Back to skills
SKILL.md
Bug Bounty Methodology
ASecurityUse when participating in bug bounty programs.
- 2 stars
- 0 votes
- 0 copies
- 3 views
- Added September 10, 2026
Works with
Security analysis
100/100npx -y skills add LoopyLuci/Skills --skill bug-bounty-methodology --agent claude-codeAre you the author of Bug Bounty Methodology?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/loopyluci-bug-bounty-methodology)---
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)
Attribution
Comments
Loading comments…
Newsletter
Get the weekly list of safe new skills, and the ones we pulled.