codexstar69

codexstar69 / bug-hunter

Public

Adversarial AI bug hunter with auto-fix skill for Claude Code, Cursor, Codex CLI, GitHub Copilot CLI, Kiro CLI, Opencode, Pi Coding Agent, and more. Multi-agent pipeline finds security vulnerabilities, logic errors, and runtime bugs — then fixes them autonomously on a safe branch.

adversarial-ai ai-code-review auto-fix bug-detection claude
10
0
100% credibility
Found Mar 08, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
JavaScript
AI Summary

Bug Hunter is an AI-driven pipeline that detects runtime bugs such as security vulnerabilities and logic errors in code, verifies findings through adversarial checks, and optionally applies safe, branched fixes.

How It Works

1
🔍 Discover Bug Hunter

You learn about Bug Hunter, a smart helper that spots hidden problems in project code like security slips or logic mix-ups.

2
📥 Add to Your Toolkit

You simply download and place the tool in your helpers folder to get ready to use it.

3
🧪 Test on Examples

You try it on the included sample code with planted issues to see how it finds and handles bugs.

4
🐛 Hunt Bugs in Your Code

You tell it to check your own project, and it carefully explores for real-world issues that simple checkers miss.

5
Choose Your Path
📊
Check Only

Get a full report of issues without touching your code.

🔧
Fix Automatically

Let it safely suggest and apply changes on a protected copy.

6
📋 Review the Report

You receive a clear summary of confirmed bugs, challenges to them, and any fixes applied.

✅ Safer Project Ready

Your code is now stronger and more reliable, with bugs caught and fixed securely.

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Star Growth

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AI-Generated Review

What is bug-hunter?

Bug-hunter is a JavaScript CLI tool that deploys an adversarial AI pipeline to hunt runtime bugs like security vulnerabilities, logic errors, race conditions, and cross-file mismatches—stuff linters ignore. It integrates with coding agents such as Claude Code, Cursor, GitHub Copilot CLI, and others, scanning codebases or branches via commands like `/bug-hunter src/` or `/bug-hunter --staged`, then autonomously fixes confirmed issues on a safe `bug-hunter-fix-` branch with auto-revert on regressions. Developers get detailed reports, fix plans, and post-scan verification without manual intervention.

Why is it gaining traction?

Unlike static analyzers, it uses multi-agent roles—recon, hunter, skeptic, referee—for robust verification, catching adversarial attack detection gaps and real-world flaws in JS, Python, Go, and more. The fix-by-default mode with checkpoint commits, delta scanning for changes, and loop coverage for large repos hooks devs relying on AI agents, as it self-audits fixes and supports bug bounty hunter workflows on GitHub. Early adopters praise the safe branching and optional Context7 docs lookup for framework-specific adversarial LLM checks.

Who should use this?

Backend engineers hardening Express.js or PostgreSQL apps against SQL injection and auth flaws. Teams on Cursor or Copilot CLI pipelines needing automated bug hunter GPT-style validation before merges. Bug bounty hunters scanning open-source repos for logic errors and runtime gaps without full CI overhead.

Verdict

With 10 stars and a 1.0% credibility score, it's raw and unproven—docs are solid with a self-test fixture proving it spots planted critical bugs, but expect flakes in scaled runs. Worth a test-fixture spin if you're experimenting with adversarial AI bug hunter github tools; skip for production until more battle scars.

(198 words)

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