Complete GitHub Bounty Hunting Toolkit for Developers (2026)

After claiming $3,100 in bounties across 9 PRs, here is every tool and technique I use.

The Toolkit

1. Finding Bounties

Search query: label:bounty is:issue is:open
Filter by language: language:python, language:typescript
Filter by difficulty: label:"good first issue"

2. Automated Scanner (BountyHunter)

Python script running 24/7 on GitHub Actions (free). Scans 11 queries every 30 minutes. Scores bounties by language match, amount, and competition level. Open source at github.com/luw8072-gif/bountyhunter.

3. PR Templates

git checkout -b fix/issue-XX
git add . && git commit -m "fix: description (closes #XX)"
git push origin fix/issue-XX
gh pr create --repo owner/repo --title "fix: ..." --body "Closes #XX"
gh issue comment XX --repo owner/repo --body "/claim #XX"

4. Testing

ALWAYS write tests. PRs with tests are 2x more likely to be merged. Even basic tests show effort.

5. Batching

One repo, multiple issues in one PR. Saves time and shows depth. My record: 8 issues in one PR.

Real Results

• OpenAgents: $2,200 (Python, 1 hour)
• Agent Playground: $800 (TypeScript, 13 issues)
• SecureBananaLabs: 4 issues (JavaScript)
• Memanto: $100 (Python, benchmark)

Key Tips

1. Pick repos with recently merged bounty PRs (active maintainers)
2. Avoid Solidity, hardware, and 30+ comment issues
3. Diversify: 5 PRs across 3 repos
4. Tests double your merge rate
5. Use AI to write code, but verify it yourself

Free tools and full guide: github.com/luw8072-gif