What makes CodeQL different from standard linting or Semgrep?

Unlike pattern-matching tools that look at single files, CodeQL performs interprocedural analysis. It tracks data flow across your entire application, identifying how input in one function might reach a dangerous sink in a different part of the codebase.

Do I need to compile my code to use the CodeQL skill?

For compiled languages like C/C++, Java, C#, and Rust, CodeQL requires a successful build command to create its analysis database. For interpreted languages like Python and JavaScript, no build is required.

Does this skill work with Trail of Bits security queries?

Yes, the skill includes instructions for downloading and running specialized query packs from Trail of Bits for enhanced coverage in Go and C++ environments.

Can I use this skill to write my own security rules?

Yes, this skill provides the structure and guidance to write custom QL queries, allowing you to define specific patterns or proprietary security requirements tailored to your project.

CodeQL Security Analysis

Name: CodeQL Security Analysis
Author: trailofbits

bytrailofbits

•

938

安全与测试

Performs deep static analysis and interprocedural taint tracking to detect complex security vulnerabilities across multi-function code paths.

关于

The CodeQL Security Analysis skill empowers Claude to conduct sophisticated security audits by leveraging the CodeQL engine to find vulnerabilities that pattern-matching tools miss. By modeling code as a database, it enables interprocedural data flow analysis, allowing you to trace untrusted input from its source through multiple function calls to dangerous sinks. It is ideal for security researchers and developers performing deep audits, creating custom vulnerability queries, or integrating comprehensive security scanning into CI/CD pipelines across languages like Python, JavaScript, Go, C++, and Java.

主要功能

938 GitHub stars
Interprocedural data flow and taint tracking analysis
Detection of complex vulnerabilities spanning multiple files and functions
Automated CodeQL database creation for compiled and interpreted languages
Integration with Trail of Bits and GitHub security query packs
Support for writing, testing, and running custom QL queries

使用场景

Conducting deep security audits on large-scale, complex codebases
Identifying zero-day vulnerabilities using custom data flow queries
Setting up automated security analysis in GitHub Actions pipelines

关于

主要功能

938 GitHub stars
Interprocedural data flow and taint tracking analysis
Detection of complex vulnerabilities spanning multiple files and functions
Automated CodeQL database creation for compiled and interpreted languages
Integration with Trail of Bits and GitHub security query packs
Support for writing, testing, and running custom QL queries

使用场景

Conducting deep security audits on large-scale, complex codebases
Identifying zero-day vulnerabilities using custom data flow queries
Setting up automated security analysis in GitHub Actions pipelines