Use when participating in bug bounty programs.
Scanned 9/10/2026
Install to Claude Code
npx -y skills add LoopyLuci/Skills --skill bug-bounty-methodology --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Bug Bounty Methodology?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/loopyluci-bug-bounty-methodology)More formats (shields.io, HTML) on the badges page.
---
name: bug-bounty-methodology
description: "Use when participating in bug bounty programs."
version: 1.0.0
author: Hermes Agent
license: MIT
metadata:
hermes:
tags: [bug-bounty, vulnerability-disclosure, recon, HackerOne, Bugcrowd, triage]
related_skills: [osint-reconnaissance-techniques, webapp-penetration-testing, api-penetration-testing, sql-injection-exploitation]
---
# Bug Bounty Methodology
Participating in bug bounty programs — from platform selection and recon through vulnerability discovery, report writing, and disclosure.
## When to Use
- Hunting bugs on HackerOne, Bugcrowd, or Intigriti
- Building a systematic bug hunting methodology
- Writing effective vulnerability reports
- Prioritizing targets and attack surfaces
## Bug Hunting Methodology
```python
BUG_BOUNTY_WORKFLOW = {
'target_selection': 'Choose programs by scope, bounty range, response time, reputation',
'recon': 'Subdomain enumeration, port scanning, technology fingerprinting, Wayback Machine',
'automation': 'Nuclei templates, custom scripts for mass scanning',
'manual_testing': 'Deep dive on interesting endpoints, business logic, auth flows',
'exploitation': 'Validate PoC, maximize impact, chain vulnerabilities',
'reporting': 'Clear, reproducible, triage-friendly report',
}
class BugBountyHunter:
"""Track bug bounty findings and earnings."""
def __init__(self):
self.findings = []
self.total_earnings = 0.0
def submit_finding(self, program: str, vulnerability: str,
severity: str, payout: float = 0):
self.findings.append({
'program': program, 'vuln': vulnerability,
'severity': severity, 'payout': payout,
})
self.total_earnings += payout
def stats(self) -> Dict:
return {
'total_findings': len(self.findings),
'total_earnings': self.total_earnings,
'by_severity': {s: sum(1 for f in self.findings if f['severity'] == s)
for s in ['critical', 'high', 'medium', 'low', 'info']},
}
```
## Verification Checklist
- [ ] Program scope reviewed (in/out, eligible domains, testing rules)
- [ ] Reconnaissance phase (subdomain enumeration, technology detection, endpoint discovery)
- [ ] Automated scanning (nuclei, custom tools)
- [ ] Manual testing on high-value targets (auth, payment, PII)
- [ ] Impact maximization (chaining vulnerabilities)
- [ ] Report written with reproducible steps
- [ ] Proof of concept ready (screenshots, requests, scripts)
- [ ] Disclosure timeline: report → triage → fix → public disclosure
- [ ] Program-specific rules followed (rate limits, testing times, no social engineering)

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!