code-audit

Audit code security vulnerabilities across 9 languages and 14 frameworks.

Updated Aug 28, 2021
One-click install
npx skills add https://github.com/XhstormR/dotfiles --skill code-audit-xhstormr
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: code-audit
Source: https://github.com/XhstormR/dotfiles/tree/main/.claude/skills/code-audit
Command: npx skills add https://github.com/XhstormR/dotfiles --skill code-audit-xhstormr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Code auditing is often manual, slow, and error-prone. This Skill orchestrates automated, self-contained code-security audits with a dual-track model and multi-agent reasoning to reliably identify vulnerabilities across languages and frameworks.

Core Features & Use Cases

  • Dual-track auditing (Sink-driven + Control-driven) for comprehensive detection
  • 9 languages and 14 frameworks supported, plus WooYun-inspired case library
  • Anti-Hallucination rules and Read/Grep/Glob-backed verification for accuracy
  • CI/CD-ready reporting with attack paths, remediation guidance, and reproducible turns

Quick Start

To begin, run code-audit on a target repository to generate a structured vulnerability report with confirmed findings and remediation guidance.

Frequently Asked Questions about code-audit

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

FAQPage Schema
How do I automate code security audits across multiple languages and frameworks?

Static analysis for code security uses a dual-track approach combining sink-driven and control-driven detection. This multi-agent workflow cross-references 143 mandatory checks with real-world WooYun cases to comprehensively identify vulnerabilities across supported languages.

Does this code audit tool support CI/CD integration and reproducible reporting?

Code audit accuracy is enforced through anti-hallucination rules that require findings to be grounded in actual code via Read, Grep, and Glob tooling. This verification process ensures reproducible analysis turns and reliable vulnerability confirmation.

Can I use this to perform taint analysis on a large scale repository?

Yes, you can perform taint analysis at scale because the Skill orchestrates multi-agent reasoning to audit code security vulnerabilities. It supports deep, reproducible analysis across 9 languages and 14 frameworks for large target repositories.

What is the best way to identify security vulnerabilities without getting false positives?

The best way to identify vulnerabilities without false positives is using a dual-track model with anti-hallucination rules. This approach verifies findings against actual code using Read and Glob tooling, ensuring grounded and accurate detection.

Are there limitations when using multi-agent static analysis for code audits?

Limitations of multi-agent static analysis include dependency on supported environments, as the workflow is constrained to 9 languages, 14 frameworks, and 143 mandatory checks. Auditing code outside these supported specifications may not yield comprehensive results.