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codeql

Perform static code analysis with CodeQL for security vulnerabilities and data flow.

Updated Feb 13, 2026
Search Tags:#static analysis#security#data flow#vulnerability detection#codeql#taint tracking#ql
One-click install
npx skills add https://github.com/fjor1025/InfoSec-Framework --skill codeql-fjor1025
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codeql
Source: https://github.com/fjor1025/InfoSec-Framework/tree/main/ClaudeSkills/plugins/static-analysis/skills/codeql
Command: npx skills add https://github.com/fjor1025/InfoSec-Framework --skill codeql-fjor1025

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables in-depth static analysis of source code to identify security vulnerabilities, track data flow, and detect complex bugs that traditional methods might miss.

Core Features & Use Cases

  • Vulnerability Detection: Identifies security flaws using pre-defined and custom queries.
  • Data Flow & Taint Tracking: Traces the flow of data through the codebase to find potential injection points or leaks.
  • CodeQL Database Creation: Builds specialized databases from source code for analysis.
  • Custom Query Development: Supports writing and running bespoke QL queries for specific analysis needs.
  • Use Case: Analyze a Rust smart contract codebase to find potential reentrancy vulnerabilities or insecure handling of external calls.

Quick Start

Use the codeql skill to create a database for the current Go project and run the standard security-extended query suite.

Frequently Asked Questions about codeql

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify security vulnerabilities using static code analysis?▼

Static code analysis identifies security vulnerabilities by building a CodeQL database from source code and executing pre-defined or custom queries to detect complex flaws through interprocedural analysis.

How does taint tracking trace data flow to find injection points?▼

Taint tracking traces data flow through the codebase to find injection points by analyzing how untrusted inputs propagate across functions, using custom QL queries to uncover potential leaks.

Can I analyze a Rust smart contract codebase for reentrancy vulnerabilities?▼

Yes, you can analyze a Rust smart contract codebase for reentrancy vulnerabilities by creating a CodeQL database and running bespoke QL queries to detect insecure handling of external calls.

What is the best way to write custom QL queries for specific code analysis needs?▼

The best way to write custom QL queries for specific code analysis needs is to develop bespoke queries within the CodeQL framework, allowing targeted interprocedural analysis for complex security bugs.

Does this static analysis approach support integration into CI/CD pipelines?▼

Yes, this static analysis approach supports integration into CI/CD pipelines, allowing automated vulnerability detection and data flow analysis during the software build and deployment process.

Do I need to create a CodeQL database before running security queries?▼

Yes, you need to create a CodeQL database before running security queries, because the database builds a specialized representation of the source code required for interprocedural taint tracking.

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