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CodeQL version 2.20.5 has been released and includes a host of coverage improvements, including extended support for C# 13 and new detection capabilities for Java and GitHub Actions workflow files.

CodeQL is the static analysis engine that powers GitHub code scanning, which finds and remediates security issues in your code.

CodeQL 2.20.5 adds full support for new language features introduced in C# 13 / .NET 9, as well improved coverage for .NET 9. This will improve the detection of alerts and reduce the chance of false negative results.

CodeQL Java analysis is improved with additional support for Cross Site Request Forgery (CSRF). The new analysis capability detects vulnerabilities that occur when using HTTP request types that are not protected against cross site requests by default.

Go analysis has been updated to support Go 1.24, which includes new language features and improvements. This will improve the detection of alerts and reduce the chance of false negative results.

For a full list of changes, please refer to the complete changelog for version 2.20.5. Every new version of CodeQL is automatically deployed to users of GitHub code scanning on GitHub.com. The new functionality in CodeQL 2.20.5 will also be included in GitHub Enterprise Server (GHES) version 3.17. If you use an older version of GHES, you can manually upgrade your CodeQL version.

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We recently launched analysis capabilities for GitHub Actions workflow files in public preview.

With the release of CodeQL 2.20.5, we are expanding the analysis capabilities to detect additional types of security risks associated with Actions workflow files and we have adjusted some of the existing queries.

The analysis coverage is improved with the addition of five new queries that identify additional types of security risks associated with Actions workflow files. The new queries are:

  • actions/envpath-injection/medium detects situations where user-controlled sources (like the text of a GitHub issue) are used to populate the PATH environment variable. This could allow an attacker to alter the execution of system commands.
  • actions/envvar-injection/medium detects situations where environment variables which are not properly sanitized can lead to the injection of additional unwanted variables, using new lines or {delimiters}.
  • actions/code-injection/medium– detects situation where user-controlled input can end up in contexts like run: or script:, leading to malicious code being executed and secrets being leaked.
  • actions/artifact-poisoning/medium detects situations where artifacts are not correctly extracted, stored and verified, which could result in a poisoned artifact being executed, leading to repository compromise.
  • actions/untrusted-checkout/medium detects situations where workflows triggered by events like pull_request_target or issue_comment can execute arbitrary code from untrusted sources, if followed by an explicit checkout.

Because of its lower precision and the large number of alerts it generates, the query actions/unpinned-tag has been moved to the security-extended query suite from the default query suite, and all existing alerts for this query will be automatically closed if the security-extended suite is not being used.

Three queries have been removed from the default and security-extended query suites because they do not produce relevant security alerts. Alerts generated by these queries will be closed automatically.

These changes are now available with the release of CodeQL 2.20.5. For a full list of changes, please refer to the complete changelog for version 2.20.5. Every new version of CodeQL is automatically deployed to users of GitHub code scanning on GitHub.com. The new functionality in CodeQL 2.20.5 will also be included in GitHub Enterprise Server (GHES) version 3.17. If you use an older version of GHES, you can manually upgrade your CodeQL version.

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Now it is easier to see how many of your historical CodeQL alerts received autofix suggestions and how many of those alerts were resolved across all the repositories in your organization.

Historical alerts are those found in your default and protected branches, indicating potential existing security issues in your code. You can stay informed about the progress of historical alert resolution and expediting this process as it is essential for accurately assessing your security risks.

Screenshot of total alerts fixed with an accepted autofix out of all with a suggested autofix.

The new “Alerts fixed with autofix suggestions” tile on the Security Overview provides you with the total number of fixed vulnerabilities compared to the total suggested autofixes for existing alerts. This will help you stay informed about the security trends in your organization.

Learn more about Copilot Autofix for CodeQL code scanning and security overview.

To leave feedback for Copilot Autofix for code scanning, join the discussion.

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Copilot Autofix helps you fix code scanning alerts and avoid introducing new security vulnerabilities by using large language models to suggest potential fixes.

We recently expanded the range of CodeQL security alerts where Copilot can suggest an autofix, covering a group that accounts for 29% of all CodeQL alerts. This expansion led to an 8% overall increase in alerts with an available autofix and a 270% increase in autofixes for this specific group of improved alerts. With more autofix suggestions, you can resolve security issues identified by CodeQL more easily—either by applying Copilot’s suggested fix directly or using it as a starting point for your own edits.

We made these improvements by analyzing our usage data to understand the most common types of alerts where Copilot was not suggesting fixes and then made a targeted effort to improve autofix for these alerts. Read more about the testing process that GitHub uses to identify the quality of autofix suggestions.

We continuously evaluate the performance of CodeQL and Copilot Autofix, so look for more improvements in the future.

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CodeQL is the static analysis engine behind GitHub code scanning, which finds and remediates security issues in your code. The CodeQL engine has become faster, covers 28 more security queries, supports more ecosystems, and can now scan GitHub Actions (public preview)—among various other bug fixes and small improvements.

All of these improvements were automatically rolled out to code scanning users in the past few months. For users of the CodeQL CLI, here are some highlights of the past few CodeQL releases:

  • CodeQL 2.20.46 February 2025
    • Analysis support for GitHub Actions workflow files is now in public preview, and therefore the use of the actions language (for analysis of GitHub Actions workflows) no longer requires the CODEQL_ENABLE_EXPERIMENTAL_FEATURES environment variable to be set.
    • All experimental queries for C#, Java, and Kotlin have been migrated to the default query suite in the CodeQL community packs that are managed by GitHub Security Lab.
  • CodeQL 2.20.324 January 2025
    • Resolves a security vulnerability where CodeQL databases or logs produced by the CodeQL CLI may contain the environment variables from the time of database creation. This includes any secrets stored in an environment variables. For more information, see the CodeQL CLI security advisory.
  • CodeQL 2.20.222 January 2025
    • All data flow queries have been standardized on a single data flow library, which may result in differences for JavaScript and TypeScript analysis.
    • CodeQL databases now take 2-3x less space on disk, which makes them faster to transfer and read/manipulate. This is thanks to a new compressed database format.
  • CodeQL 2.20.19 January 2025
    • CodeQL is now easier to set up and roll out: automatic build command detection with automatic dependency installation for C/C++ is now supported on Ubuntu 24.04.
    • A new Server Side Template Injection query for Python has been released, thanks to a community contribution.
    • Swift 6.0.2 is now supported.
  • CodeQL 2.19.42 December 2024
  • CodeQL 2.19.37 November 2024
    • Analysis for .NET 8 and JDK 17 has been improved.
    • The CodeQL Bundle is now available as an artifact that is compressed using Zstandard. This artifact is smaller and faster to decompress than the original, gzip-compressed bundle. The CodeQL bundle is a tar archive containing tools, scripts, and various CodeQL-specific files.
  • CodeQL 2.19.221 October 2024
    • Analysis of Python apps now has significantly faster extraction and analysis times.
  • CodeQL 2.19.14 October 2024
    • Java 23 is now supported.
    • A new command, codeql resolve packs, shows each step in the pack search process, including what packs were found in each step.

Detailed changelogs for every CodeQL release are available in the CodeQL documentation, and new CodeQL releases occur roughly every two weeks.

For GitHub Enterprise Server customers: All new functionality from CodeQL releases 2.19.0 through 2.20.3 will be included in GHES 3.16 and the latest patch versions of 3.12-3.15. Functionality from 2.20.3 and later 2.20.X versions will be included in 3.17. If you use an older version of GHES, you can manually upgrade your CodeQL version.

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Copilot Autofix suggestions for code scanning alerts can now be edited and validated using Copilot Workspace for pull requests.

Copilot Workspace for Copilot Autofix for code scanning

With this, GitHub Advanced Security users can:

  • Review and integrate Copilot Autofix suggestions within the context of the pull request, benefiting from an improved diff-viewing experience.
  • Refine and address code scanning alerts directly within the pull request, utilizing an enhanced code editing experience.
  • Build, test, and run proposed changes in the pull request without impacting your personal build and test environment.

All GitHub Advanced Security users can use this feature in private repositories on GitHub.com. A Copilot license is not required.

To learn more about code scanning alerts and Copilot Autofix, see About Copilot Autofix for CodeQL code scanning. If you have feedback regarding Copilot Autofix for code scanning, please join the discussion here.

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We’re releasing various improvements to security campaigns to help security teams and developers collaborate more effectively to resolve security debt with the help of Copilot Autofix.

Security campaigns with Copilot Autofix were released in public preview at GitHub Universe.

Available as part of GitHub Advanced Security, security campaigns help you rapidly reduce your backlog of application security debt. With security campaigns, you can make sure your developers focus on the most important security alerts across your portfolio. Copilot Autofix also automatically generates contextual explanations and suggests fixes for alerts in a campaign.

Today we are announcing multiple improvements based on the customer feedback we have received during the security campaigns public preview:

  • The repository limit for security campaigns has increased from 100 to 1000, making it easier to create campaigns from more of your critical repositories.
  • Multiple users or teams can now be specified as campaign managers, giving application security teams greater flexibility in assigning responsibility for monitoring campaign progress and collaborating with developers on fixing alerts.
  • We’ve added a new contact link field in the security campaigns user interface to facilitate better communication between security teams and developers during campaigns.
  • Email notifications are now consolidated when security campaigns are created or closed. Developers watching multiple repositories included in the same campaign will receive a single email including details of all relevant repositories rather than one email per repository.
  • Security campaigns are available for users of GitHub Advanced Security on GitHub Enterprise Cloud.

For more information about security campaigns, see About security campaigns in the GitHub documentation. If you have any feedback on security campaigns, join the discussion in the GitHub Community.

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GitHub Code Scanning powered by CodeQL now supports dependency caching for Java, Go, and C# projects. This feature ensures that scans can deliver meaningful results even if registries are temporarily unavailable, while also reducing overall scanning time after the cache is established.

Dependency Caching Availability:

  • Default Setup: For repositories using GitHub-hosted runners, dependency caching is automatically enabled for both public and private repositories during scans.
  • Advanced Setup: Users with custom configurations can manually enable dependency caching as needed.

This is now available on github.com.

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On December 13, 2023, we released CodeQL Action v3, which runs on the Node.js 20 runtime. In January 2024, we announced that CodeQL Action v2 would be retired at the same time as GitHub Enterprise Server (GHES) 3.11. This retirement period has elapsed and CodeQL Action v2 is now discontinued. It will no longer be updated or supported, and while we will not be deleting it except in the case of a security vulnerability, workflows using it may eventually break. New CodeQL analysis capabilities will only be available to users of v3.

For more information about this retirement, please see the original retirement announcement from January 2024.

How does this affect me?

Default setup

Users of code scanning default setup do not need to take any action in order to automatically move to CodeQL Action v3.

Advanced setup

Users of code scanning advanced setup need to change their workflow files in order to start using CodeQL Action v3.

Users of GitHub.com and GitHub Enterprise Server 3.12 (and newer)

All users of GitHub code scanning (which by default uses the CodeQL analysis engine) on GitHub Actions on the following platforms should update their workflow files:

  • GitHub.com (including open source repositories, users of GitHub Teams and GitHub Enterprise Cloud)
  • GitHub Enterprise Server (GHES) 3.12 (and newer)

Users of the above-mentioned platforms should update their CodeQL workflow file(s) to refer to the new v3 version of the CodeQL Action. Note that the upcoming release of GitHub Enterprise Server 3.12 will ship with v3 of the CodeQL Action included.

Users of GitHub Enterprise Server 3.11 (and older)

GitHub Enterprise Server 3.11 (and older) is now retired. For more information on using the CodeQL Action on a retired GitHub Enterprise Server version, refer to the relevant sections of the CodeQL Action v2 retirement announcement.

Exactly what do I need to change?

To upgrade to CodeQL Action v3, open your CodeQL workflow file(s) in the .github directory of your repository and look for references to:

  • github/codeql-action/init@v2
  • github/codeql-action/autobuild@v2
  • github/codeql-action/analyze@v2
  • github/codeql-action/upload-sarif@v2

These entries need to be replaced with their v3 equivalents:

  • github/codeql-action/init@v3
  • github/codeql-action/autobuild@v3
  • github/codeql-action/analyze@v3
  • github/codeql-action/upload-sarif@v3

Can I use Dependabot to help me with this upgrade?

Yes, you can! For more details on how to configure Dependabot to automatically upgrade your Actions dependencies, please see this page.

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CodeQL build-mode: none scans can now access private dependencies stored in private registries (e.g. Artifactory) for Java and C# projects. This makes your scans more comprehensive, ensuring you receive all important alerts regardless of where your dependencies are stored.

Previously, build-mode: none code scans with the default setup were unable to fetch code for dependent packages stored in private registries, which could result in incomplete analysis. Now, organization administrators can configure access credentials for private registries at the organization level. This enhancement allows CodeQL scans in child repositories to retrieve all necessary dependencies, enabling comprehensive code analysis when using the code scanning default setup.

This feature is currently in public preview for GitHub Advanced Security customers.

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You can now enable code scanning in your GitHub Actions workflow files. By opting-in to this feature, you can enhance the security of repositories using GitHub Actions.

Actions analysis support includes a set of CodeQL queries developed by the GitHub Security Lab to capture common misconfigurations of workflow files that can lead to security vulnerabilities. You can now easily run these queries as part of Code Scanning’s default or advanced setup and use Copilot Autofix to get remediation suggestions on your findings.

You can opt-in to the public preview by selecting the “GitHub Actions” language via code scanning default setup, or by adding the actions language to your existing advanced setup. New repositories onboarding to default setup after today will start analyzing Actions workflows right away. Existing repositories will not be automatically opted-in as part of the public preview.

Learn more about configuring default setup for code scanning, securing your use of Actions, and vulnerabilities identified with CodeQL.

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New REST API endpoints for code scanning allow you to request the generation of Copilot Autofix for code scanning alerts. These endpoints also provide the Autofix generation status, along with metadata and AI-generated descriptions for the fixes, and enable you to apply Autofix to a branch. This functionality can be particularly useful for addressing security vulnerabilities programmatically and for tracking the status of alerts with Copilot Autofixes in your system.

To generate Copilot Autofix, call the POST /repos/{owner}/{repo}/code-scanning/alerts/{number}/autofix endpoint.
Additionally, you can retrieve the Autofix and commit it by using the GET /repos/{owner}/{repo}/code-scanning/alerts/{number}/autofix endpoint followed by POST /repos/{owner}/{repo}/code-scanning/alerts/{number}/autofix/commits.

For more information, see: About Copilot Autofix for CodeQL code scanning. If you have feedback for Copilot Autofix for code scanning, please join the discussion here.

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The metrics overview for CodeQL pull request alerts now includes enhanced tracking and reporting mechanisms, resulting in greater accuracy and more CodeQL pull request alerts and Copilot Autofixes displayed on the dashboard.

These changes retroactively affect the dashboard numbers, allowing you to effectively monitor your organization’s security posture.

With these insights, you can proactively identify and address security risks before they reach your default branch. The metrics overview for CodeQL pull request alerts helps you understand how effectively CodeQL prevents vulnerabilities in your organization. You can use these metrics to easily identify the repositories where action is needed to mitigate security risks.

The change is now generally available on GitHub Enterprise Cloud.

Learn more about security overview and code scanning.

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The enterprise and organization-level audit log events are now created when a code scanning alert is created, fixed, dismissed, reopened, or appeared in a new branch:

  • code_scanning.alert_created – a code scanning alert was seen for the first time;
  • code_scanning.alert_appeared_in_branch – an existing code scanning alert appeared in a branch;
  • code_scanning.alert_closed_became_fixed – a code scanning alert was fixed;
  • code_scanning.alert_reappeared – a code scanning alert that was previously fixed reappeared;
  • code_scanning.alert_closed_by_user – a code scanning alert was manually dismissed;
  • code_scanning.alert_reopened_by_user – a code scanning alert that was previously dismissed was reopened.

The new functionality, which will be included in GHES 3.17, provides more insight into the history of a code scanning alert for easier troubleshooting and analysis.

For more information:

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When configuring CodeQL security analysis using code scanning’s default setup, you can now specify whether to run the analysis on a standard GitHub-hosted runner, a larger GitHub-hosted runner, or a self-hosted runner. Previously, support for larger GitHub-hosted and self-hosted runners was limited to those with the code-scanning custom label. Now, you can specify any custom label, ensuring the analysis runs on the desired machine(s).

For example, using a custom label you are able to assign more powerful runners to critical repositories for faster analyses, better spread the workload over GitHub-hosted and self-hosted runners, or run the analysis on a particular platform (like macOS).

The new setting is available today on GitHub.com, and can be configured both at the repository level and within code security configurations for deployments at scale. This new setting will also be included in GitHub Enterprise Server (GHES) version 3.16.

Learn more about configuring default setup for code scanning.

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