Btr4k

Btr4k / bugbounty-agent

Public

Automated bug bounty reconnaissance and scanning agent

24
4
100% credibility
Found Apr 06, 2026 at 21 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Go
AI Summary

HawkEye automates bug bounty hunting by chaining reconnaissance, vulnerability scanning, AI validation, and report generation into a single workflow for authorized security testing.

How It Works

1
🔍 Discover HawkEye

You hear about HawkEye, a helpful tool that automatically checks websites for security weak spots and makes bug hunting easier.

2
📥 Get it ready

You download and set it up quickly with a simple installer that grabs everything you need.

3
🧠 Link a smart thinker

You connect a clever AI helper so it can deeply review findings and spot real problems from false alarms.

4
🎯 Choose your target

You pick a website you have permission to test, like one from a bug bounty program.

5
🚀 Start the full check

With one simple command, you launch the complete scan that explores sub-sites, hunts vulnerabilities, and validates everything.

6
⏳ Watch it work

You see progress updates as it gathers clues, tests for issues, and uses AI to confirm what's real.

📊 Receive your report

You get a clean, professional summary with only confirmed issues, proof, risks, and fix suggestions — ready for bug bounties!

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Star Growth

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AI-Generated Review

What is bugbounty-agent?

Bugbounty-agent (aka HawkEye) is an automated bug bounty scanner built in Go that runs full recon, vulnerability scanning, AI validation, and reporting in one command: `./hawkeye -d target.com`. It discovers subdomains, live URLs, and JS files, then probes for CVEs, misconfigs, XSS, SQLi, CORS issues, and hidden params using tools like Nuclei, ffuf, and dalfox. An LLM agent (Claude, GPT-4, DeepSeek) filters false positives, generates PoCs, and outputs clean Markdown reports with severity breakdowns.

Why is it gaining traction?

This bug bounty AI agent on GitHub stands out by chaining recon-to-report without noise, using AI for automated bug triage and JS secret hunting (API keys, endpoints) that manual tools miss. Developers love the zero-config install script, verbose progress, and options like `--js-only` for quick scans or `--skip-recon` for known subdomains. Parallel scanning and multi-AI support keep costs low while delivering analyst-grade output.

Who should use this?

Bug bounty hunters automating recon and initial scans on large scopes, like HackerOne targets. Security teams triaging Nuclei alerts with AI to cut false positives. Pentesters needing fast JS analysis for cloud leaks or parameter discovery before deep dives.

Verdict

Promising automated bug bounty tool for early adopters, but 18 stars and 1.0% credibility score signal low maturity—test on non-prod first. Solid docs and MIT license make it worth forking; pair with manual review until more battle-tested.

(198 words)

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