoringASKAnything># DtosuEventsASKAnvihinoPromorseHistorvService.ohoAskJiminnvAiD AWSBilllinaManagement2 CacheCountnCustomerAnDatabaseD Datadogm DateTimeDealinsiahtsm DoalPickeM ClacticSoarchM Sioauent|D EncodingD EncryptionCDESu raker0 FeatureFlags0 FFMpeaC FileSystemu GeckoD GondD GuzzleHttoKevPointsb KioskLanquade DetectionM livefeedVIewINavicarecodeLaravelKeractorTOOISWindowc) RevortController.onp©PlaybackController.php© AutomatedReportResult.phpsenakeportJob.onpcLass keporcuontrouler excenas Adstractcontroulerif (Sreport->getReport()->getFrequency === AutomatedReportsService::FREQUENCY_ONE_OFF) %send the primary revortSthis->disoatcher->disoatchtnew SendRenortJob(sreportUuid)s101// send the podcast report if it set and generatedif (SreportPodcast && SreportPodcast->getStatus === AutomatedReportResult::STATUS_GENERATED) ‹Sthis->disnatchen->disnatchinewSendRenont.lohcrenontlluid•SrenontPodcast->aetlluidon%// Track Datadog metrics for automated reportsSautomatedReport = $report->getReport):scnis->caLLbackservice->pushlovaradoe caucomareakeport sreporcif (SreportPodcast) {sch1s->callbackservice->pushlobaradoq sautomatedkeport, sreportroacast^Sthis->logger->info(self::L0G PREFIX ' Triggering Event for UserPilot tracking'. ['report uuid' => SautomatedReport->getUuid@.'result uuid' => Sreportluid.Sthis->eventDispatcher->disoatch.new_AutomatedRenortGeneratedSautomatedRenort:catch ModelNotFoundExcention Sexcention) <Sthis->logger->error(self::L0G PREFIX . " Report not found'. "erron' => sexcention->detMessadeOl.return response()->json(['status' => 'error', 'message' => 'Report not found'], status: 404):catchThrowable Sexcention) ^Sthis->logger->error(self::LOG_PREFIX. ' Failed to update report status', [luuadt => Coenontllundi'error' => $exception->getMessage).return responsed->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500):return response"->json(['status' => 'ok')):40"suppont Dally • In 2n z0h100% S2• Wed 13 May 12:32:56• HandlerubspotkateLimiclest v= custom.log•laravel.log• SF [jiminny@localhost]• HS_ local jiminny@localnost• console [PROD]• console [Eull• console [STAGING] X se lect# id, uuid, type, provider, playbook_category_id, user_id, Lead_id, contact_id, account_id, opportunity_id, stage_id,# crm confiquration id. crm orovider id. transcrintion id. status.from activities where crm_configuration_id = 1 and type = 'conference'# and crm orovider id iS NOT NULLIand provider != 'uploader'and actual start time is NOT NULLORDER by id desc;select * from activities where id = 54747783; # 00U0400000pCzojMACselect p.id, p.activity_type, pc.id, pc.nameFROM playbooks pjoin playbook_categories pc 1<->1..n: on p.id = pc.playbook_idwhere p.team_id = 1 and p.activity_type =SELECT * FROM crm_fields WHERE crm_configuration_id = 1 and object_type = 'event';SELECT * FROM crm field values WHERE crm field id = 4select * from crm layouts cl join playbook layouts pl 1<->1..n: on cl.id = pl.layout idwhere crm_configuration id = 1 and pl.playbook10 = 175:select * from teamssaleur.x rur automatedreoortsrjoin teams t 1.n<->1: on r.team_id = t.idWHERE r.frequency = darlyand r.status =1AND t.status = 'active)AND (r.expires at >= now@) OR r.expires at IS NULL):select * from automated renort results where renort 1d IN (08, 3594select * from activity_searches where id = 10932;select * from activity search filters where activitv search id = 10932.select * from automated_reports order by id desc;select * from automated_report_results order by id desc;select * from automated_reports where id IN (55);celect * from automated nenont noculte whene id TN (81).select * from users where id IN (10633, 13987, 11985);select * from users where group id IN (3710):SELECT * FROM automated reports WHERE uuid to bin('18a06a75-afd2-476f-aadc-14d4057bdda2') = uuidSELECT * FROM automated report results WHERE uuid to bin('582d4b50-8cd3-42a9-9819-d676ff8f3b43') = uuid;select * from automated_report_results where media_type = 'pdf' and status = 2;SELECT * FROM automated report results WHERE uuid to bin('82e74956-6144-4cd1-a3d3-af985c3070a4') = uuid:...
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2026-05-13T09:33:01.335578+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664781335_m1.jpg...
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PhpStorm
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faVsco.js – console [STAGING]
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monitor_1
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Downloading plugin 'Windsurf Plugin for Python Downloading plugin 'Windsurf Plugin for Python, JS, Java, Go...'
Project: faVsco.js, menu
Start Listening for PHP Debug Connections
HandleHubspotRateLimitTest
Run 'HandleHubspotRateLimitTest'
Debug 'HandleHubspotRateLimitTest'
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<?php
declare(strict_types=1);
namespace Jiminny\Http\Controllers\Webhook;
use Carbon\Carbon;
use Illuminate\Contracts\Bus\Dispatcher as BusDispatcher;
use Illuminate\Contracts\Events\Dispatcher as EventDispatcher;
use Illuminate\Http\JsonResponse;
use Illuminate\Http\Request;
use Jiminny\Events\AutomatedReports\AutomatedReportGenerated;
use Jiminny\Exceptions\ModelNotFoundException;
use Jiminny\Http\Controllers\AbstractController;
use Jiminny\Jobs\AutomatedReports\SendReportJob;
use Jiminny\Models\AutomatedReportResult;
use Jiminny\Services\Kiosk\AutomatedReports\AutomatedReportsCallbackService;
use Jiminny\Services\Kiosk\AutomatedReports\AutomatedReportsService;
use Psr\Log\LoggerInterface;
use Throwable;
class ReportController extends AbstractController
{
/**
* Log prefix for all log messages
*/
private const string LOG_PREFIX = '[Report Ready]';
public function __construct(
private readonly AutomatedReportsService $automatedReportsService,
private readonly BusDispatcher $dispatcher,
private readonly LoggerInterface $logger,
private readonly AutomatedReportsCallbackService $callbackService,
private readonly EventDispatcher $eventDispatcher,
) {
}
public function ready(Request $request): JsonResponse
{
$payload = $request->all();
$now = Carbon::now();
$this->logger->info(self::LOG_PREFIX . ' Webhook received', [
'payload' => $payload,
]);
// validate
$reportUuid = $this->callbackService->getResultUuid($payload);
if (empty($reportUuid)) {
return response()->json(['status' => 'error', 'message' => 'Request ID is empty'], status: 400);
}
try {
$report = $this->automatedReportsService->getReportResult($reportUuid);
// validate
if ($this->callbackService->isProcessed($report)) {
$this->logger->warning(self::LOG_PREFIX . ' Report has been already processed', [
'uuid' => $reportUuid,
'currentStatus' => $report->getStatusLabel(),
]);
return response()->json(['status' => 'already_processed']);
}
// always try to get a child podcast cause report configuration cannot be trusted
$reportPodcast = $this->automatedReportsService->findChildResult(
result: $report,
type: AutomatedReportsService::MEDIA_TYPE_PODCAST
);
// update results
$report->update([
'status' => $this->callbackService->getPrimaryStatus($report, $payload),
'response' => $payload,
'generated_at' => $now,
]);
// if a podcast is set, update it
$reportPodcast?->update([
'status' => $this->callbackService->getPodcastStatus($payload),
'response' => $payload,
'generated_at' => $now,
]);
$this->logger->info(self::LOG_PREFIX . ' Report has been processed', [
'uuid' => $reportUuid,
'child_uuid' => $reportPodcast?->getUuid(),
]);
if (! $this->callbackService->isSuccess($payload)) {
$this->logger->warning(self::LOG_PREFIX . ' Error creating report', $payload);
return response()->json(['status' => 'ok']);
}
// If one-off, send the report immediately, if not leave it for the scheduler (automated-reports:send)
if ($report->getReport()->getFrequency() === AutomatedReportsService::FREQUENCY_ONE_OFF) {
// send the primary report
$this->dispatcher->dispatch(new SendReportJob($reportUuid));
// send the podcast report if it set and generated
if ($reportPodcast && $reportPodcast->getStatus() === AutomatedReportResult::STATUS_GENERATED) {
$this->dispatcher->dispatch(new SendReportJob(reportUuid: $reportPodcast->getUuid()));
}
}
// Track Datadog metrics for automated reports
$automatedReport = $report->getReport();
$this->callbackService->pushToDatadog($automatedReport, $report);
if ($reportPodcast) {
$this->callbackService->pushToDatadog($automatedReport, $reportPodcast);
}
$this->logger->info(self::LOG_PREFIX . ' Triggering Event for UserPilot tracking', [
'report_uuid' => $automatedReport->getUuid(),
'result_uuid' => $reportUuid,
]);
$this->eventDispatcher->dispatch(new AutomatedReportGenerated($automatedReport));
} catch (ModelNotFoundException $exception) {
$this->logger->error(self::LOG_PREFIX . ' Report not found', [
'uuid' => $reportUuid,
'error' => $exception->getMessage(),
]);
return response()->json(['status' => 'error', 'message' => 'Report not found'], status: 404);
} catch (Throwable $exception) {
$this->logger->error(self::LOG_PREFIX . ' Failed to update report status', [
'uuid' => $reportUuid,
'error' => $exception->getMessage(),
]);
return response()->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500);
}
return response()->json(['status' => 'ok']);
}
}
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Hide This Notification
Code changed:
Hide...
|
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' Webhook received', [\n 'payload' => $payload,\n ]);\n\n // validate\n $reportUuid = $this->callbackService->getResultUuid($payload);\n if (empty($reportUuid)) {\n return response()->json(['status' => 'error', 'message' => 'Request ID is empty'], status: 400);\n }\n\n try {\n $report = $this->automatedReportsService->getReportResult($reportUuid);\n\n // validate\n if ($this->callbackService->isProcessed($report)) {\n $this->logger->warning(self::LOG_PREFIX . ' Report has been already processed', [\n 'uuid' => $reportUuid,\n 'currentStatus' => $report->getStatusLabel(),\n ]);\n\n return response()->json(['status' => 'already_processed']);\n }\n\n // always try to get a child podcast cause report configuration cannot be trusted\n $reportPodcast = $this->automatedReportsService->findChildResult(\n result: $report,\n type: AutomatedReportsService::MEDIA_TYPE_PODCAST\n );\n\n // update results\n $report->update([\n 'status' => $this->callbackService->getPrimaryStatus($report, $payload),\n 'response' => $payload,\n 'generated_at' => $now,\n ]);\n // if a podcast is set, update it\n $reportPodcast?->update([\n 'status' => $this->callbackService->getPodcastStatus($payload),\n 'response' => $payload,\n 'generated_at' => $now,\n ]);\n\n $this->logger->info(self::LOG_PREFIX . ' Report has been processed', [\n 'uuid' => $reportUuid,\n 'child_uuid' => $reportPodcast?->getUuid(),\n ]);\n\n if (! $this->callbackService->isSuccess($payload)) {\n $this->logger->warning(self::LOG_PREFIX . ' Error creating report', $payload);\n\n return response()->json(['status' => 'ok']);\n }\n\n // If one-off, send the report immediately, if not leave it for the scheduler (automated-reports:send)\n if ($report->getReport()->getFrequency() === AutomatedReportsService::FREQUENCY_ONE_OFF) {\n // send the primary report\n $this->dispatcher->dispatch(new SendReportJob($reportUuid));\n\n // send the podcast report if it set and generated\n if ($reportPodcast && $reportPodcast->getStatus() === AutomatedReportResult::STATUS_GENERATED) {\n $this->dispatcher->dispatch(new SendReportJob(reportUuid: $reportPodcast->getUuid()));\n }\n }\n\n // Track Datadog metrics for automated reports\n $automatedReport = $report->getReport();\n $this->callbackService->pushToDatadog($automatedReport, $report);\n\n if ($reportPodcast) {\n $this->callbackService->pushToDatadog($automatedReport, $reportPodcast);\n }\n\n $this->logger->info(self::LOG_PREFIX . ' Triggering Event for UserPilot tracking', [\n 'report_uuid' => $automatedReport->getUuid(),\n 'result_uuid' => $reportUuid,\n ]);\n $this->eventDispatcher->dispatch(new AutomatedReportGenerated($automatedReport));\n } catch (ModelNotFoundException $exception) {\n $this->logger->error(self::LOG_PREFIX . ' Report not found', [\n 'uuid' => $reportUuid,\n 'error' => $exception->getMessage(),\n ]);\n\n return response()->json(['status' => 'error', 'message' => 'Report not found'], status: 404);\n } catch (Throwable $exception) {\n $this->logger->error(self::LOG_PREFIX . ' Failed to update report status', [\n 'uuid' => $reportUuid,\n 'error' => $exception->getMessage(),\n ]);\n\n return response()->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500);\n }\n\n return response()->json(['status' => 'ok']);\n }\n}","depth":4,"on_screen":true,"value":"<?php\n\ndeclare(strict_types=1);\n\nnamespace Jiminny\\Http\\Controllers\\Webhook;\n\nuse Carbon\\Carbon;\nuse Illuminate\\Contracts\\Bus\\Dispatcher as BusDispatcher;\nuse Illuminate\\Contracts\\Events\\Dispatcher as EventDispatcher;\nuse Illuminate\\Http\\JsonResponse;\nuse Illuminate\\Http\\Request;\nuse Jiminny\\Events\\AutomatedReports\\AutomatedReportGenerated;\nuse Jiminny\\Exceptions\\ModelNotFoundException;\nuse Jiminny\\Http\\Controllers\\AbstractController;\nuse Jiminny\\Jobs\\AutomatedReports\\SendReportJob;\nuse Jiminny\\Models\\AutomatedReportResult;\nuse Jiminny\\Services\\Kiosk\\AutomatedReports\\AutomatedReportsCallbackService;\nuse Jiminny\\Services\\Kiosk\\AutomatedReports\\AutomatedReportsService;\nuse Psr\\Log\\LoggerInterface;\nuse Throwable;\n\nclass ReportController extends AbstractController\n{\n /**\n * Log prefix for all log messages\n */\n private const string LOG_PREFIX = '[Report Ready]';\n\n public function __construct(\n private readonly AutomatedReportsService $automatedReportsService,\n private readonly BusDispatcher $dispatcher,\n private readonly LoggerInterface $logger,\n private readonly AutomatedReportsCallbackService $callbackService,\n private readonly EventDispatcher $eventDispatcher,\n ) {\n }\n\n public function ready(Request $request): JsonResponse\n {\n $payload = $request->all();\n $now = Carbon::now();\n\n $this->logger->info(self::LOG_PREFIX . ' Webhook received', [\n 'payload' => $payload,\n ]);\n\n // validate\n $reportUuid = $this->callbackService->getResultUuid($payload);\n if (empty($reportUuid)) {\n return response()->json(['status' => 'error', 'message' => 'Request ID is empty'], status: 400);\n }\n\n try {\n $report = $this->automatedReportsService->getReportResult($reportUuid);\n\n // validate\n if ($this->callbackService->isProcessed($report)) {\n $this->logger->warning(self::LOG_PREFIX . ' Report has been already processed', [\n 'uuid' => $reportUuid,\n 'currentStatus' => $report->getStatusLabel(),\n ]);\n\n return response()->json(['status' => 'already_processed']);\n }\n\n // always try to get a child podcast cause report configuration cannot be trusted\n $reportPodcast = $this->automatedReportsService->findChildResult(\n result: $report,\n type: AutomatedReportsService::MEDIA_TYPE_PODCAST\n );\n\n // update results\n $report->update([\n 'status' => $this->callbackService->getPrimaryStatus($report, $payload),\n 'response' => $payload,\n 'generated_at' => $now,\n ]);\n // if a podcast is set, update it\n $reportPodcast?->update([\n 'status' => $this->callbackService->getPodcastStatus($payload),\n 'response' => $payload,\n 'generated_at' => $now,\n ]);\n\n $this->logger->info(self::LOG_PREFIX . ' Report has been processed', [\n 'uuid' => $reportUuid,\n 'child_uuid' => $reportPodcast?->getUuid(),\n ]);\n\n if (! $this->callbackService->isSuccess($payload)) {\n $this->logger->warning(self::LOG_PREFIX . ' Error creating report', $payload);\n\n return response()->json(['status' => 'ok']);\n }\n\n // If one-off, send the report immediately, if not leave it for the scheduler (automated-reports:send)\n if ($report->getReport()->getFrequency() === AutomatedReportsService::FREQUENCY_ONE_OFF) {\n // send the primary report\n $this->dispatcher->dispatch(new SendReportJob($reportUuid));\n\n // send the podcast report if it set and generated\n if ($reportPodcast && $reportPodcast->getStatus() === AutomatedReportResult::STATUS_GENERATED) {\n $this->dispatcher->dispatch(new SendReportJob(reportUuid: $reportPodcast->getUuid()));\n }\n }\n\n // Track Datadog metrics for automated reports\n $automatedReport = $report->getReport();\n $this->callbackService->pushToDatadog($automatedReport, $report);\n\n if ($reportPodcast) {\n $this->callbackService->pushToDatadog($automatedReport, $reportPodcast);\n }\n\n $this->logger->info(self::LOG_PREFIX . 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' Failed to update report status', [\n 'uuid' => $reportUuid,\n 'error' => $exception->getMessage(),\n ]);\n\n return response()->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500);\n }\n\n return response()->json(['status' => 'ok']);\n }\n}","role_description":"text entry area","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Sync Changes","depth":4,"bounds":{"left":0.0,"top":0.0,"width":0.018055556,"height":0.026666667},"on_screen":false,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Hide This Notification","depth":4,"bounds":{"left":0.0,"top":0.0,"width":0.018055556,"height":0.026666667},"on_screen":false,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Code changed:","depth":4,"bounds":{"left":0.0,"top":0.0,"width":0.088194445,"height":0.027777778},"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Hide","depth":4,"bounds":{"left":0.0,"top":0.0,"width":0.018055556,"height":0.026666667},"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false}]...
|
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|
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|
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|
Downloading plugin 'Windsurf Plugin for Python Downloading plugin 'Windsurf Plugin for Python, JS, Java, Go...'
Project: faVsco.js, menu
Start Listening for PHP Debug Connections
HandleHubspotRateLimitTest
Run 'HandleHubspotRateLimitTest'
Debug 'HandleHubspotRateLimitTest'
More Actions
JetBrains AI
Search Everywhere
IDE and Project Settings
Sync Changes
Hide This Notification
Code changed:
Hide
<?php
declare(strict_types=1);
namespace Jiminny\Http\Controllers\Webhook;
use Carbon\Carbon;
use Illuminate\Contracts\Bus\Dispatcher as BusDispatcher;
use Illuminate\Contracts\Events\Dispatcher as EventDispatcher;
use Illuminate\Http\JsonResponse;
use Illuminate\Http\Request;
use Jiminny\Events\AutomatedReports\AutomatedReportGenerated;
use Jiminny\Exceptions\ModelNotFoundException;
use Jiminny\Http\Controllers\AbstractController;
use Jiminny\Jobs\AutomatedReports\SendReportJob;
use Jiminny\Models\AutomatedReportResult;
use Jiminny\Services\Kiosk\AutomatedReports\AutomatedReportsCallbackService;
use Jiminny\Services\Kiosk\AutomatedReports\AutomatedReportsService;
use Psr\Log\LoggerInterface;
use Throwable;
class ReportController extends AbstractController
{
/**
* Log prefix for all log messages
*/
private const string LOG_PREFIX = '[Report Ready]';
public function __construct(
private readonly AutomatedReportsService $automatedReportsService,
private readonly BusDispatcher $dispatcher,
private readonly LoggerInterface $logger,
private readonly AutomatedReportsCallbackService $callbackService,
private readonly EventDispatcher $eventDispatcher,
) {
}
public function ready(Request $request): JsonResponse
{
$payload = $request->all();
$now = Carbon::now();
$this->logger->info(self::LOG_PREFIX . ' Webhook received', [
'payload' => $payload,
]);
// validate
$reportUuid = $this->callbackService->getResultUuid($payload);
if (empty($reportUuid)) {
return response()->json(['status' => 'error', 'message' => 'Request ID is empty'], status: 400);
}
try {
$report = $this->automatedReportsService->getReportResult($reportUuid);
// validate
if ($this->callbackService->isProcessed($report)) {
$this->logger->warning(self::LOG_PREFIX . ' Report has been already processed', [
'uuid' => $reportUuid,
'currentStatus' => $report->getStatusLabel(),
]);
return response()->json(['status' => 'already_processed']);
}
// always try to get a child podcast cause report configuration cannot be trusted
$reportPodcast = $this->automatedReportsService->findChildResult(
result: $report,
type: AutomatedReportsService::MEDIA_TYPE_PODCAST
);
// update results
$report->update([
'status' => $this->callbackService->getPrimaryStatus($report, $payload),
'response' => $payload,
'generated_at' => $now,
]);
// if a podcast is set, update it
$reportPodcast?->update([
'status' => $this->callbackService->getPodcastStatus($payload),
'response' => $payload,
'generated_at' => $now,
]);
$this->logger->info(self::LOG_PREFIX . ' Report has been processed', [
'uuid' => $reportUuid,
'child_uuid' => $reportPodcast?->getUuid(),
]);
if (! $this->callbackService->isSuccess($payload)) {
$this->logger->warning(self::LOG_PREFIX . ' Error creating report', $payload);
return response()->json(['status' => 'ok']);
}
// If one-off, send the report immediately, if not leave it for the scheduler (automated-reports:send)
if ($report->getReport()->getFrequency() === AutomatedReportsService::FREQUENCY_ONE_OFF) {
// send the primary report
$this->dispatcher->dispatch(new SendReportJob($reportUuid));
// send the podcast report if it set and generated
if ($reportPodcast && $reportPodcast->getStatus() === AutomatedReportResult::STATUS_GENERATED) {
$this->dispatcher->dispatch(new SendReportJob(reportUuid: $reportPodcast->getUuid()));
}
}
// Track Datadog metrics for automated reports
$automatedReport = $report->getReport();
$this->callbackService->pushToDatadog($automatedReport, $report);
if ($reportPodcast) {
$this->callbackService->pushToDatadog($automatedReport, $reportPodcast);
}
$this->logger->info(self::LOG_PREFIX . ' Triggering Event for UserPilot tracking', [
'report_uuid' => $automatedReport->getUuid(),
'result_uuid' => $reportUuid,
]);
$this->eventDispatcher->dispatch(new AutomatedReportGenerated($automatedReport));
} catch (ModelNotFoundException $exception) {
$this->logger->error(self::LOG_PREFIX . ' Report not found', [
'uuid' => $reportUuid,
'error' => $exception->getMessage(),
]);
return response()->json(['status' => 'error', 'message' => 'Report not found'], status: 404);
} catch (Throwable $exception) {
$this->logger->error(self::LOG_PREFIX . ' Failed to update report status', [
'uuid' => $reportUuid,
'error' => $exception->getMessage(),
]);
return response()->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500);
}
return response()->json(['status' => 'ok']);
}
}
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Switch workspaces… (Jiminny Inc) Has new messages
Switch workspaces… (Jiminny Inc) Has new messages
Home
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
Screenshot 2026-05-13 at 11.01.01.png
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
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Nikolay Ivanov
Today at 11:01:50 AM
11:01 AM
Хм, Джейс дали не може да ти помогне?
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Lukas Kovalik
Today at 11:01:52 AM
11:01 AM
ще питам James, предполагам че нямам права
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Today at 11:01:56 AM
11:01
да мерси
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Nikolay Ivanov
Today at 11:01:56 AM
11:01 AM
мда
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Today at 11:01:58 AM
11:01
моля
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Lukas Kovalik
Today at 12:13:43 PM
12:13 PM
Ники сори, още един въпрос имам
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Today at 12:14:12 PM
12:14
когато ги правеше ти FE ли оправя
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Today at 12:15:18 PM
12:15
има vulnerabilities по npm
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Nikolay Ivanov
Today at 12:28:03 PM
12:28 PM
не
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Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
Screenshot 2026-05-13 at 11.01.01.png
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
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Nikolay Ivanov
Today at 11:01:50 AM
11:01 AM
Хм, Джейс дали не може да ти помогне?
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Lukas Kovalik
Today at 11:01:52 AM
11:01 AM
ще питам James, предполагам че нямам права
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Today at 11:01:56 AM
11:01
да мерси
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Nikolay Ivanov
Today at 11:01:56 AM
11:01 AM
мда
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Today at 11:01:58 AM
11:01
моля
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Lukas Kovalik
Today at 12:13:43 PM
12:13 PM
Ники сори, още един въпрос имам
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Today at 12:14:12 PM
12:14
когато ги правеше ти FE ли оправя
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Today at 12:15:18 PM
12:15
има vulnerabilities по npm
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Nikolay Ivanov
Today at 12:28:03 PM
12:28 PM
не
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ViewNavigateLaravelDOCKER181DEV (-zsh)RefactorRunToolsGitWindowDOCKER (docAPP (-zsh₴8211DOCKER (docker-compose)"e802ad473a4f""message"module [x-pack-ql]"elasticsearch1 {"type":"timestamp" :"2026-05-13T09:32:54,789Z"NFO""component" :"o.e.p.PluginsService"cluster.name":"docker-cluster""I"node. name""e802ad473a4f""message":"loaded module[x-pack-rollup]" }elasticsearch"timestamp""INFO",1 {"type":"2026-05-13T09:32:54,789Z""component":"o.e.p.PluginsService"cluster. name":"docker-cluster""node.name""e802ad473a4f""message":"loaded module [x-pack-security]" }elasticsearch1 {"type""timestamp"NFO","component":"o.e.p.PluginsService""2026-05-13T09:32:54,790Z"cluster.name":"docker-cluster""I"node. name""e802ad473a4f""message"."Loadedmodule [x-pack-sql]"}elasticsearch{"type""server""timestamp" :NFO","component":"o.e.p.PluginsService","2026-05-13T09:32:54,790Z""cluster.name" :"docker-cluster""level":"I"node. name": "e802ad473a4f""message" :"loadedmodule [x-pack-stack]" }elasticsearch1 {"type":"server""timestamp" :"2026-05-13T09:32:54,790Z"NFO""component" :"o.e.p.PluginsService""cluster.name":"docker-cluster""level":"I"node.name""e802ad473a4f""message" :"loadedelasticsearch1 {"type":"server"module [x-pack-voting-only-node]" }"timestamp" :NFO","2026-05-13T09:32:54,790Z""level":"I"component": "o.e.p.PluginsService","cluster.name": "docker-cluster","node. name": "e802ad473a4f"', "message": "loaded module [x-pack-watcher]" }elasticsearch1 {"type": "server", "timestamp": "2026-05-13T09:32:54,790Z"NFO", "component": "o.e.p.PluginsService","cluster. name":"docker-cluster""level": "I"node. name":"e802ad473a4f"elasticsearch" "ye " precations Lotmestm', "timestamp": "2026-05-13T09:32:54,956Z", "level": "DEPRECATION","component": "o.e.d.c.s.Settings", "cluster.name":node.name":"docker-cluster","e802ad473a4f", "message":"[node.data] setting was deprecated in Elasticsearch and will be removed in a future release!See the breaking changes documentation forthe next major version." }elasticsearch1 {"type": "server".NFO","component": "o.e.e.NodeEnvironment"onmenes euster-non5-13709:32-c,ust2*:"level": "I"node.name":"e802ad473a4f"', "message": "using [1] data paths, mounts [[/usr/share/elasticsearch/data (/dev/vda1)]], net usable_space [14.1gb], net total_space [58.3gb], types [ext4]"elasticsearch1 {"type": "server""timestamp": "2026-05-13T09:32:54,997Z""level": "INFO","component": "o.e.e.NodeEnvironment""cluster.name": "docker-cluster""node. name": "e802ad473a4f", "message": "heap size [700mb], compressed ordinaryobject pointers [true]"}elasticsearch1 {"type": "server"NFO""timestamp": "2026-05-13T09:32:55,4272""level": "I"component": "o.e.n.Node""cluster.name": "docker-cluster","node.name": "e802ad473a4f""message": "node name [e80Zad473a4f], node ID [e2ZKzgw4Q4aCf2w51jWr1A], clustername [docker-cluster], roles [transform, master,remote_cluster_client, data, ml, data_content, data_hot, data_warm, data_cold, ingest]" }-v View in Docker Desktop• View Configw Enable WatchHelp•HomeDMsActivityFilesLaterMoreSupport Daily • in 2 h 27 m100% <78•Wed 13 May12:33:04→Describe what you are looking forJiminny... vcarosity_lau# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...Nikolay Ivanov6 0MessagesAdd canvas@ Files+Lukas Kovalik 11.Today ~мен все ме праща наhttps://app.vanta.com/c/jiminny.com/employee/onboardingNikolay Ivanov 11:01 AMХм, Джейс дали не може да ти помогне?Lukas Kovalik 11:01 AMще питам James, предполагам че нямам правада мерсиNikolay Ivanov 11:01 AMмда° Direct messages& Nikolay Ivanovdo James Graham. Stoyan Tanev®. Galya Dimitrova&. Steliyan GeorgievLo Petko Kashinski®. Aneliya Angelovaã. Stefka Stoyanova•. Vasil Vasilev •!E. Lukas Kovalik y...МОЛЯLukas Kovalik 12:13 PMНики сори, още един въпрос имамкогато ги правеше ти FE ли оправяима vulnerabilities no npmNikolay Ivanov 12:28 PMнетях ги оставямLukas Kovalik 12:29 PMаз погледнах твоя тикет и там друго нямашесамо FEкак стигна до WorkerAppsJira CloudMessage Nikolay IvanovToast...
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1...
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Switch workspaces… (Jiminny Inc) Has new messages
Switch workspaces… (Jiminny Inc) Has new messages
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Files
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Later
More…
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PnostormVIeWINavicatecodeFV faVsco.js vProject© ReportController.phpx© AutomatedReportResult.phpPlaybackController.phpv Dapp>.circleci> D.cursor>Ga-github> D.sonarlint› D.vscode> D.windsurfvD app› DActionsv D Component> DAclclass keporcuontroller excenas Adstracttontrouler103eetlelninte nntsD ActivityW AcuviLyAnalyuesD ActivitySearchAIACTVIy lyoeD AiAutomation• AIcallscoringASKAnything># DtosuEvents: AskAnythingPromptSeHistorvService.ohoAskJiminnvAiD AWSBilllinaManagement2 Cachel CountrvCustomerAnDatabaseDatadogm DateTimeDeallnsightsm DoalPicke• ElasticSearchD EloquentEncodingEncryptionDESu rakerFeatureFlagsDFFMpegFileSystemu Geckou Gonab Guzz eHttoKevPointsb KioskLanquade Detectionl Livereedif (Sreport->getReport() ->getFrequency() === AutomatedReportsService::FREQUENCY_ONE_OFF) €send the primary revort$this->dispatcher->dispatch(new SendReportJob($reportUuid));// send the podcast report if it set and generatedif (SreportPodcast && $reportPodcast->getStatus() === AutomatedReportResult::STATUS_GENERATED) €$this-›dispatcher-›dispatch(new SendReportJob(reportUuid: $reportPodcast->getUuid()));// Track Datadog metrics for automated reportsSautomatedReport = $report->getReport();scnis->caLLbackservice->pushlovaradoe caucomareakeport, sreporcif (SreportPodcast) {schis->callbackservice->pushlobaradoasautomacedkeport, sreportrodcast^sthis->loqger->intolselt::06_Prerix"revort uund' => sautomatedkenort'result uuid' => Sreportluid.PS$1Sthis->eventDispatcher->dispatch.new} catch (ModelNotFoundException SexceptioSthis->logger->error(self:: L0G PREFIIXIPhpStormerron' => sexcention->detMessadeOl.return response() ->json(['status' >> 'error', 'message' => 'Report not found'], status: 404);catchThrowable Sexcention) ^$this->logger->error(self::LOG_PREFIX . ' Failed to update report status', [luuadi => Coenontllurdi'error' => $exception-›getMessage(),return response()->json(['status' => 'error', 'message' => 'Failed to update report status'], status: 500);return response()->json(['status' => 'ok']);E custom.log $0supoont Dally • In Zn Z/nA SF [jiminny@localhost]f ho_local Uiminny@localnost# console [PKol)A console (EU]A console [STAGING] X# id, uuid, type, provider, playbook_category_id, user_id, Lead_id, contact_id, account_id, opportunity_id, stage_id,# crm confiquration id. crm orovider id. transcrintion id. status.from activities where crm_configuration_id = 1 and type = 'conference'# and crm orovider id is NOT NULLIand provider != 'uploader'and actual_start_time IS NOT NULLORDER by id desc;select * from activities where id = 54747783; # 00U0400000pCzojMACselect p.id, p.activity_type, pc.id, pc.nameFROM playbooks pjoin playbook_categories pc on p.id = pc.playbook_idwhere p.team_id = 1 and p.activity_type = 'event':SELECT * FROM crm_fields WHERE crm_configuration_id = 1 and object_type = 'event';SELECT * FROM crm_field_values WHERE crm_field_id = 4;select * from crm_layouts cl join playbook_layouts pl on cl.id = pl.layout_idWhere crm contiquration 10 = 1 and pl.playbo0k 10 = 1757lololselect * from automated renort results where renort 1d IN 108. 3590select * from activity_searches where id = 10932;select * from activity search filters where activity search 1d = 10932÷select * from automated_reports order by id desc;select * from automated_report_results order by id desc;select * from automated_reports where id IN (55);select * from automated_report_results where id IN (81);select * from users where id IN (10633, 13987, 11985);select * from users where group_id IN (3710);SELECT * FROM automated_reports WHERE uuid_to_bin('18a06a75-afd2-476f-aadc-14d4057bdda2') = uuid;SELECT * FROM automated_report_results WHERE uuid_to_bin(^582d4b50-8cd3-42a9-9819-d676ff8f3b43') = uvid;select * from automated_report_results where media_type = 'pdf' and status = 2;SELECT * FROM automated_report_results WHERE uuid_to_bin('82e74956-6144-4cd1-a3d3-af985c3070a4') = uvid;100% 52• wea 13 May 12.33.02578:33UTF-84 spaces...
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32699
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NULL
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32703
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1253
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7
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2026-05-13T09:33:08.561830+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664788561_m2.jpg...
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Firefox
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NVD - cve-2026-24765 — Work
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1
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nvd.nist.gov/vuln/detail/cve-2026-24765
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monitor_2
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NULL
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
Close tab
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
New Tab
New Tab
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765...
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A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to nvd@nist.gov. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765...
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NVD - cve-2026-24765 — Work
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
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NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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[SRD-6848] Sidekick SMS issue - Jira
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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You said how can I fix these vulnareabilities in laravel project
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how can I fix these vulnareabilities in laravel project
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Gemini said
Gemini said
Fixing this vulnerability in a Laravel project is a very straightforward process. In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.
Here is exactly how to secure your project:
1. Check Your Current Version
1. Check Your Current Version
First, verify which version of PHPUnit your Laravel application is currently using. Run this command in your terminal at the root of your project:
Bash
Download code
Copy code
composer show phpunit/phpunit
Look at the
versions
line in the output to see if you are running a vulnerable version (anything lower than 12.5.8, 11.5.50, 10.5.62, 9.6.33, or 8.5.52).
2. Update PHPUnit...
|
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A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. 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Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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The flaw allows for potential","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Remote Code Execution (RCE)","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"through the unsafe handling of code coverage data.","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Vulnerability Mechanism","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Vulnerability Mechanism","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Root Cause:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"cleanupForCoverage()","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"method in PHPUnit performs deserialization on","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".coverage","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files during PHPT test execution without restricting the classes that can be instantiated (lacking the","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"allowed_classes","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"parameter).","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Attack Vector:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"An attacker with local file write access can place a malicious serialized PHP object into a","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".coverage","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"file.","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Impact:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"__wakeup()","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"magic method, it can trigger arbitrary code execution in the context of the user running the tests.","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Affected Versions","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Affected Versions","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The vulnerability impacts versions prior to:","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"12.x:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Before 12.5.8","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"11.x:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Before 11.5.50","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"10.x:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Before 10.5.62","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"9.x:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Before 9.6.33","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"8.x:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Before 8.5.52","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Risk Assessment","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Risk Assessment","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CVSS Score:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"7.8 (High)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Vector:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Requirement:","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Requires local file write access to the directory where PHPUnit expects coverage files. 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In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is exactly how to secure your project:","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Check Your Current Version","depth":23,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Check Your Current Version","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"First, verify which version of PHPUnit your Laravel application is currently using. Run this command in your terminal at the root of your project:","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Bash","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Download code","depth":25,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy code","depth":25,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"composer show phpunit/phpunit","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Look at the","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"versions","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"line in the output to see if you are running a vulnerable version (anything lower than 12.5.8, 11.5.50, 10.5.62, 9.6.33, or 8.5.52).","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. Update PHPUnit","depth":23,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"}]...
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
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NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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[SRD-6848] Sidekick SMS issue - Jira
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[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
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You said I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765 Detail Description PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control. Metrics NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed. CVSS 3.x Severity and Vector Strings: NIST: NVD Base Score: N/A NVD assessment not yet provided. CNA: GitHub, Inc. Base Score: 7.8 HIGH Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H References to Advisories, Solutions, and Tools By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [EMAIL]. URL Source(s) Tag(s) https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda GitHub, Inc. Patch https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33 GitHub, Inc. Release Notes https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p GitHub, Inc. Mitigation Vendor Advisory https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html CVE Mailing List Third Party Advisory Weakness Enumeration CWE-ID CWE Name Source CWE-502 Deserialization of Untrusted Data GitHub, Inc. Known Affected Software Configurations Switch to CPE 2.2 Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s) From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s) Denotes Vulnerable Software Are we missing a CPE here? Please let us know. Change History 3 change records found show changes Quick Info CVE Dictionary Entry: CVE-2026-24765 NVD Published Date: 01/27/2026 NVD Last Modified: 03/03/2026 Source: GitHub, Inc.</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>NVD - cve-2026-24765</tabTitle>” with “<selection>CVE-2026-24765
Detail
Description
PHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52 involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the `cleanupForCoverage()` method, which deserializes code coverage files without validation, potentially allowing remote code execution if malicious `.coverage` files are present prior to the execution of the PHPT test. The vulnerability occurs when a `.coverage` file, which should not exist before test execution, is deserialized without the `allowed_classes` parameter restriction. An attacker with local file write access can place a malicious serialized object with a `__wakeup()` method into the file system, leading to arbitrary code execution during test runs with code coverage instrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage files for PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies. Rather than just silently sanitizing the input via `['allowed_classes' => false]`, the maintainer has chosen to make the anomalous state explicit by treating pre-existing `.coverage` files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62, 9.6.33, when a `.coverage` file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying the anomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeral runners, code review enforcement, branch protection, artifact isolation, and access control.
Metrics
NVD enrichment efforts reference publicly available information to associate
vector strings. CVSS information contributed by other sources is also
displayed.
CVSS 3.x Severity and Vector Strings:
NIST: NVD
Base
Score: N/A
NVD assessment
not yet provided.
CNA: GitHub, Inc.
Base
Score: 7.8 HIGH
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace.
We have provided these links to other web sites because they
may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web
sites that are more appropriate for your purpose. NIST does
not necessarily endorse the views expressed, or concur with
the facts presented on these sites. Further, NIST does not
endorse any commercial products that may be mentioned on
these sites. Please address comments about this page to [EMAIL].
URL
Source(s)
Tag(s)
https://github.com/sebastianbergmann/phpunit/commit/3141742e00620e2968d3d2e732d320de76685fda
GitHub, Inc.
Patch
https://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/12.5.8
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33
GitHub, Inc.
Release Notes
https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vvj3-c3rp-c85p
GitHub, Inc.
Mitigation
Vendor Advisory
https://lists.debian.org/debian-lts-announce/2026/02/msg00009.html
CVE
Mailing List
Third Party Advisory
Weakness Enumeration
CWE-ID
CWE Name
Source
CWE-502
Deserialization of Untrusted Data
GitHub, Inc.
Known Affected Software Configurations Switch
to CPE 2.2
Configuration 1 ( hide ) cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
Up to (excluding)8.5.52 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)9.0.0Up to (excluding)9.6.33 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)10.0.0Up to (excluding)10.5.62 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)11.0.0Up to (excluding)11.5.50 cpe:2.3:a:phpunit_project:phpunit:*:*:*:*:*:-:*:* Show Matching CPE(s)
From (including)12.0.0Up to (excluding)12.5.8 Configuration 2 ( hide ) cpe:2.3:o:debian:debian_linux:11.0:*:*:*:*:*:*:* Show Matching CPE(s)
Denotes Vulnerable Software
Are we missing a CPE here? Please let us know.
Change History
3 change records found show changes
Quick Info
CVE Dictionary Entry: CVE-2026-24765 NVD
Published Date: 01/27/2026 NVD
Last Modified: 03/03/2026
Source: GitHub, Inc.</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
Summary of CVE-2026-24765: PHPUnit Insecure Deserialization
CVE-2026-24765 describes a high-severity security vulnerability in
PHPUnit
, a popular testing framework for PHP. The flaw allows for potential
Remote Code Execution (RCE)
through the unsafe handling of code coverage data.
Vulnerability Mechanism
Vulnerability Mechanism
Root Cause:
The
cleanupForCoverage()
method in PHPUnit performs deserialization on
.coverage
files during PHPT test execution without restricting the classes that can be instantiated (lacking the
allowed_classes
parameter).
Attack Vector:
An attacker with local file write access can place a malicious serialized PHP object into a
.coverage
file.
Impact:
When PHPUnit runs tests with code coverage instrumentation enabled, it deserializes the malicious file. If the object contains a
__wakeup()
magic method, it can trigger arbitrary code execution in the context of the user running the tests.
Affected Versions
Affected Versions
The vulnerability impacts versions prior to:
12.x:
Before 12.5.8
11.x:
Before 11.5.50
10.x:
Before 10.5.62
9.x:
Before 9.6.33
8.x:
Before 8.5.52
Risk Assessment
Risk Assessment
CVSS Score:
7.8 (High)
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Requirement:
Requires local file write access to the directory where PHPUnit expects coverage files. Common threat environments include compromised CI/CD pipelines, local development machines, or malicious dependencies.
Resolution and Mitigation
Resolution and Mitigation
Official Patch:
The maintainer updated PHPUnit to treat pre-existing
.coverage
files as an error condition rather than attempting to sanitize and process them.
Recommended Actions:
* Update PHPUnit to the latest patched version in your respective release branch.
Implement security best practices in CI/CD, such as using ephemeral runners and strict access controls.
Enforce code reviews and branch protection to prevent malicious file injection.
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You said how can I fix these vulnareabilities in laravel project
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how can I fix these vulnareabilities in laravel project
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Gemini said
Gemini said
Fixing this vulnerability in a Laravel project is a very straightforward process. In Laravel, PHPUnit is managed as a development dependency via Composer, so resolving the issue simply requires updating that package to a patched version.
Here is exactly how to secure your project:
1. Check Your Current Version
1. Check Your Current Version
First, verify which version of PHPUnit your Laravel application is currently using. Run this command in your terminal at the root of your project:
Bash
Download code
Copy code
composer show phpunit/phpunit
Look at the
versions
line in the output to see if you are running a vulnerable version (anything lower than 12.5.8, 11.5.50, 10.5.62, 9.6.33, or 8.5.52).
2. Update PHPUnit...
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Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Slack...
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
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Nikolay Ivanov
Today at 11:01:50 AM
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Хм, Джейс дали не може да ти помогне?
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Lukas Kovalik
Today at 11:01:52 AM
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ще питам James, предполагам че нямам права
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Today at 11:01:56 AM
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да мерси
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Nikolay Ivanov
Today at 11:01:56 AM
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мда
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моля
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Lukas Kovalik
Today at 12:13:43 PM
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Ники сори, още един въпрос имам
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когато ги правеше ти FE ли оправя
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има vulnerabilities по npm
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Nikolay Ivanov
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не
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тях ги оставям
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Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
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Nikolay Ivanov
Today at 11:01:50 AM
11:01 AM
Хм, Джейс дали не може да ти помогне?
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Lukas Kovalik
Today at 11:01:52 AM
11:01 AM
ще питам James, предполагам че нямам права
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Today at 11:01:56 AM
11:01
да мерси
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Nikolay Ivanov
Today at 11:01:56 AM
11:01 AM
мда
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Today at 11:01:58 AM
11:01
моля
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Lukas Kovalik
Today at 12:13:43 PM
12:13 PM
Ники сори, още един въпрос имам
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Today at 12:14:12 PM
12:14
когато ги правеше ти FE ли оправя
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Today at 12:15:18 PM
12:15
има vulnerabilities по npm
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Nikolay Ivanov
Today at 12:28:03 PM
12:28 PM
не
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Today at 12:28:17 PM
12:28
тях ги оставям
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Lukas Kovalik
SlackFileEditViewGoHistoryWindowHelpDOCKER18111DOCKER (docker-compose)NFO""component":e":"e802ad473a4f""o.e.t.TransportService""message":"publish_addressDEV (-zsh)₴82DOCKER (docAPP (-zsh"cluster.name": "docker-cluster""node.nam{[IP_ADDRESS]:9300}, bound_addresses {[::]elasticsearchI {"type": "server""timestamp":"component" :"o.e.c.c.Coordinator""2026-05-13T09:33:19,976Z""cluster.name":"docker-cluster""e802ad473a4f""node. name":"message":"cluster UUID [8uhZw1CUSGyWYR_OvaKx6g]" }"timestamp" :"2026-05-13T09:33:20,383Z""component":"o.e.c.s.MasterService""CCuster. name": "docker-cluster""node. name"e802ad473a4f""message":"elected-as-masternodes joined)[{e802ad473a4f}{e2ZKzgw4Q4aCf2w5ljWr1A}{SiMipGnoTmSDT1N9rN_JSQ}{[IP_ADDRESS]{[IP_ADDRESS]:93003{cdhilmrstw}{ml.machine_memory=4109217792, xpack.installed=true,transform.node=true, ml.max_open_jobs=20} elect leader,_BECOME_MASTER_TASK_, _FINISH_ELECTION_],term: 240,version: 8782, deltnode changed {previous [],current [{e802ad473a4f}{e2ZKzgw4Q4aCf2w5ljWr1A}{SiMipGnoTmSDT1N9rN_JSQ}{[IP_ADDRESS]{[IP_ADDRESS]:9300}{cdhilmrstw}-{ml.machine_memory=41092177xpack.installed=true,transform.node=true,ml.max_open_jobs=20}]}" }elasticsearchI {"type": "server""timestamp":"2026-05-13T09:33:20,763Z""component" :"o.e.c.s.ClusterApplierService""cluster.name" :"docker-cluster""e802ad473a4f", "message":"master node changed {previous [], current [{e802ad473a4f}{e2ZKzgw4Q4aCf2w51jWr1A}{SiMipGnoTmSDT1N9rN_JSQ}{[IP_ADDRESS]{[IP_ADDRESS]:93003{cdhilmrstw}-{ml.machine_memory=4109217792, xpack.installed=true, transform.node=true, ml.max_open_jobs=20}]}, term: 240, version: 8782, reason: Publication{term=240, version=8782}elasticsearch | {"type": "server"', "timestamp": "2026-05-13T09:33:21, 280Z", "level": "INFO", "component": "o.e.h.AbstractHttpServerTransport""cluster.name": "docker-cluster", "node.name": "e802ad473a4f", "message": "publish_address {[IP_ADDRESS]:9200}, bound_addresses {[::]:9200}", "cluster.uuid": "8uhZw1CUSGyWYR_OvaKx6g", "node.id" : "e2ZKzgw4Q4aCf2w5ljWr1A"elasticsearchI {"type": "server", "timestamp": "2026-05-13T09:33:21,281Z","level": "I"component": "o.e.n.Node""cluster.name": "docker-cluster""node. name":73a4f","message": "started", "cluster.uuid": "8uhZw1CUSGyWYR_OvaKx6g", "node.id": "e2ZKzgw4Q4aCf2w5ljWr1A" }elasticsearch | {"type": "server", "timestamp": "2026-05-13T09:33:22,331Z",NFO", "component": "o.e.l.LicenseService", "cluster.name": "docker-cluster","node. name": "e802ad473a4f""message": "license [85e882e5-5714-4173-a5dd-9baa841494a0] mode] - valid", "cluster.uuid": "8uhZw1CUSGyWYR_OvaKx6g", "node.id": "e2ZKzgw4Q4aCf2w51jWr1Aelasticsearch | {"type": "server", "timestamp": "2026-05-13T09:33:22,348Z",NFO", "component": "o.e.g.GatewayService", "cluster.name": "docker-cluster""node. name": "e802ad473a4f", "message": "recovered [15] indices into cluster_state","cluster.uuid""8uhZw1CUSGyWYR_OvaKx6g", "node.id": "e2ZKzgw4Q4aCf2w51jWr1A"View in Docker Desktop• View Configw Enable WatchHomeDMsActivityFilesLaterMoreSupport Daily - in 2 h 27 m100% (C478•Wed 13 May 12:33:25ED→QDescribe what you are looking forJiminny ...carosity_lau# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...Nikolay Ivanov6 0• Messages+° Direct messages& Nikolay Ivanovdo James Graham. Stoyan Tanev. Galya DimitrovaRo Steliyan Georgievo Petko KashinskiR. Aneliya Angelovaã. Stefka Stoyanova€. Vasil Vasilev •Lukas Kovalik y...AppsAdd canvasO FilesLukas Kovalik 11.Today ~мен все ме праща наhttps://app.vanta.com/c/jiminny.com/employee/onboardingNikolay Ivanov 11:01 AMХм, Джейс дали не може да ти помогне?Lukas Kovalik 11:01 AMще питам James, предполагам че нямам правада мерсиNikolay Ivanov 11:01 AMмдаМОЛЯLukas Kovalik 12:13 PMНики сори, още един въпрос имамкогато ги правеше ти FE ли оправяима vulnerabilities no npmNikolay Ivanov 12:28 PMнетях ги оставямLukas Kovalik 12:29 PMаз погледнах твоя тикет и там друго нямашесамо FEкак стигна до WorkerJira CloudMessage Nikolay IvanovToast...
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whisper_backend_init_gpu: found GPU device 0: Meta whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)
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2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted
2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted
2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2
2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)
zsh: terminated npx screenpipe@latest record
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\n2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted\n2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted\n2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2\n2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","depth":4,"on_screen":true,"value":"whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\n2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted\n2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted\n2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2\n2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.19722222,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.19722222,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.2013889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.3940972,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.3982639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.59097224,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.5951389,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.7878472,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.7920139,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"APP (-zsh)","depth":1,"bounds":{"left":0.475,"top":0.033333335,"width":0.05138889,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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whisper_backend_init_gpu: found GPU device 0: Meta whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)
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2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted
2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted
2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2
2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)
zsh: terminated npx screenpipe@latest record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664805746_m2.jpg...
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Slack
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Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Nikolay Ivanov (DM) - Jiminny Inc - 4 new items - Slack...
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Switch workspaces… (Jiminny Inc) Has new messages
Switch workspaces… (Jiminny Inc) Has new messages
Home
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Today at 11:00:45 AM
11:00
къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
Screenshot 2026-05-13 at 11.01.01.png
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Screenshot 2026-05-13 at 11.01.01.png
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Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
React with white_check_mark
React with eyes
React with raised_hands...
|
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Kovalik","depth":23,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":23,"on_screen":true,"role_description":"text"},{"role":"AXLink","text":"Today at 11:00:48 AM","depth":23,"on_screen":true,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"11:00 AM","depth":24,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"например това може ли да 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на","depth":24,"on_screen":true,"role_description":"text"},{"role":"AXLink","text":"https://app.vanta.com/c/jiminny.com/employee/onboarding","depth":24,"on_screen":true,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"https://app.vanta.com/c/jiminny.com/employee/onboarding","depth":25,"on_screen":true,"role_description":"text"},{"role":"AXCheckBox","text":"React with white_check_mark","depth":25,"on_screen":true,"role_description":"toggle button","subrole":"AXToggleButton","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXCheckBox","text":"React with eyes","depth":25,"on_screen":true,"role_description":"toggle button","subrole":"AXToggleButton","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXCheckBox","text":"React with raised_hands","depth":25,"on_screen":true,"role_description":"toggle button","subrole":"AXToggleButton","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false}]...
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Switch workspaces… (Jiminny Inc) Has new messages
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Today at 11:00:45 AM
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къде точно
Lukas Kovalik
Today at 11:00:48 AM
11:00 AM
например това може ли да отвориш
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
https://app.vanta.com/c/jiminny.com/tests/packages-checked-for-vulnerabilities-v2-records-closed-github-dependabot-low?tab=results
Nikolay Ivanov
Today at 11:01:07 AM
11:01 AM
Screenshot 2026-05-13 at 11.01.01.png
Toggle file
Screenshot 2026-05-13 at 11.01.01.png
Download Screenshot 2026-05-13 at 11.01.01.png
Share file: Screenshot 2026-05-13 at 11.01.01.png
View canvas details
More actions
Lukas Kovalik
Today at 11:01:33 AM
11:01 AM
мен все ме праща на
https://app.vanta.com/c/jiminny.com/employee/onboarding
https://app.vanta.com/c/jiminny.com/employee/onboarding
React with white_check_mark
React with eyes
React with raised_hands
rirerox[JY-19967] Upgrade Python and liDependabot alerts • jiminny/proph# (UY-19958] Upgrade BE ibraries -liminny/app/backend-code - VantaNo NVD - cve-2026-24765Low vulnerabilities identified in paciminnylaop/backend-code - Vanta1o NVD - cve-2026-6722fuy-207731 User Pilot not receivin@ JY-19957 | Remove abanded sympTypeError: Leaque\Flysystem\FilesNew Tabu Userpilot | Ask Jiminny Report Gen(SRD-68481 Sidekick SMS issue. 1Y-199571 Unarade BE librariesJY-19957 | Remove abanded symp2 Hich vulnerabilities identified in oã(* Medium vulnerabilities identified inLow vulnerabilities identified in pa• Goodle geminiPronlles10019Windownvd.nist.gov/vuln/detail/cve-2026-24765••• XFixing this vulnerability in a Laravel project is avery straightforward process. In Laravel,PHPUnit is managed as a developmentdependency via Composer, so resolving theissue simply requires updating that package toa patched version.Here is exactiv now to secure vour orolect"Check Your current VersionFirst, verify which version of PHPUnit yourLaravel application is currently using. Run thiscommand in your terminal at the root of yourproject:composer show phpunit/phpunitLook at the versions line in the output to seeif you are running a vulnerable version(anything lower than 12.5.8, 11.5.50, 10.5.62,9633. 0r 85. 5212. Update PHPUnitTell Composer to update PHPUnit and itsassociared derendencies to tne latest secureversions allowed ov vour comooser. isonconstraintsEnter a prompt for GeminiAl lt can make mistakes, so double check it. Your privacy &Summarize page‹ S0 liil 1 Support Daily- in 2h 27 mlAJ100% C4 8 • Wed 13 May 12:33:25XCVE-2026-24765 DetailDescriptionPHPUnit is a testing framework for PHP. A vulnerability has been discovered in versions prior to 12.5.8, 11.5.50, 10.5.62, 9.6.33, and 8.5.52involving unsafe deserialization of code coverage data in PHPT test execution. The vulnerability exists in the 'cleanupForCoverage()* method,which deserializes code coverage files without alidation, potentially allowing remote code execution if malicious ' coverage files arepresent prior to the execution of the PHPT test. The vulnerability occurs when a'.coverage' file, which should not exist before test execution,Is deserialized without the allowed_classes parameter restriction. An attacker with local file write access can place a malicious serializedobiect with a__wakeup()* method into the file system, leading to arbitrary code execution during test runs with code coverageinstrumentation enabled. This vulnerability requires local file write access to the location where PHPUnit stores or expects code coverage filesfor PHPT tests. This can occur through CI/CD pipeline attacks, the local development environment, and/or compromised dependencies.Rather than just silently sanitizing the input via '['allowed_classes' => false]*, the maintainer has chosen to make the anomalous stateexplicit by treating pre-existing ':coverage* files for PHPT tests as an error condition. Starting in versions in versions 12.5.8, 11.5.50, 10.5.62,9.6.33, when a'coverage* file is detected for a PHPT test prior to execution, PHPUnit will emit a clear error message identifying theanomalous state. Organizations can reduce the effective risk of this vulnerability through proper CI/CD configuration, including ephemeralrunners, code review enforcement, branch protection, artifact isolation, and access control.MetricsCVSS Version 4.0cuss version 3.›CUss Version 2.01NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displaved.CVSS 3.x Severity and Vector Strings:NIST. NVDBase Score: N/ANVD assessment not yet provided.CNA: GitHub, Inc.Base Score: 7.8 HIGIVector. CVSS'2 1/AV• IAC•UPR•/UI-N/S•U/C•H/IHIA•HIReferences to Advisories, Solutions, and ToolsBy selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may haveinformation that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from thispage. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed,or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned onthese sites. Please address comments about this page to [EMAIL]:/lgithuh.com/sehastianheromann/nhnunit/commit/3141742e00620e2968d3d2e732d320de76685fdahttps://github.com/sebastianbergmann/phpunit/releases/tag/10.5.63https://github.com/sebastianbergmann/phpunit/releases/tag/11.5.50ihtins:/loithuh.com/sehastianheromann/nhnunit/releases/tag/12_5.8lhttps://github.com/sebastianbergmann/phpunit/releases/tag/8.5.52https://github.com/sebastianbergmann/phpunit/releases/tag/9.6.33https://github.com/sebastianbergmann/phpunit/security/advisories/GHSA-vj3-c3rp-c85pSource(s)GitHub.IngTag(s)GitHub, Inc.GitHub, Inc.GitHuh.IncGitHub, Inc.GitHub, Inc.GitHub, Inc.Салао ватоVendor AdvisoryQUICK INFOCVE Dictionary Entry:CVE-2026-24765NVD Published Date:01/27/2026NVD Last Modified:03/03/2026Source:GitHub. Ind...
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whisper_backend_init_gpu: found GPU device 0: Meta whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)
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2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted
2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted
2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2
2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)
zsh: terminated npx screenpipe@latest record
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|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\n2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted\n2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted\n2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2\n2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","depth":4,"on_screen":true,"value":"whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\n2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted\n2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted\n2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)\n2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)\n2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2\n2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.0944149,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.36469415,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.36668882,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.45894283,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4609375,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5531915,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.55518615,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.64744014,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.64943486,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7280585,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"APP (-zsh)","depth":1,"bounds":{"left":0.4976729,"top":1.0,"width":0.024601065,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
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whisper_backend_init_gpu: found GPU device 0: Meta whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:41:06.939405Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:41:27.647937Z INFO screenpipe_audio::transcription::handle_new_transcript: device MacBook Pro Microphone (input) skipping duplicate transcript (entire content overlaps with previous)
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
2026-05-12T21:41:59.317221Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3440566600782839939, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:43:08.720605Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:44:11.518742Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-12T21:44:12.276375Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.4MB → 0.4MB (4.0x), 10 JPEGs deleted
2026-05-12T21:44:12.983817Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:13.060085Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.5MB → 0.2MB (7.0x), 10 JPEGs deleted
2026-05-12T21:44:14.128680Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:14.131824Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=830658247309044920, trigger=click)
2026-05-12T21:44:16.574164Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:19.656976Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:22.673874Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8311882007572234868, trigger=visual_change)
2026-05-12T21:44:29.611055Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8311882007572234868, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T21:45:10.439111Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T21:46:05.778707Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-12T21:46:10.782449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-12T21:46:10.833161Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 2
2026-05-12T21:46:10.850809Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-12T21:46:10.943081Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T21:46:11.015324Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T21:46:12.422572Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=2699797568401243855, trigger=click)
zsh: terminated npx screenpipe@latest record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $
DOCKER
Close Tab
DEV (-zsh)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
⌥⌘1
APP (-zsh)...
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NULL
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NULL
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NULL
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NULL
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32709
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1253
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10
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2026-05-13T09:33:31.148032+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664811148_m2.jpg...
|
iTerm2
|
DEV (-zsh)
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1
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NULL
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monitor_2
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NULL
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NULL
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NULL
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NULL
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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $
DOCKER
Close Tab
DEV (-zsh)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
⌥⌘1
DEV (-zsh)...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Tue May 12 20:12:05 on ttys006\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker: 'docker exec' requires at least 2 arguments\n\nUsage: docker exec [OPTIONS] CONTAINER COMMAND [ARG...]\n\nSee 'docker exec --help' for more information\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","depth":4,"bounds":{"left":0.27027926,"top":1.0,"width":0.4793883,"height":-0.06304872},"on_screen":true,"value":"Last login: Tue May 12 20:12:05 on ttys006\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker: 'docker exec' requires at least 2 arguments\n\nUsage: docker exec [OPTIONS] CONTAINER COMMAND [ARG...]\n\nSee 'docker exec --help' for more information\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.0944149,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.36469415,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.36668882,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.45894283,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4609375,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5531915,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.55518615,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.64744014,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.64943486,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7280585,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"DEV (-zsh)","depth":1,"bounds":{"left":0.4976729,"top":1.0,"width":0.024933511,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
|
-4787217529817495859
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-4142645165976770429
|
click
|
accessibility
|
NULL
|
Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $
DOCKER
Close Tab
DEV (-zsh)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
⌥⌘1
DEV (-zsh)...
|
32708
|
NULL
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NULL
|
NULL
|
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32710
|
1252
|
12
|
2026-05-13T09:33:34.606536+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664814606_m1.jpg...
|
iTerm2
|
DEV (docker)
|
1
|
NULL
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
root@docker_lamp_1:/home/jiminny#
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
⌥⌘1
DEV (docker)...
|
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login: Tue May 12 20:12:05 on ttys006\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker: 'docker exec' requires at least 2 arguments\n\nUsage: docker exec [OPTIONS] CONTAINER COMMAND [ARG...]\n\nSee 'docker exec --help' for more information\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\nroot@docker_lamp_1:/home/jiminny#","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.19722222,"height":0.026666667},"on_screen":true,"role_description":"radio 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(-zsh)","depth":2,"bounds":{"left":0.3940972,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.3982639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.59097224,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.5951389,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.7878472,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.7920139,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"DEV (docker)","depth":1,"bounds":{"left":0.46944445,"top":0.033333335,"width":0.0625,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
-4866017581599879076
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-4421726990668257133
|
visual_change
|
accessibility
|
NULL
|
Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
root@docker_lamp_1:/home/jiminny#
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
⌥⌘1
DEV (docker)...
|
NULL
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NULL
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NULL
|
NULL
|
|
32711
|
1253
|
11
|
2026-05-13T09:33:37.272478+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664817272_m2.jpg...
|
iTerm2
|
DEV (docker)
|
1
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
root@docker_lamp_1:/home/jiminny#
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
⌥⌘1
DEV (docker)...
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Tue May 12 20:12:05 on ttys006\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker: 'docker exec' requires at least 2 arguments\n\nUsage: docker exec [OPTIONS] CONTAINER COMMAND [ARG...]\n\nSee 'docker exec --help' for more information\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\nroot@docker_lamp_1:/home/jiminny#","depth":4,"bounds":{"left":0.27027926,"top":1.0,"width":0.4793883,"height":-0.06304872},"on_screen":true,"value":"Last login: Tue May 12 20:12:05 on ttys006\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker: 'docker exec' requires at least 2 arguments\n\nUsage: docker exec [OPTIONS] CONTAINER COMMAND [ARG...]\n\nSee 'docker exec --help' for more information\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\nroot@docker_lamp_1:/home/jiminny#","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.0944149,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.36469415,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.36668882,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.45894283,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4609375,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5531915,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.55518615,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.64744014,"top":1.0,"width":0.09424867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.64943486,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7280585,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"DEV (docker)","depth":1,"bounds":{"left":0.4950133,"top":1.0,"width":0.029920213,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
root@docker_lamp_1:/home/jiminny#
DOCKER
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APP (-zsh)
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screenpipe"
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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
root@docker_lamp_1:/home/jiminny# composer show phpunit/phpunit
name : phpunit/phpunit
descrip. : The PHP Unit Testing framework.
keywords : phpunit, testing, xunit
versions : * 11.5.55
type : library
license : BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) (OSI approved) [URL_WITH_CREDENTIALS]
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
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⌥⌘1
DEV (docker)...
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Tue May 12 20:12:05 on ttys006\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker: 'docker exec' requires at least 2 arguments\n\nUsage: docker exec [OPTIONS] CONTAINER COMMAND [ARG...]\n\nSee 'docker exec --help' for more information\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\nroot@docker_lamp_1:/home/jiminny# composer show phpunit/phpunit\nname : phpunit/phpunit\ndescrip. : The PHP Unit Testing framework.\nkeywords : phpunit, testing, xunit\nversions : * 11.5.55\ntype : library\nlicense : BSD 3-Clause \"New\" or \"Revised\" License (BSD-3-Clause) (OSI approved) https://spdx.org/licenses/BSD-3-Clause.html#licenseText\nhomepage : https://phpunit.de/\nsource : [git] https://github.com/sebastianbergmann/phpunit.git adc7262fccc12de2b30f12a8aa0b33775d814f00\ndist : [zip] https://api.github.com/repos/sebastianbergmann/phpunit/zipball/adc7262fccc12de2b30f12a8aa0b33775d814f00 adc7262fccc12de2b30f12a8aa0b33775d814f00\npath : /home/jiminny/vendor/phpunit/phpunit\nnames : phpunit/phpunit\n\nsupport\nissues : https://github.com/sebastianbergmann/phpunit/issues\nsecurity : https://github.com/sebastianbergmann/phpunit/security/policy\nsource : https://github.com/sebastianbergmann/phpunit/tree/11.5.55\n\nautoload\nfiles\nclassmap\nsrc/\n\nrequires\next-dom *\next-json *\next-libxml *\next-mbstring *\next-xml *\next-xmlwriter *\nmyclabs/deep-copy ^1.13.4\nphar-io/manifest ^2.0.4\nphar-io/version ^3.2.1\nphp >=8.2\nphpunit/php-code-coverage ^11.0.12\nphpunit/php-file-iterator ^5.1.1\nphpunit/php-invoker ^5.0.1\nphpunit/php-text-template ^4.0.1\nphpunit/php-timer ^7.0.1\nsebastian/cli-parser ^3.0.2\nsebastian/code-unit ^3.0.3\nsebastian/comparator ^6.3.3\nsebastian/diff ^6.0.2\nsebastian/environment ^7.2.1\nsebastian/exporter ^6.3.2\nsebastian/global-state ^7.0.2\nsebastian/object-enumerator ^6.0.1\nsebastian/recursion-context ^6.0.3\nsebastian/type ^5.1.3\nsebastian/version ^5.0.2\nstaabm/side-effects-detector ^1.0.5\n\nsuggests\next-soap To be able to generate mocks based on WSDL files\nroot@docker_lamp_1:/home/jiminny#","depth":4,"on_screen":true,"value":"Last login: Tue May 12 20:12:05 on ttys006\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker: 'docker exec' requires at least 2 arguments\n\nUsage: docker exec [OPTIONS] CONTAINER COMMAND [ARG...]\n\nSee 'docker exec --help' for more information\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\nroot@docker_lamp_1:/home/jiminny# composer show phpunit/phpunit\nname : phpunit/phpunit\ndescrip. : The PHP Unit Testing framework.\nkeywords : phpunit, testing, xunit\nversions : * 11.5.55\ntype : library\nlicense : BSD 3-Clause \"New\" or \"Revised\" License (BSD-3-Clause) (OSI approved) https://spdx.org/licenses/BSD-3-Clause.html#licenseText\nhomepage : https://phpunit.de/\nsource : [git] https://github.com/sebastianbergmann/phpunit.git adc7262fccc12de2b30f12a8aa0b33775d814f00\ndist : [zip] https://api.github.com/repos/sebastianbergmann/phpunit/zipball/adc7262fccc12de2b30f12a8aa0b33775d814f00 adc7262fccc12de2b30f12a8aa0b33775d814f00\npath : /home/jiminny/vendor/phpunit/phpunit\nnames : phpunit/phpunit\n\nsupport\nissues : https://github.com/sebastianbergmann/phpunit/issues\nsecurity : https://github.com/sebastianbergmann/phpunit/security/policy\nsource : https://github.com/sebastianbergmann/phpunit/tree/11.5.55\n\nautoload\nfiles\nclassmap\nsrc/\n\nrequires\next-dom *\next-json *\next-libxml *\next-mbstring *\next-xml *\next-xmlwriter *\nmyclabs/deep-copy ^1.13.4\nphar-io/manifest ^2.0.4\nphar-io/version ^3.2.1\nphp >=8.2\nphpunit/php-code-coverage ^11.0.12\nphpunit/php-file-iterator ^5.1.1\nphpunit/php-invoker ^5.0.1\nphpunit/php-text-template ^4.0.1\nphpunit/php-timer ^7.0.1\nsebastian/cli-parser ^3.0.2\nsebastian/code-unit ^3.0.3\nsebastian/comparator ^6.3.3\nsebastian/diff ^6.0.2\nsebastian/environment ^7.2.1\nsebastian/exporter ^6.3.2\nsebastian/global-state ^7.0.2\nsebastian/object-enumerator ^6.0.1\nsebastian/recursion-context ^6.0.3\nsebastian/type ^5.1.3\nsebastian/version ^5.0.2\nstaabm/side-effects-detector ^1.0.5\n\nsuggests\next-soap To be able to generate mocks based on WSDL files\nroot@docker_lamp_1:/home/jiminny#","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.19722222,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.19722222,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio 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Tab","depth":3,"bounds":{"left":0.3982639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.59097224,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.5951389,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.7878472,"top":0.05888889,"width":0.196875,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.7920139,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"DEV (docker)","depth":1,"bounds":{"left":0.46944445,"top":0.033333335,"width":0.0625,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
root@docker_lamp_1:/home/jiminny# composer show phpunit/phpunit
name : phpunit/phpunit
descrip. : The PHP Unit Testing framework.
keywords : phpunit, testing, xunit
versions : * 11.5.55
type : library
license : BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) (OSI approved) [URL_WITH_CREDENTIALS]
DOCKER
Close Tab
DEV (docker)
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screenpipe"
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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
root@docker_lamp_1:/home/jiminny# composer show phpunit/phpunit
name : phpunit/phpunit
descrip. : The PHP Unit Testing framework.
keywords : phpunit, testing, xunit
versions : * 11.5.55
type : library
license : BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) (OSI approved) [URL_WITH_CREDENTIALS]
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
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⌥⌘1
DEV (docker)...
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Tue May 12 20:12:05 on ttys006\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker: 'docker exec' requires at least 2 arguments\n\nUsage: docker exec [OPTIONS] CONTAINER COMMAND [ARG...]\n\nSee 'docker exec --help' for more information\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\nroot@docker_lamp_1:/home/jiminny# composer show phpunit/phpunit\nname : phpunit/phpunit\ndescrip. : The PHP Unit Testing framework.\nkeywords : phpunit, testing, xunit\nversions : * 11.5.55\ntype : library\nlicense : BSD 3-Clause \"New\" or \"Revised\" License (BSD-3-Clause) (OSI approved) https://spdx.org/licenses/BSD-3-Clause.html#licenseText\nhomepage : https://phpunit.de/\nsource : [git] https://github.com/sebastianbergmann/phpunit.git adc7262fccc12de2b30f12a8aa0b33775d814f00\ndist : [zip] https://api.github.com/repos/sebastianbergmann/phpunit/zipball/adc7262fccc12de2b30f12a8aa0b33775d814f00 adc7262fccc12de2b30f12a8aa0b33775d814f00\npath : /home/jiminny/vendor/phpunit/phpunit\nnames : phpunit/phpunit\n\nsupport\nissues : https://github.com/sebastianbergmann/phpunit/issues\nsecurity : https://github.com/sebastianbergmann/phpunit/security/policy\nsource : https://github.com/sebastianbergmann/phpunit/tree/11.5.55\n\nautoload\nfiles\nclassmap\nsrc/\n\nrequires\next-dom *\next-json *\next-libxml *\next-mbstring *\next-xml *\next-xmlwriter *\nmyclabs/deep-copy ^1.13.4\nphar-io/manifest ^2.0.4\nphar-io/version ^3.2.1\nphp >=8.2\nphpunit/php-code-coverage ^11.0.12\nphpunit/php-file-iterator ^5.1.1\nphpunit/php-invoker ^5.0.1\nphpunit/php-text-template ^4.0.1\nphpunit/php-timer ^7.0.1\nsebastian/cli-parser ^3.0.2\nsebastian/code-unit ^3.0.3\nsebastian/comparator ^6.3.3\nsebastian/diff ^6.0.2\nsebastian/environment ^7.2.1\nsebastian/exporter ^6.3.2\nsebastian/global-state ^7.0.2\nsebastian/object-enumerator ^6.0.1\nsebastian/recursion-context ^6.0.3\nsebastian/type ^5.1.3\nsebastian/version ^5.0.2\nstaabm/side-effects-detector ^1.0.5\n\nsuggests\next-soap To be able to generate mocks based on WSDL files\nroot@docker_lamp_1:/home/jiminny#","depth":4,"bounds":{"left":0.27027926,"top":0.6895451,"width":0.4793883,"height":0.3104549},"on_screen":true,"value":"Last login: Tue May 12 20:12:05 on ttys006\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker: 'docker exec' requires at least 2 arguments\n\nUsage: docker exec [OPTIONS] CONTAINER COMMAND [ARG...]\n\nSee 'docker exec --help' for more information\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev\nroot@docker_lamp_1:/home/jiminny# composer show phpunit/phpunit\nname : phpunit/phpunit\ndescrip. : The PHP Unit Testing framework.\nkeywords : phpunit, testing, xunit\nversions : * 11.5.55\ntype : library\nlicense : BSD 3-Clause \"New\" or \"Revised\" License (BSD-3-Clause) (OSI approved) https://spdx.org/licenses/BSD-3-Clause.html#licenseText\nhomepage : https://phpunit.de/\nsource : [git] https://github.com/sebastianbergmann/phpunit.git 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Last login: Tue May 12 20:12:05 on ttys006
Poetry Last login: Tue May 12 20:12:05 on ttys006
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug /bin/bash
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ dev
root@docker_lamp_1:/home/jiminny# composer show phpunit/phpunit
name : phpunit/phpunit
descrip. : The PHP Unit Testing framework.
keywords : phpunit, testing, xunit
versions : * 11.5.55
type : library
license : BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) (OSI approved) [URL_WITH_CREDENTIALS]
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
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-zsh
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screenpipe"
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DEV (docker)...
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NVD - cve-2026-24765 — Work
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
Close tab
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
New Tab
New Tab
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
New Tab
Customize sidebar
Close Google Gemini (⌃X)
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WORK, Google Account: [EMAIL]
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-1640126304560497898
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click
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NULL
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
Close tab
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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NULL
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NULL
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NULL
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NULL
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32715
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1253
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13
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2026-05-13T09:34:22.778675+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778664862778_m2.jpg...
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Firefox
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NVD - cve-2026-24765 — Work
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1
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nvd.nist.gov/vuln/detail/cve-2026-24765
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monitor_2
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NULL
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NULL
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NULL
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NULL
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
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[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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[JY-19967] Upgrade Python and libraries - Apr - Ji [JY-19967] Upgrade Python and libraries - Apr - Jira
[JY-19967] Upgrade Python and libraries - Apr - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-24765
NVD - cve-2026-24765
Close tab
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
jiminny/app/backend-code - Vanta
jiminny/app/backend-code - Vanta
NVD - cve-2026-6722
NVD - cve-2026-6722
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
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[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
High vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Medium vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
Low vulnerabilities identified in packages are addressed (GitHub Repo) - Vanta
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