codeql

Static analysis detects security vulnerabilities by querying your codebase with CodeQL. You build a language-specific CodeQL database, run custom QL queries against it, and analyze the resulting data-flow and taint-tracking paths to identify interprocedural security issues.

Integrating CodeQL into CI/CD pipelines automates continuous security vulnerability detection. You add steps to create CodeQL databases during the build process, execute custom queries, and package the analysis results to fail workflows when security vulnerabilities or taint paths are found.

Yes, you need the CodeQL CLI installed to run custom queries for taint tracking. The CLI is required to create CodeQL databases for your project's source code, execute the QL queries, and package the data-flow analysis results.

Building a CodeQL database for multiple languages requires language-specific build steps. You use the CodeQL CLI to capture compilation details during the build process, creating separate databases that enable precise security analysis and interprocedural data-flow tracking across your project.

Writing custom QL queries to find data-flow issues involves using CodeQL's taint-tracking libraries. You define source and sink points in your code, and the query analyzes the generated database to detect interprocedural paths where untrusted data flows to vulnerable operations.

Yes, you can conduct comprehensive security audits across repositories using CodeQL. By generating databases for each repository and running targeted queries, you can identify taint paths, data-flow vulnerabilities, and security issues across multiple projects.