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

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

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Customers desire clear, relevant, and actionable insights about how Actions workflows are being used in their organization. Today, we are thrilled to announce that Actions Usage Metrics is available in public beta for GitHub Enterprise Cloud plans.

Actions Usage Metrics screenshot

Time is the most important metric for DevOps and DevEx teams. The question they want answered is, “where are all my minutes going?” Actions Usage Metrics addresses this question and others by focusing on minutes used per workflow, job, repository, runtime OS, and runner type. This data helps organizations locate areas of improvement in their software delivery lifecycle, saving time and money.

Customers can filter data by any combination of workflows, jobs, repositories, runtime OS, and runner type to view total minutes, number of jobs, workflow executions, and more. All usage metrics, filtered or not, can be downloaded as a .csv file to use with your tool of choice.

By default, organization owners can access Actions Usage Metrics. However, access permissions can be granted to other members or teams using Actions fine-grained permissions. This ensures the right level of access to Actions Usage Metrics data, enabling informed decisions and improvements.

To learn more about Actions Usage Metrics, check out our docs or head to our community discussion.

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Dependabot grouped security updates are now generally available. This feature automatically groups Dependabot pull requests, lets you specify several additional options to fine tune your groupings.

You can enable grouped security updates for Dependabot at the repository or organization-level. To enable this feature, go to your repository or organization settings page, then go to the Code security and analysis tab, and click “Enable” for grouped security updates (this also requires each affected repository to enable Dependency graph, Dependabot alerts, and Dependabot security updates). When you enable this feature, Dependabot will collect all available security updates in a repository and attempt to open one pull request with all of them, per ecosystem, across directories.

If you would like more granular control over Dependabot’s grouping, you can also configure the dependabot.yml file in a repository to group by any of the following:

  • Package name
  • Dependency type (production vs development)
  • Semver update level (patch, minor, major)

For additional information, check out the Dependabot configuration file documentation.

For GitHub Enterprise Server users, grouped security updates will be available in Version 3.14.

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We have partnered with Mergify to scan for their tokens to help secure our mutual users in public repositories. Mergify’s API key enables users to interact with Mergify’s API in order to retrieve information on their merge queues. GitHub will forward any exposed API keys found in public repositories to Mergify, who will then revoke the key and notify the key owner. Read more information about Mergify API keys.

GitHub Advanced Security customers can also scan for and block Mergify tokens in their private repositories.
Learn more about secret scanning
Partner with GitHub on secret scanning

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GitHub secret scanning protects users by searching repositories for known types of secrets. By identifying and flagging these secrets, we help protect users from data leaks and fraud associated with exposed data.

We have partnered with volcengine to scan for their access tokens, which are used for cloud computing services. We’ll forward access tokens found in public repositories to volcengine, who will notify the user by email without making any changes to the tokens. Users can request support for their volcengine API tokens.

We continue to welcome new partners for public repository secret scanning. GitHub Advanced Security customers can also scan their private repositories for leaked secrets.
Learn more about secret scanning
Partner with GitHub on secret scanning

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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 Lightspeed to scan for their tokens to help secure our mutual users in public repositories. Lightspeed Retail Personal Tokens enable users to interact with Lightspeed Retail POS programmatically. Read more information about Lightspeed tokens.

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

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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 WorkOS to scan for their tokens to help secure our mutual users in public repositories. WorkOS’ API key enables access to WorkOS’ API for adding Enterprise Ready features to your application. GitHub will forward any exposed API keys found in public repositories to WorkOS, who will then notify admin users on your WorkOS account. Read more information about WorkOS API keys.

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

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With the 2.16.5 release of CodeQL, we’re introducing a new mechanism for creating a CodeQL database for Java codebases, without relying on a build. This enables organizations to more easily adopt CodeQL for Java projects at scale. Note: this release announcement contains details for users of the CodeQL CLI and advanced setup for code scanning. If you’re using GitHub code scanning default setup (which is powered by the CodeQL engine), this related release announcement will likely contain the information you’re looking for.

Previously, CodeQL required a working build to analyze Java projects. This could either be automatically detected or manually specified. Starting with CodeQL 2.16.5, you can now scan Java code without the need for a build. 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 GitHub.com advanced setup for code scanning and CodeQL CLI users scanning Java code:

  • Repositories using advanced setup for code scanning via workflow files will have the option to choose a build-mode. The default value for newly configured Java repos will be build-mode: none.
  • CodeQL CLI users will not experience any change in the default behaviour, for compatibility with existing workflows. Users that want to enable this feature can now use the --build-mode none option. Generally, we also recommend users set the --build-mode option when using the CLI to make it easier to debug and persist the configuration should default behaviour change at any point in the future.
    codeql database create test_no_build_db --language java --build-mode none

  • Repositories containing a mix of Kotlin and Java code still require a working build for CodeQL analysis.

The new mechanism for scanning Java is available on GitHub.com and in CodeQL CLI 2.16.5. While in public beta, this feature will not be available on GitHub Enterprise Server for default setup or advanced setup for code scanning. As we continue to work on scanning Java projects without the need for working builds, send us your feedback.

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Today, we’re releasing a host of new insights to the security overview dashboard, as well as an enhanced secret scanning metrics page.

New dashboard insights

overview dashboard with third-party tools, the trend indicator for age of alerts, and reopened alerts tile highlighted

  • Third-party alerts integration: Beyond GitHub’s own CodeQL, secret scanning, and Dependabot security tools, you can now view alert metrics for third-party tools directly on the overview dashboard. Use tool:[third-party-tool name] to view metrics for a specific third-party security tool, or tool:third-party to view metrics for all third-party security alerts.
  • Reopened alerts tracking: Uncover recurring vulnerabilities with the new reopened alerts metric tile, which identifies vulnerabilities that have resurfaced after being previously resolved. This data point helps assess the long-term effectiveness of your remediation efforts.
  • Trend indicators: Review changes over time with trend indicators for key metrics like age of alerts, mean time to remediate, net resolve rate, and total alert count. These indicators offer a clear view of performance shifts and trends between a given date range and that same range reflected backward in time.
  • Advisories tab: Stay informed with the new advisories table, which details the top 10 alert advisories affecting your organization, including the advisories’ CVE IDs, ecosystems, open alert counts, and severities.

Secret scanning metrics page enhancements

secret scanning metrics page with filter bar highlighted

You can now refine your insights with filters for dates, repository custom properties, teams, and more on the secret scanning metrics page. These new filters empower you to pinpoint specific repositories and view changes over time, enabling a more targeted analysis. Additionally, if you are an organization member, you can now view metrics for the repositories you have access to.

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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GitHub Copilot in the CLI banner demonstrating "ghcs" alias for supporting command execution

GitHub Copilot in the CLI is now generally available

We are excited to announce Copilot in the CLI is now generally available (GA) for all our Copilot Individual, Business, and Enterprise customers.

Copilot in the CLI allows users to access the power of GitHub Copilot to get command suggestions and explanations without leaving the terminal. Starting today, developers can also use GitHub Copilot to execute suggested commands based on feedback shared during the public beta.

GitHub Copilot in the CLI has also gained a couple of helper aliases for Bash, PowerShell, and Zsh. The new gh copilot alias command generates shell-specific configuration for ghcs and ghce aliases. These aliases use fewer keystrokes to jump into the gh copilot experience. Additionally, the new ghcs alias streamlines the process for executing commands suggested while making them available for later reuse!

How to get started?

If you were already using Public Beta:

  • Update the extension to v1.0.0 by running gh extension upgrade gh-copilot.

If you haven’t enabled Copilot in the CLI yet or coming from the GitHub Next technical preview

  • Copilot Individual users: You automatically have access to the Copilot in the CLI.
  • Copilot Business and Enterprise users: Your organization admins will need to grant you access to Copilot in the CLI.

After receiving access to Copilot in the CLI, consult our guide on how to install the tool and get started.

How to give us your feedback?

We are dedicated to continuous improvement and innovation. Your feedback remains a crucial part of our development process, and we look forward to hearing more about your experiences with GitHub Copilot in the CLI. Please use our public repository to provide feedback or ideas on how to improve the product.

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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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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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SSH CAs uploaded to GitHub.com after March 27th, or in GHES 3.13 and beyond, can only sign certificates that expire. They must expire within 366 days of being created.
While expirations on certificates are not required by signing tools such as ssh-keygen, we are enforcing this best practice in order to protect against a weakness in how SSH certificates are linked to users.

CAs uploaded before the cutoff date or release will be marked in the UI as being allowed to sign non-expiring certificates:

image

An “upgrade” option on the CA lets you enforce expiration of signed certificates. Once you’ve validated that you are indeed using a lifetime on your certificates, we recommend upgrading your CAs. This upgrade step is irreversible, and new CAs cannot be downgraded to allow non-expiring certificates.
If a certificate is signed with no expiration, or a too-long expiration, it will be rejected during SSH connection with an error indicating The SSH certificate used was issued for a longer period than allowed.

This change forces the valid_after issuance timestamp to be written to the certificate, which allows GitHub to detect if the user changed their username after the certificate was issued for that username. This prevents a reuse attack vector where the former holder of a username is able to use certificates issued to them to sign in as the new holder of that username.

To learn more about managing SSH CAs, see “Managing your organization’s SSH CAs” and “Managing SSH CAs for your enterprise.” For information on using SSH CAs, see “About SSH CAs.”

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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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Dependency review helps you understand dependency changes and the security impact of these changes at every pull request. We have updated the dependency review action to include information from the OpenSSF Scorecard project into the review, helping you better understand the security posture of the dependencies that you’re using.

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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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Starting today for GitHub Enterprise Cloud and as part of GitHub Enterprise Server version 3.13, enterprise and organization audit log events will include the applicable SAML and SCIM identity data associated with the user. This data provides increased visibility into the identity of the user and enables logs from multiple systems to quickly and easily be linked using a common corporate identity. The SAML identity information will be displayed in the external_identity_nameid field and the SCIM identity data will be displayed in the external_identity_username field within the audit log payloads.

In GitHub Enterprise Cloud Classic, SAML SSO gives organization and enterprise owners a way to control and secure access to resources like repositories, issues, and pull requests. Organization owners can invite GitHub users to join an organization backed by SAML SSO, allowing users to become members of the organization while retaining their existing identity and contributions on GitHub.

If your Enterprise Cloud Classic organization uses SAML SSO, you can use SCIM to add, manage, and remove organization members’ access to your organization. For example, an administrator can deprovision an organization member using SCIM and automatically remove the member from the organization.

To learn more, read our documentation about SAML SSO authentication data in our audit logs.

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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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