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Code scanning autofix is now available in public beta for all GitHub Advanced Security customers. Powered by GitHub Copilot, code scanning suggests fixes for Javascript, Typescript, Java, and Python alerts found by CodeQL.
This feature empowers developers to reduce the time and effort spent remediating alerts found in pull requests, and helps prevent new vulnerabilities from being introduced into your code base.

Autofix

The feature is automatically enabled on all private repositories for GitHub Advanced Security customers.
When code scanning analysis is performed on pull requests, autofixes will be generated for supported alerts. They include a natural language explanation of the suggested fix, together with a preview of the code suggestion that the developer can accept, edit, or dismiss. In addition to changes to the current file, these code suggestions can include changes to multiple files. Where needed, autofix may also add or modify dependencies.

You can see the total number of autofix suggestions provided for CodeQL alerts in open and closed pull requests in security overview:

Autofixes on the overview dashboard

You can configure code scanning autofix for a repository or organisation. You can also use Policies for Code security and analysis to allow autofix for CodeQL code scanning for an enterprise.

Enterprise settings

Code scanning autofix supports, on average, 90% of CodeQL Javascript, Typescript, Java, and Python alerts from queries in the Default code scanning suite. The fix generation for any given alert also depends on the context and location of the alert. In some cases, code scanning won’t display a fix suggestion for an alert if the suggested code change fails syntax tests or safety filtering.

This change is now available to all GitHub Advanced Security customers on GitHub.com. For more information, see About autofix for CodeQL code scanning.

Provide feedback for code scanning autofix here.

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You can now monitor enablement trends for all security products within your GitHub organization. This functionality is designed to give you a detailed overview of how your organization is implementing security product coverage.

new tool adoption report

Explore enablement trends for historical insights into the activation status of GitHub security features:
* Dependabot alerts
* Dependabot security updates
* Code scanning
* Secret scanning alerts
* Secret scanning push protection

Historical data is available from January 1, 2024, with the exception of Dependabot security updates data, which is available from January 17, 2024.

To access the enablement trends page, visit security overview at the organization level. You can find security overview by clicking on the “Security” tab.

This feature is now available as a public beta on GitHub Enterprise Cloud and will be available in GitHub Enterprise Server 3.13.

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

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Previously, if you specified your private registry configuration in the dependabot.yml file and also had a configuration block for that ecosystem using the target-branch key, Dependabot security updates wouldn’t utilize the private registry information as expected. Starting today, Dependabot now uses private registry configurations specified in the dependabot.yml file as expected, even if there is a configuration with target-branch. This ensures that security updates are applied correctly, regardless of your repository’s configuration settings. Note that security updates still does not support target-branch configuration.

Learn more about configuring private registries for Dependabot in the Dependabot documentation.

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Previously, if Dependabot encountered 30 consecutive failures, it would stop running scheduled jobs until manual intervention via updating the dependency graph or manifest file. Dependabot will now pause scheduled jobs after 15 failures. This will give an earlier indication of potential issues while still ensuring that critical security updates will continue to be applied without interruption.

Read more in the Dependabot Docs. 

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CodeQL is the static analysis engine that powers GitHub code scanning. CodeQL version 2.16.4 has been released and has now been rolled out to code scanning users on GitHub.com.

CodeQL code scanning now supports automatic fix suggestions for Java alerts on pull requests, powered by Copilot. This is automatically enabled for all current autofix preview participants. You can sign up for the preview here and use our public discussion for questions and feedback.

The number of generated autofixes is now also visible in a dedicated security overview tile:

security overview showing a counter of fix suggestions

Furthermore, this release

For a full list of changes, please refer to the complete changelog for version 2.16.4. All new functionality will also be included in GHES 3.13. Users of GHES 3.12 or older can upgrade their CodeQL version.

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Secret scanning now helps you more easily define custom patterns with GitHub Copilot.

As of today, you can leverage AI to generate custom patterns without expert knowledge of regular expressions.

Generate a secret scanning custom pattern with AI

What’s changing?

You can create your own custom detectors for secret scanning by using custom patterns. Formatted as regular expressions, these custom patterns can be challenging to write. Secret scanning now supports a pattern generator backed by GitHub Copilot in order to generate regular expressions that match your input.

How do I use the regular expression generator?

When defining a custom pattern, you can select “generate with AI” in order to launch the regular expression generator.

The model returns up to three regular expressions for you to review. You can click on the regular expression to get an AI-generated plain language description of the regular expression. You should still review this input and carefully validate performance of results by performing a dry run across your organization or repository.

Who can use the regular expression generator?

Anyone able to define custom patterns is able to use the regular expression generator. This feature is shipping to public beta today for all GitHub Enterprise Cloud customers with GitHub Advanced Security.

Learn more about the regular expression generator or how to define your own custom patterns.

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Dependabot security updates help you keep your dependencies secure by opening pull requests when a Dependabot alert is raised. With today’s release, you can now use flexible grouping options in dependabot.yml to control how Dependabot structures its security pull requests to make them more mergeable for you based on your context. Whether you’d like to simply update as many dependencies at once as possible (patterns: '*') or minimize the risk of breaking changes (dependency-type: development or update-types: "patch"), there are grouping options for you.

By specifying applies-to: security-updates in your group rule configuration, you can specify how you would like Dependabot to group your security updates. If you would like Dependabot to group together all possible updates for an ecosystem, you can instead use the UI located in your repository settings to do so. To learn more about this, check out our documentation here.

The available grouping options are:

  • patterns, which will match based on package names
  • dependency-type, which will group based on development or production dependencies, for ecosystems where this is supported, and
  • update-types, which will group based on SemVer level update

Learn more about grouping configuration options here.

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CodeQL is the static analysis engine that powers GitHub code scanning. CodeQL version 2.16.3 has been released and has now been rolled out to code scanning users on GitHub.com.

Important changes in this release include:

  • CodeQL code scanning now supports AI-powered automatic fix suggestions for Python alerts on pull requests. This is automatically enabled for all current autofix preview participants.
  • A new option has been added to the Python extractor: python_executable_name. This allows you to select a non-default Python executable installed on the system running the scan (e.g. py.exe on Windows machines).
  • A fix for CVE-2024-25129, a low-severity data exfiltration vulnerability that could be triggered by processing untrusted databases or CodeQL packs.
  • Two new queries:
  • The sinks of queries java/path-injection and java/path-injection-local have been reworked to reduce the number of false positives.

For a full list of changes, please refer to the complete changelog for version 2.16.3. All new functionality will also be included in GHES 3.13. Users of GHES 3.12 or older can upgrade their CodeQL version.

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CodeQL 2.16.2 is now available to users of GitHub code scanning on github.com, and all new functionality will also be included in GHES 3.13. Users of GHES 3.12 or older can upgrade their CodeQL version.

Important changes in this release include:

We added two new Java / Android queries (java/android/sensitive-text and java/android/sensitive-notification) to detect sensitive data exposure via text fields and notifications.

We have improved the precision of several C/C++ queries.

We now recognize collection expressions introduced in C# 12 (e.g. [1, y, 4, .. x]).

For a full list of changes, please refer to the complete changelog for version 2.16.2

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Secret scanning is extending validity check support to Mailgun (mailgun_api_key) and Mailchimp (mailchimp_api_key) API keys.

Validity checks indicate if the leaked credentials are active and could still be exploited. If you’ve previously enabled validation checks for a given repository, GitHub will now automatically verify validity for alerts on supported token types.

Validity checks are available for repositories with GitHub Advanced Security on Enterprise Cloud. You can enable the feature at both organization and repository levels from the “Code security and analysis” settings page by checking the option to “automatically verify if a secret is valid by sending to the relevant partner.”

Learn more about secret scanning or our supported patterns for validity checks.

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If you use private hosted pub repositories or registries to manage your Dart dependencies, Dependabot can now automatically update those dependencies. By adding the details of the private repository or registry to dependabot.yml, Dependabot will be able to access and update these dependencies.

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The secret_scanning_alert webhook is sent for activity related to secret scanning alerts. Secret scanning webhooks now support validity checks, so you can keep track of changes to validity status.

Changes to the secret_scanning_alert webhook:

  • A new validity property that is either active, inactive, or unknown depending on the most recent validity check.
  • A new action type, validated, which is triggered when a secret’s validity status changes.

Note: you must enable validity checks at the repository or organization level in order to opt in to the feature. This can be done from your secret scanning settings on the Code security and analysis settings page by selecting the option to “automatically verify if a secret is valid by sending it to the relevant partner.”

Learn more about which secret types are supported or the secret scanning webhook.

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Secret scanning is extending validity check support to several additional token types.

Validity checks indicate if the leaked credentials are active and could still be exploited. If you’ve previously enabled validation checks for a given repository, GitHub will now automatically verify validity for alerts on supported token types. In addition to token types announced in our previous changelogs, you will now see validity checks for the following token types:

Provider Token
Dropbox dropbox_short_lived_access_token
Notion notion_integration_token
OpenAI openai_api_key
OpenAI openai_api_key_v2
SendGrid sendgrid_api_key
Stripe stripe_api_key
Stripe stripe_test_secret_key
Telegram telegram_bot_token

Validity checks are available for repositories with GitHub Advanced Security on Enterprise Cloud. You can enable the feature at both organization and repository levels from the “Code security and analysis” settings page by checking the option to “automatically verify if a secret is valid by sending to the relevant partner.”

Learn more about secret scanning or our supported patterns for validity checks.

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Code scanning can now be enabled on repositories even if they don’t contain any code written in the languages currently supported by CodeQL. Default setup will automatically trigger the first scan when a supported language is detected on the default branch. This means users can now enable code scanning using default setup, for example on empty repositories, and have confidence that they will be automatically protected in the future when the languages in the repository change to include supported languages.

This also takes effect from the organization level so you can bulk-enable code scanning on repositories without CodeQL supported languages.

Enabled on repo without supported languages

This change is now on GitHub.com and will be available in GitHub Enterprise Server 3.13. For more information, see “About code scanning default setup.”

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CodeQL 2.16.1 is now available to users of GitHub code scanning on github.com, and all new functionality will also be included in GHES 3.13. Users of GHES 3.12 or older can upgrade their CodeQL version.

Important changes in this release include:

Swift 5.9.2 is now supported.

We added a new query for Swift, swift/weak-password-hashing, to detect the use of inappropriate hashing algorithms for password hashing and a new query for Java, java/exec-tainted-environment, to detect the injection of environment variables names or values from remote input.

We improved the tracking of flows from handler methods of a PageModel class to the corresponding Razor Page (.cshtml) file, which may result in additional alerts from some queries.

JavaScript now supports doT templates and Go added support for AWS Lambda functions and fasthttp framework.

In the previous version, 2.16.0, we announced that we will update the way we measure the number of scanned files in the Code Scanning UI. This change is now live for JavaScript/TypeScript, Python, Ruby, Swift, and C#.

For a full list of changes, please refer to the complete changelog for version 2.16.1.

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If you use devcontainer.json files to define your development containers, you will now be able to use Dependabot version updates to keep your Features up-to-date. Once configured in dependabot.yml, Dependabot will open pull requests on a specified schedule to update the listed Features to latest. This ensures Features are pinned to the latest major version in the associated devcontainer.json file. If a dev container has a lockfile, that file will also be updated. Dependabot security updates for dev containers are not supported at this time.

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CodeQL 2.16.0 is now available to users of GitHub code scanning on github.com, and all new functionality will also be included in GHES 3.13. Users of GHES 3.12 or older can upgrade their CodeQL version.

Important changes in this release include:

In July 2023, we disabled automatic dependency installation for new CodeQL code scanning setups when analyzing Python code. With the release of CodeQL 2.16.0, we have disabled dependency installation for all existing configurations as well. This change should lead to a decrease in analysis time for projects that were installing dependencies during analysis, without any significant impact on results. A fallback environment variable flag is available to ease the transition, but will be removed in CodeQL 2.17.0. No action is required for Default setup users. Advanced setup users that had previously set the setup-python-dependencies option in their CodeQL code scanning workflows are encouraged to remove it, as it no longer has any effect.

We fixed a bug that could cause CodeQL to consume more memory than configured when using the --ram flag. If you have used this flag to manually override the memory allocation limit for CodeQL, you may be able to increase it slightly to more closely match the system’s available memory. No action is required for users of the CodeQL Action (on github.com or in GHES) who are not using this flag, as memory limits are calculated automatically.

We added 2 new C/C++ queries that detect pointer lifetime issues, and identify instances where the return value of scanf is not checked correctly. We added a new Java query that detects uses of weakly random values, which an attacker may be able to predict. Furthermore, we improved the precision and fixed potential false-positives for several other queries.

The measure of scanning Go files in the code scanning UI now includes partially extracted files, as this more accurately reflects the source of extracted information even when parts of a file could not be analyzed. We will gradually roll this change out for all supported languages in the near future.

We fixed a bug that led to errors in build commands for Swift analyses on macOS that included the codesign tool.

For a full list of changes, please refer to the complete changelog for version 2.16.0 and 2.15.5.

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On December 13, 2023, we released CodeQL Action v3, which runs on the Node.js 20 runtime. CodeQL Action v2 will be deprecated at the same time as GHES 3.11, which is currently scheduled for December 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

While GHES 3.11 does support Node 20 Actions, it does not ship with CodeQL Action v3. Users who want to migrate to v3 on GHES 3.11 should request that their system administrator enables GitHub Connect to download v3 onto GHES before updating their workflow files.

Users of GitHub Enterprise Server 3.10 (and older)

GHES 3.10 (and earlier) does not support running Actions using the Node 20 runtime and is therefore unable to run CodeQL Action v3. Please upgrade to a newer version of GitHub Enterprise Server prior to changing your CodeQL Action workflow files.

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.

What happens in December 2024?

In December 2024, CodeQL Action v2 will be officially deprecated (at the same time as the GHES 3.11 deprecation). At that point, no new updates will be made to CodeQL Action v2, which means that new CodeQL analysis capabilities will only be available to users of CodeQL Action v3. We will keep a close eye on the migration progress across GitHub. If many workflow files still refer to CodeQL Action v2, we might consider scheduling one or more brownout moments later in the year to increase awareness.

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GitHub secret scanning protects users by searching repositories for known types of secrets such as tokens and private keys. By identifying and flagging these secrets, our scans help prevent data leaks and fraud.

We have partnered with Canva to scan for their tokens to help secure our mutual users in public repositories. Canva tokens enable users to perform authentication for their Canva Connect API integrations. GitHub will forward any exposed tokens found in public repositories to Canva, who will then rotate the token and notify the user about the leaked token. Read more information about Canva tokens.

GitHub Advanced Security customers can also scan for and block Canva tokens in their private repositories.

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