vulnhunter

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

6|20|Updated Mar 14, 2026
One-click install
npx skills add https://github.com/andresdefi/cryptoskills --skill vulnhunter-andresdefi
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vulnhunter
Source: https://github.com/andresdefi/cryptoskills/tree/main/skills/vulnhunter
Command: npx skills add https://github.com/andresdefi/cryptoskills --skill vulnhunter-andresdefi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Security reviews often miss recurring vulnerability patterns because auditors fix one instance without hunting for its variants elsewhere in the codebase. This Skill systematizes sharp edges detection and variant analysis so dangerous APIs, insecure defaults, and repeated vulnerability patterns are found and documented consistently. ## Core Features & Use Cases - Sharp Edges Detection: Systematically check for dangerous defaults, error-prone APIs, cryptographic footguns, and language-specific risks across Python, JavaScript, Rust, C/C++, and Solidity. - Variant Analysis: Extract abstract patterns from a confirmed vulnerability, then hunt for similar flaws using grep, Semgrep, and CodeQL search strategies. - Structured Reporting: Use the included variant report template and methodology guide to produce severity-scored findings with remediation guidance. - Use Case: After finding a reentrancy bug in one Solidity contract, use the variant hunting workflow to discover three more instances across LendingPool, Staking, and NFTVault contracts, then recommend a systemic ReentrancyGuard fix. ## Quick Start Review this codebase for security vulnerabilities using sharp edges detection and hunt for variants of any findings.

Frequently Asked Questions about vulnhunter

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

FAQPage Schema
How do I find vulnerability variants across a codebase?

Extract the abstract pattern from a confirmed vulnerability by identifying its source, transform, sink, and missing validation. Then search for that pattern using grep regexes or Semgrep rules, and validate each match for reachability and exploitability.

What is sharp edges detection in security code review?

Sharp edges detection is the systematic identification of error-prone APIs, dangerous defaults, and footgun designs such as strcpy, pickle.loads, tx.origin authentication, and permissive CORS. It uses categorized checklists covering authentication, injection, cryptography, and concurrency risks.

Which tools work with variant analysis for security auditing?

The methodology supports grep for quick regex searches, Semgrep for cross-language semantic pattern matching, and CodeQL for dataflow analysis. Language-specific tools like Bandit, Slither, and cargo audit complement the manual review workflow.

Does this approach work for Solidity smart contract audits?

Yes, it includes Solidity-specific sharp edges such as reentrancy, tx.origin authentication, and integer overflow, plus a worked example hunting reentrancy variants across DeFi contracts. Slither detectors and Semgrep rules for Solidity are provided.

How are findings severity-rated in the audit report?

Findings are scored using a CVSS-like matrix covering access vector, complexity, privileges, and impact, then prioritized in a matrix mapping exploitability against impact. Each finding requires proof of concept or clear reproduction steps before reporting.