Automatically scanning your code for vulnerabilities and errors

You can use code scanning to find security vulnerabilities and errors in the code for your project on GitHub.

Learn about the different types of code scanning alerts and the information that helps you understand the problem each alert highlights.

When code scanning identifies a problem in a pull request, you can review the highlighted code and resolve the alert.

You can configure code scanning for a repository to find security vulnerabilities in your code.

The tool status page shows useful information about all of your code scanning tools. If code scanning is not working as you'd expect, the tool status page is a good starting point for debugging problems.

From the security view, you can view, fix, or dismiss alerts for potential vulnerabilities or errors in your project's code.

You can add code scanning alerts to issues using task lists. This makes it easy to create a plan for development work that includes fixing alerts.

You can customize how GitHub scans the code in your project for vulnerabilities and errors.

You can use CodeQL to identify vulnerabilities and errors in your code. The results are shown as code scanning alerts in GitHub.

Recommended specifications (RAM, CPU cores, and disk) for running CodeQL analysis on self-hosted machines, based on the size of your codebase.

You can choose from different built-in CodeQL query suites to use in your CodeQL code scanning setup.

You can configure how GitHub uses the CodeQL analysis workflow to scan code written in compiled languages for vulnerabilities and errors.

You can configure code scanning for eligible repositories in your organization using default setup for CodeQL or use a script to configure advanced setup for a specific group of repositories.

If you're having problems with the default code scanning setup, you can troubleshoot by using these tips for resolving issues.

If you're having problems with advanced setup for code scanning, you can troubleshoot by using these tips for resolving issues.

You can run code scanning in a container by ensuring that all processes run in the same container.

You can view the output generated during code scanning analysis in GitHub.com.