Long Term Support Channel Update for ChromeOS

A new LTS-144  version 144.0.7559.257(Platform Version: 16503.90.0), is being rolled out for most ChromeOS devices. 


This version includes selected security fixes including:


520202726 High CVE-2026-12467 Use after free in Extensions


521495992 High CVE-2026-13029 Use after free in Web Authentication


495948109 Critical CVE-2026-8514 Use after free in Aura


522566295 Critical CVE-2026-12443 Use after free in Web Authentication


519248779 High CVE-2026-12033 Out of bounds read


516902973 High CVE-2026-11673 Use after free in InterestGroups


515419790 High CVE-2026-11668 Uninitialized Use in Codecs


513750691 High CVE-2026-10006 Race in WebAudio


501524262 High CVE-2026-9931 Use after free in GPU


496271580 High CVE-2026-9897 Use after free in DOM


Release notes for LTS-144 can be found here 

Want to know more about Long-term Support? Click here

Andy Wu

Google Chrome OS


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Chrome for Android Update

  Hi, everyone! We've just released Chrome 150 (150.0.7871.114) for Android. It'll become available on Google Play over the next few days. 

This release includes stability and performance improvements. You can see a full list of the changes in the Git log. If you find a new issue, please let us know by filing a bug.


Android releases contain the same security fixes as their corresponding Desktop releases (Windows & Mac: 150.0.7871.114/115, Linux: 150.0.7871.114) unless otherwise noted.

Krishna Govind
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Stable Channel Update for Desktop

The Stable channel has been updated to 150.0.7871.114/.115 for Windows and Mac and 150.0.7871.114 for Linux, which will roll out over the coming days/weeks. A full list of changes in this build is available in the Log

Security Fixes and Rewards

Note: Access to bug details and links may be kept restricted until a majority of users are updated with a fix. We will also retain restrictions if the bug exists in a third party library that other projects similarly depend on, but haven’t yet fixed.


This update includes 27 security fixes. Please see the Chrome Security Page for more information.

[N/A][518006275] Critical CVE-2026-15112: Use after free in Ozone. Reported by Google on 2026-05-29

[N/A][524045160] Critical CVE-2026-15129: Use after free in Views. Reported by Google on 2026-06-15

[$500][527385397] High CVE-2026-15132: Uninitialized Use in V8. Reported by Pierre Langlois from Arm on 2026-06-24

[$500][527406824] High CVE-2026-15133: Use after free in InterestGroups. Reported by Jihyeon Jeong (Compsec Lab, Seoul National University / Research Intern) on 2026-06-24

[N/A][515443146] High CVE-2026-15108: Integer overflow in Extensions API. Reported by Google on 2026-05-21

[N/A][516899138] High CVE-2026-15109: Uninitialized Use in ANGLE. Reported by Google on 2026-05-26

[N/A][516948486] High CVE-2026-15110: Use after free in Extensions. Reported by Google on 2026-05-27

[N/A][517508651] High CVE-2026-15111: Use after free in Views. Reported by Google on 2026-05-28

[N/A][520540744] High CVE-2026-15113: Use after free in Autofill. Reported by Google on 2026-06-05

[N/A][520565945] High CVE-2026-15114: Out of bounds read and write in Codecs. Reported by Google on 2026-06-06

[N/A][520576676] High CVE-2026-15115: Insufficient validation of untrusted input in WebAppInstalls. Reported by Google on 2026-06-06

[N/A][522092013] High CVE-2026-15116: Use after free in Actor. Reported by Google on 2026-06-10

[N/A][522568496] High CVE-2026-15117: Use after free in Payments. Reported by Google on 2026-06-11

[N/A][523238265] High CVE-2026-15118: Use after free in Input. Reported by Google on 2026-06-12

[N/A][523505418] High CVE-2026-15119: Inappropriate implementation in GetUserMedia. Reported by Google on 2026-06-13

[N/A][523609602] High CVE-2026-15120: Use after free in Core. Reported by Google on 2026-06-13

[N/A][523712556] High CVE-2026-15121: Use after free in WebRTC. Reported by Google on 2026-06-14

[N/A][523717219] High CVE-2026-15122: Insufficient validation of untrusted input in Codecs. Reported by Google on 2026-06-14

[N/A][523729553] High CVE-2026-15123: Insufficient data validation in DOM. Reported by Google on 2026-06-14

[N/A][523735038] High CVE-2026-15124: Insufficient policy enforcement in Passwords. Reported by Google on 2026-06-14

[N/A][523737685] High CVE-2026-15125: Inappropriate implementation in Forms. Reported by Google on 2026-06-14

[N/A][523748081] High CVE-2026-15126: Use after free in Forms. Reported by Google on 2026-06-14

[N/A][523752265] High CVE-2026-15127: Inappropriate implementation in WebGL. Reported by Google on 2026-06-14

[N/A][523756329] High CVE-2026-15128: Inappropriate implementation in Forms. Reported by Google on 2026-06-14

[N/A][526541544] High CVE-2026-15130: Insufficient policy enforcement in Navigation. Reported by Google on 2026-06-22

[$2000][503553615] Medium CVE-2026-15107: Use after free in IndexedDB. Reported by zh1x1an1221 of Ant Group Tianqiong Security Lab on 2026-04-17

[N/A][526542464] Medium CVE-2026-15131: Insufficient data validation in Navigation. Reported by Google on 2026-06-22


We would also like to thank all security researchers that worked with us during the development cycle to prevent security bugs from ever reaching the stable channel.


Many of our security bugs are detected using AddressSanitizer, MemorySanitizer, UndefinedBehaviorSanitizer, Control Flow Integrity, libFuzzer, or AFL.


Interested in switching release channels? Find out how here. If you find a new issue, please let us know by filing a bug. The community help forum is also a great place to reach out for help or learn about common issues.


Daniel Yip

Google Chrome

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Convert your Google Slides to videos in 7 additional languages

Google Vids already lets you convert your Slides content into Vids with AI-generated scripts, voiceovers, background music, and animations for presentations and accounts in English.

We’re now expanding support to French, German, Italian, Japanese, Korean, Portuguese, and Spanish. 

Getting started

Rollout pace

Availability

  • Business: Business Starter, Standard, and Plus
  • Enterprise: Enterprise Starter, Standard, and Plus
  • Education: Education Plus
  • Consumer: Google AI Pro and Ultra
  • Other Editions: Enterprise Essentials and Enterprise Essentials Plus; Nonprofits
  • Education Add-ons: Google AI Pro for Education; Teaching and Learning
  • Other Add-ons: AI Expanded Access

Resources

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Evolving how LLMs are measured for Android: the next era of Android Bench

Posted by Zoe Lopez-Latorre, Senior Developer Relations Engineer, Android



Back in March, we introduced Android Bench—our LLM leaderboard for real-world Android development tasks. Our goal was to provide transparency around model capabilities in Android development and to encourage model improvements, to give you more helpful AI options for your everyday workflow. Since then, we have enhanced the benchmark based on your feedback, including evaluating open-weight models and adding cost and efficiency dimensions to the leaderboard.

But AI capabilities are ever-evolving, and measurement needs to follow suit. As part of our July release, we have adopted the Harbor framework, which includes an updated version of the benchmarking agent used to evaluate models.

Along with this change to our evaluation, in this July release we’re adding 8 new models (Claude Fable 5, Claude Sonnet 5, Claude Opus 4.8, GLM 5.2, Kimi K2.7 Code, MiniMax M3, Qwen 3.7 Plus and Qwen 3.7 Max) to the leaderboard. We’re also sharing opportunities for you, the Android developer community, to contribute to the benchmark.

Upgrading our methodology with the Harbor framework

When we designed Android Bench, we anchored our methodology on leading industry standards available at the time. We used mini-swe-agent v1, a general-purpose benchmarking agent, and adapted it to the nuances of Android development to provide a baseline measurement for the capabilities of models for common Android development tasks.

To continue providing you with state-of-the-art evaluations that accurately measure the latest model capabilities on Android development, we are standardizing our benchmark to the Harbor framework. Harbor defines standards and integrations that make it easy for anyone to run the benchmark, evaluate their preferred set-up, or share results – providing you with additional transparency and visibility.

This upgrade enables us to more rigorously evaluate models and their capabilities, and we re-ran the benchmark on all models to establish an updated baseline. This means there is a minor shift in scoring, but you will still be able to view historical scores within the archive on our website.

We want to ensure Android Bench is helpful for you, so we will continuously update it as our evaluations and the industry mature.

Expanding the leaderboard with 8 new models

As part of our commitment to keeping the leaderboard fresh, we have added Claude Fable 5, Claude Sonnet 5, Claude Opus 4.8, GLM 5.2, Kimi K2.7 Code, MiniMax M3, Qwen 3.7 Plus and Qwen 3.7 Max to the Android Bench leaderboard.

You will see that Claude Fable 5 is at the top of the leaderboard with a score of 84.5, followed by GPT 5.5 with 80.2, with Claude Sonnet 5 in 3rd with a score of 76.2.

When just comparing Open-weight models, GLM 5.2 is at the top with 72.2, followed by Kimi K2.7 Code with a score of 70.4.

You can check out model performance and efficiency metrics on the updated leaderboard to see how these new and previous models navigate Android-specific challenges like Jetpack Compose migrations, wearable networking, and platform API updates.

Opening Android Bench to community contributions

From the beginning, we’ve valued an open and transparent approach, which is why we made our original methodology and test harness publicly available on GitHub. You’ve asked for a way to provide feedback on our dataset, so now we’re taking collaboration a step further by giving you, the Android developer community, a chance to shape Android Bench.

Starting today, you can contribute to Android Bench in two ways:

We will be reviewing the submitted tasks and will be assessing if they get added to the benchmark. We hope to build a benchmark that truly reflects the diverse, day-to-day realities of the global Android developer community.

Looking ahead

With more and more options for agentic development, maintaining a cutting-edge benchmark ensures that the AI assistance you rely on keeps getting smarter, more helpful, and more effective. Head over to our GitHub repository to check out the tasks. We invite you to submit a task to our team for review, and you can check out Harbor Hub to explore the dataset or submit evaluations.

As always, you can find the updated leaderboard, or read the methodology on our website.

Android Bench, LLM leaderboard, Harbor framework, Android development, Claude Fable 5, GPT 5.5, Claude Sonnet 5, GLM 5.2, Kimi K2.7 Code, MiniMax M3, Qwen 3.7 Plus, Qwen 3.7 Max, AI benchmarking, Jetpack Compose migration, wearable networking, mobile AI agent, Zoe Lopez-Latorre, model evaluation, open-weight models, developer community contributions.
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