codeql

Interprocedural data flow and taint tracking analysis detects complex security vulnerabilities like SQL injection and path traversal by modeling custom API wrappers and semantic code paths. This semantic approach identifies flaws that standard pattern-matching tools often miss.

To perform a deep security audit, you create a CodeQL database for your project and execute multi-suite queries. You can run comprehensive audits or focus on high-precision checks to identify vulnerabilities across various programming languages.

Yes, the CodeQL CLI is a required dependency for running interprocedural taint tracking scans. You also need jq installed to support the automation scripts that execute the static analysis pipeline and process the vulnerability results.

Yes, customizable analysis supports multiple scan modes including high-precision important-only checks and comprehensive run-all audits. This allows you to validate custom data paths and focus on the most critical vulnerabilities without noise.

Custom data extension modeling allows you to define how project-specific API wrappers handle data flow. This ensures the taint tracking analysis accurately maps your custom data paths and detects potential exploits within your specific codebase logic.