vulnhunter

Detect dangerous APIs, footgun patterns, and vulnerability variants across codebases.

Updated Jul 10, 2026
One-click install
npx skills add https://github.com/Kaleb-Rupe/aurora --skill vulnhunter-kaleb-rupe
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vulnhunter
Source: https://github.com/Kaleb-Rupe/aurora/tree/main/claude/skills/vulnhunter
Command: npx skills add https://github.com/Kaleb-Rupe/aurora --skill vulnhunter-kaleb-rupe

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Security code reviews often miss recurring vulnerability patterns because reviewers lack a systematic method to find dangerous APIs, insecure defaults, and variants of known bugs across large codebases. ## Core Features & Use Cases - Sharp Edges Detection: Systematically identify dangerous APIs, weak cryptography, insecure defaults, and language-specific footguns in Python, JavaScript, Rust, C/C++, and Solidity. - Variant Analysis: Extract abstract patterns from a confirmed vulnerability and hunt for similar flaws across the codebase using grep, Semgrep, and CodeQL queries. - Structured Reporting: Produce severity-rated findings and variant analysis reports using built-in templates and a phased audit methodology. - Use Case: After finding one SQL injection in a Flask app, use the variant hunting workflow to extract the source-to-sink pattern, search all routes, and confirm four additional injection points with a consolidated remediation plan. ## Quick Start Review this codebase for security vulnerabilities using sharp edges detection and variant analysis, then report all confirmed findings with severity ratings.

Frequently Asked Questions about vulnhunter

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

FAQPage Schema
How do I find SQL injection vulnerabilities in a Python codebase?

Search for user input flowing into database calls without parameterization using grep patterns for f-strings, concatenation, and format strings in execute() calls. Semgrep taint-tracking rules can automate detection of source-to-sink flows.

What is variant analysis in security auditing?

Variant analysis extracts the abstract pattern from a confirmed vulnerability, such as source-to-sink data flow, then searches the codebase for structurally similar flaws. Each candidate match is validated for reachability, input control, and impact before being reported.

Which tools work for static security analysis of code?

Semgrep provides cross-language pattern matching, CodeQL enables dataflow analysis, and language-specific tools include Bandit for Python, Slither for Solidity, and cargo audit for Rust. The methodology combines automated scans with manual checklist review.

Does this approach work for Solidity smart contract audits?

Yes, the skill includes Solidity-specific patterns covering reentrancy, tx.origin authentication, delegatecall risks, and integer overflow. A worked example demonstrates hunting reentrancy variants across a DeFi protocol using Slither and Semgrep rules.

How are findings prioritized in a security audit report?

Findings are scored using CVSS-like factors including access vector, complexity, privileges, and impact, then mapped to a priority matrix combining exploitability with impact. Critical issues that are easy to exploit are flagged for immediate remediation.