code-scanning

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When using Copilot Autofix for historical alerts, you can now choose the branch to which you want to commit an autofix. You can also decide whether to then open a pull request, check out the branch locally, or open it in GitHub Desktop.

Copilot Autofix provides automatic fix suggestions for code scanning alerts in your codebase.

Example of committing Copilot Autofix to branch

This update integrates Autofix more closely within the developer workflow, so you can quickly iterate on fix suggestions and collaborate on those with your team.

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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In the coming months, the current interface for managing code security settings for an enterprise will be deprecated and replaced with new and improved code security configurations that will provide you a more consistent and scalable way to manage security settings across repositories within your enterprise.

The current REST API endpoint to enable or disable a security feature for an enterprise is now deprecated. It will continue to work for an additional year in the current version of the REST API before being removed in September of 2025, but note that it may conflict with settings assigned in code security configurations if the configuration is unenforced, potentially resulting in a security configuration being unintentionally removed from a repository. To change the security settings for repositories at the enterprise level, you can use the current enterprise-level security settings UI or the upcoming code security configurations API.

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CodeQL version 2.19.0 has been released and has now been rolled out to code scanning users on GitHub.com. CodeQL is the static analysis engine that powers GitHub code scanning.

Important changes by version include:

  • CodeQL 2.18.2
    • Support for scanning Java codebases without needing a build is generally available.
    • The Python py/cookie-injection query, which finds instances of cookies being constructed from user input, is now part of the main query pack.
    • One new query for Ruby rb/weak-sensitive-data-hashing, to detect cases where sensitive data is hashed using a weak cryptographic hashing algorithm.
  • CodeQL 2.18.3
    • New C# models for local sources from System.IO.Path.GetTempPath and System.Environment.GetFolderPath.
  • CodeQL 2.18.4
    • Support for scanning C# codebases without needing a build is generally available.
    • Support for Go 1.23.
  • CodeQL 2.19.0
    • Support for TypeScript 5.6.
    • One new query for JavaScript js/actions/actions-artifact-leak to detect GitHub Actions artifacts that may leak the GITHUB_TOKEN token.
    • A 13.7% evaluator speed improvement over CodeQL 2.17.0 release.

For a full list of changes, please refer to the complete changelog for versions 2.18.2, 2.18.3, 2.18.4 and 2.19.0.

All new functionality from 2.18.Z releases will be included in GHES 3.15, while functionality from 2.19.0 will be included in GHES 3.16. If you use GHES 3.14 or older, you can upgrade your CodeQL version.

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Now, you can view Prevention metrics alongside Detection and Remediation metrics and in an enhanced security overview dashboard. This update is available at both the organization and enterprise levels.

New prevention tab on the security overview dashboard

New to the dashboard, the Prevention insights tab highlights CodeQL pull requests alerts and will soon include secret scanning push protection insights. It’s designed to help you shift from merely responding to vulnerabilities to actively preventing them, the ultimate goal in application security. With this dashboard, you and your team can proactively keep vulnerabilities at bay, successfully blocking threats before they ever reach production.

Deep dive into the CodeQL pull request alerts

For a deeper analysis, the new CodeQL pull request alerts report is also available at both the organization and enterprise levels. This report allows you to:

  • Track historical metrics for CodeQL pull request alerts
  • Monitor code as it progresses from feature branches to the default branch
  • Analyze metrics by CodeQL rule, autofix status, and repository

The enhanced dashboard is now generally available on GitHub Enterprise Cloud and will be available in GitHub Enterprise Server 3.16.

Learn more about pull request alerts and join the discussion within the GitHub Community

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Now you can remediate existing security issues in your public repositories faster with Copilot Autofix for CodeQL alerts. Following our general availability release for all Advanced Security customers, Copilot Autofix for CodeQL alerts is now generally available (GA) for all public repositories, for free.

Powered by GitHub Copilot, this feature provides automatic fixes for vulnerabilities found by CodeQL, both on pull requests and for historical alerts that already exist in a codebase.

Importantly, you stay in full control of your codebase: Copilot Autofix will try and suggest fixes for CodeQL alerts in pull requests, but it’s ultimately up to you to decide whether you wish to accept Copilot’s suggestion wholly, partially, or not at all. The same applies to historical alerts in a codebase: you can request an autofix from Copilot, then review it, and decide whether you want to open a PR with the fix suggestion or commit straight to the affected branch (or neither).

Example of Copilot Autofix generation on the alert page

Copilot Autofix is available for all public repositories that use code scanning CodeQL, and is enabled by default for alerts on PRs. It does not generate additional notifications. If you would like to enable Copilot Autofix on your organization’s private repositories, please have a look at this blog post where we announce Autofix for GitHub Advanced Security.

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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New Export CSV button highlighted on the CodeQL pull request alerts report

You can now export data from the CodeQL pull request alerts report in CSV format, enabling you to analyze prevention and autofix metrics offline or archive the data for future use. This functionality is available at both the organization and enterprise levels. Exports will respect all filters applied, allowing you to focus on the specific data most relevant to your needs. You can download all data where you have an appropriate level of access.

Learn more about tracking metrics on CodeQL pull request alerts and join the discussion within the GitHub Community.

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You can now use Copilot Chat in GitHub.com to search across GitHub to find and learn more about GitHub Advanced Security Alerts from code scanning, secret scanning, and Dependabot. This change helps you to better understand and seamlessly fix security alerts in your pull request. ✨

Try it yourself by asking questions like:
– How would I fix this alert?
– How many alerts do I have on this PR?
– What class is this code scanning alert referencing?
– What library is affected by this Dependabot alert?
– What security alerts do I have in this repository?

Learn more about asking questions in Copilot Chat on GitHub.com or about GitHub Advanced Security.

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CodeQL code scanning can now analyze Java and C# code without having to observe a build. This makes it easier to roll out the security analysis on large numbers of repositories, especially when enabling and managing repositories with GHAS security configurations.

CodeQL is the analysis engine that powers GitHub code scanning. When analyzing source code, it is important that the analysis engine has detailed knowledge of all aspects of the codebase. Now, the analysis engine no longer depends on observing the build process for Java and C# code, resulting in higher setup success and adoption rates for CodeQL code scanning (Java and C#).

During the testing of this feature, we validated that the analysis results were as accurate as the previous methodology. This feature was previously in public beta earlier this year (Java, C#), when it became the new default analysis mode for new users of CodeQL code scanning for these languages. Some customers experienced time significant savings as some tasks that previously took weeks now are achievable in minutes.

CodeQL’s new zero-configuration analysis mechanisms for both Java and C# are available on GitHub.com. If you are setting up CodeQL code scanning for these repositories, you will benefit from this analysis mechanism by default. If you set up CodeQL code scanning for Java or C# before their respective public beta releases of this feature, your analysis will remain unchanged (but can be migrated by disabling the current configuration and re-enabling code scanning using default setup). This new functionality will also be released to our GitHub Enterprise Server (GHES) customers starting with version 3.14 for Java and 3.15 for C#.

Repositories that use code scanning advanced setup will continue to use whichever analysis mechanism is specified in the Actions workflow file. The template for new analysis configurations now uses the new analysis mechanism by specifying `build-mode: none`. The old analysis mechanisms remain available. Users of the CodeQL CLI can find more documentation here.

Learn more about GitHub code scanning. If you have any feedback about these new analysis mechanisms for Java and C#, please join the discussion here.

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You can now track prevention metrics for CodeQL pull request alerts with the new CodeQL pull request alerts report—available at both the organization and enterprise level. These insights empower you to proactively identify and mitigate security risks before they reach your default branch.

Enterprise-level CodeQL pull request alerts report

With this report, you can historically track metrics for CodeQL pull request alerts as code moves from feature branches to the default branch. Gain insights into:

  • Unresolved and merged alerts: Understand what security vulnerabilities made it to the default branch.
  • Fixes (autofix and manual): Track which alerts were addressed before merging.
  • Dismissed alerts: See which alerts were deemed false positive or risk accepted.

Additionally, analyze metrics by CodeQL rule, autofix status, and repository.

Historical data is available starting from May 1, 2024.

To access these reports, click your profile photo in the top-right corner of GitHub.com and select the organization or enterprise you want to view. For organizations, go to the Security tab and find CodeQL pull request alerts in the sidebar. For enterprises, click Code Security in the sidebar, then select CodeQL pull request alerts.

These reports are now generally available on GitHub Enterprise Cloud and will be available in GitHub Enterprise Server 3.15.

Learn more about security overview and join the discussion within the GitHub Community.

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Today, we’ve announced the general availability of Copilot Autofix for CodeQL alerts in GitHub code scanning! Powered by GitHub Copilot, this feature brings automatic fixes for vulnerabilities found by CodeQL into the developer workflow.

Through a deep integration in GitHub pull requests, autofixes help developers to fix vulnerabilities quickly and early in the development process, thereby preventing new vulnerabilities from entering your codebase. Data from our beta programme shows that vulnerabilities with a fix suggestion are fixed 3x faster across all vulnerability types, and even faster for complicated vulnerability types like cross-site scripting (7x faster) and SQL injection (12x faster). For security debt that already exists in your codebases, Copilot Autofix can help you with on-demand autofixes for historical alerts. Copilot Autofix for CodeQL code scanning was previously called “code scanning autofix”, and is now generally available for all GitHub Advanced Security customers on GitHub.com.

As developers start using autofixes, security teams can see an overview of how their organisation adopts autofixes generated by Copilot on their security overview dashboard. This includes detailed information about remediation rates.

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.

Example of Copilot Autofix operating on a CodeQL alert in a pull request

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New Export CSV button highlighted on the overview dashboard on the Security tab at the organization level

Enhance your security workflows by exporting security alert data for offline analysis, reporting, and archival purposes with our new CSV export functionality, available at the organization level. CSV exports will respect all filters you’ve applied to the page, allowing you to generate multiple exports focusing on different datasets. You can download all data where you have an appropriate level of access.

Learn more about the security overview dashboard and send us your feedback.

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CodeQL is the static analysis engine that powers GitHub code scanning. CodeQL version 2.18.1 has been released and has now been rolled out to code scanning users on GitHub.com.

Important changes by version include:

For a full list of changes, please refer to the complete changelog for versions 2.17.6, 2.18.0, and 2.18.1. All new functionality will be included in GHES 3.15. Users of GHES 3.14 or older can upgrade their CodeQL version.

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Code security configurations were made generally available on July 10th, 2024. This experience replaces our old settings experience and its API.

If you are currently using the REST API endpoint to enable or disable a security feature for an organization, this endpoint is now considered deprecated.

It will continue to work for an additional year in the current version of the REST API before being removed in July of 2025. However, users should note this will conflict with the settings assigned in code security configurations if the configuration is unenforced. This may result in a code security configuration being unintentionally removed from a repository.

The endpoint will be removed entirely in the next version of the REST API.

To change the security settings for repositories, you can use the code security configurations UI, the configurations API, or the unaffected enterprise-level security settings.

Send us your feedback!.

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Today, we’re excited to announce the general availability of our new organization and enterprise-level security overview dashboards, alongside enhanced secret scanning metrics and the enablement trends reports. These features are designed to provide comprehensive insights, improved prioritization, and advanced filtering options to streamline your security improvements.

Code security insights

Organization-level overview dashboard on the security tab

Our new security overview dashboard, available at both the organization and enterprise levels, integrates security into the core of the development lifecycle. This empowers you to proactively identify and address vulnerabilities. Key features include:

  • Track security improvements: Monitor trends over time by age, severity, and security tool, simplifying prioritization with top 10 lists focused on repositories and advisories.
  • Autofix impact: Understand how autofix, powered by GitHub Copilot, is influencing your enterprise’s security remediation efforts.
  • Advanced filtering: Customize data focus with filters by attributes such as team, repository metadata (i.e., custom repository properties), and security tool-specific filters:
    • Dependabot: Filter by ecosystem, package, and dependency scope.
    • CodeQL/Third-Party: Filter by specific rules.
    • Secret Scanning: Filter by secret type, provider, push protection status, and validity.

Organization-level enablement trends report

Monitor the enablement trends of all security tools with detailed insights into the activation status of Dependabot alerts, Dependabot security updates, code scanning, secret scanning alerts, and secret scanning push protection, giving you at-a-glance oversight of your security coverage.

Push protection insights for secret scanning

Organization-level secret scanning metrics page

Gain insights into how push protection is functioning throughout your enterprise. Monitor the number of pushes containing secrets that have been successfully blocked, as well as instances where push protection was bypassed. Detailed insights by secret type, repository, and reasons for bypassing are also available.

To access these features, navigate to your profile photo in the top-right corner of GitHub.com and select the organization or enterprise you wish to view. For organizations, click on the Security tab. For enterprises, click Code Security in the enterprise account sidebar.

These features are generally available on GitHub.com today and will be generally available in GitHub Enterprise Server 3.14.

Learn more about the security overview dashboard, the secret scanning metrics report and the enablement trends report

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GitHub Enterprise Cloud customers can now see code security configurations data in audit log events.

Code security configurations simplify the rollout of GitHub security products at scale by defining collections of security settings and helping you apply those settings to groups of repositories. Configurations help you change the settings for important features like code scanning, secret scanning, and Dependabot.

With the addition of configurations data in the audit log, organization and enterprise owners have easy visibility into why the settings on certain repositories may have changed.

Audit log events now include:
– Name of the configuration applied to a repository
– When the configuration application fails
– When a configuration is removed from a repository
– When configurations are created, updated, or deleted
– When configurations become enforced
– When the default configuration for new repositories changes

Code security configurations are now available in public beta on GitHub.com and will be available in GitHub Enterprise Server 3.15. You can learn more about code security configurations or send us your feedback.

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