security-and-compliance

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Java projects no longer require a build when using code scanning via default setup

CodeQL, the static analysis engine that powers GitHub code scanning, can now analyze Java projects without needing a build. This enables organizations to more easily roll out CodeQL at scale. This new way of analyzing Java codebases is now enabled by default for GitHub.com users setting up new repositories with default setup for code scanning.

Previously, CodeQL required a working build to analyze Java projects. This could either be automatically detected or manually specified. By removing that requirement, our large-scale testing has shown that CodeQL can be successfully enabled for over 90% of Java repos without manual intervention.

This feature is currently in public beta and is accessible to all users scanning Java code using default setup for code scanning on GitHub.com:

  • Anyone setting up their repo using code scanning default setup will automatically benefit from this new analysis approach.
  • Repositories containing a mix of Kotlin and Java code still require a working build for CodeQL analysis. CodeQL will default to the autobuild build mode to automatically try and detect the right build command.
  • Repositories with an existing code scanning setup will not experience any changes. If code scanning is working for you today it will continue to work as-is, and there is no need to change your configuration.

GitHub.com users using advanced setup for code scanning and users of the CodeQL CLI will be able to analyze Java projects without needing a working build as part of CodeQL CLI version 2.16.5. While in public beta, this feature will not be available for GitHub Enterprise Server. As we continue to work on scanning Java projects without needing a working build, send us your feedback.

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Security overview dashboard: Alert age trends, custom repository and severity filters, and date pickers

Starting today, you can take advantage of the new “age” grouping for the alert trends graph and explore enhanced filter options on the security overview dashboard, aimed at improving your analytical process and security management.

alert trends grouped by age

Explore the dynamics of your security alerts with the new alert age grouping on the alert trends graph. This new functionality offers a refined view into the lifecycle of your security alerts, enabling you to better evaluate the timeliness and effectiveness of your response strategies.

New filter options

repository custom property filter on the security overview page

Leverage enhanced filters to fine-tune your security insights on the overview dashboard:
* Custom repository property filters: With repository custom properties, you can now tag your repositories with descriptive metadata, aiding in efficient organization and analysis across security overview.
* Severity filters: Severity-based filters allow you to concentrate on the vulnerabilities that matter most, streamlining the process of security risk assessment and prioritization.
* Improved date picker controls: Navigate through time with ease using the new date picker options, allowing for quick selection of rolling periods like “Last 14 days,” “Last 30 days,” or “Last 90 days.” Bookmark your preferred time window to keep your analysis current with each visit.

You can access these new functionalities in security overview by navigating to the “Security” tab at the organization level.

These features are 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 send us your feedback

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Improved error handling for Dependabot updates for NuGet

Dependabot will now fail gracefully with informative error messages when an unsupported NuGet project type is encountered. If you were using an unsupported project type previously, Dependabot might have failed silently without producing updates. Dependabot is able to process updates to NuGet project files in the .csproj, .vbproj, and .fsproj formats.

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Code scanning now suggests AI-powered autofixes for CodeQL alerts in pull request (beta)

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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Enablement trends for security products (public beta)

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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Dependabot security updates work with private registries even if target branch is specified

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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Dependabot will now pause scheduled jobs after 15 failures

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 2.16.4: AI-powered autofixes for Java, support for C# 12 & Go 1.22, new queries

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 AI-generated custom patterns (public beta)

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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Group Configuration Options for Dependabot Security Updates – Public Beta

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 2.16.3: AI-powered autofixes for Python, updated queries, and security fixes

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: New Android queries and improved precision

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 adds validity checks for Mailgun and Mailchimp

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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Dependabot support for pub private repositories and registries

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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