Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sanjaysaini1952/BugBounty-Arsenal --skill methodologygit clone --depth 1 https://github.com/sanjaysaini1952/BugBounty-ArsenalWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sanjaysaini1952/bugbounty-arsenal/methodology)<a href="https://agentmods.dev/skills/sanjaysaini1952/bugbounty-arsenal/methodology"><img src="https://agentmods.dev/badge/skills/sanjaysaini1952/bugbounty-arsenal/methodology/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sanjaysaini1952/bugbounty-arsenal/methodology"><img src="https://agentmods.dev/badge/skills/sanjaysaini1952/bugbounty-arsenal/methodology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01359 |
| Opus 5 | $0.00000 | $0.00679 |
| Sonnet 5 | $0.00000 | $0.00272 |
| Haiku 4.5 | $0.00000 | $0.00136 |
Grade B, and why
methodology scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Cloud metadata endpointmediumServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
2. Probe cloud metadata endpoints (169.254.169.254) Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
4. Can you reproduce it with a clean curl command? How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hunting Methodology Skill
General-purpose hunting workflow. Load when: hunting, testing, exploitation, vulnerability hunting.
Trigger
Load when: hunt, hunt-methodology, bug-hunting, vulnerability-testing, pentest-methodology.
7-Question Gate (Validate Before Reporting)
Before submitting ANY finding, answer ALL seven:
- Is the target explicitly in scope?
- Is this on the accepted-impact list?
- Does this affect real users (not just the researcher)?
- Can you reproduce it with a clean curl command?
- Is this not already disclosed (check dupcheck)?
- Does the impact match or exceed the severity claimed?
- Would a triager agree this is a valid bug?
If ANY answer is "no" or "unsure" — do NOT report. Keep hunting.
5-Phase Non-Linear Workflow
Phase 1: Reconnaissance
Follow skills/recon/SKILL.md. Map the entire attack surface before testing.
Phase 2: Map & Rank
Priority Order:
1. Admin panels / dashboards (auth bypass, IDOR)
2. API endpoints with parameters (injection, IDOR, mass assignment)
3. Authentication flows (OAuth, JWT, session management)
4. File upload functionality (RCE, storage takeover)
5. Payment/subscription flows (business logic, race conditions)
6. Third-party integrations (SSRF, open redirect)
7. JavaScript bundles (secret keys, hidden endpoints, DOM XSS sinks)
8. GraphQL endpoints (introspection, batching, injection)
9. WebSocket connections (CSWSH, injection)
10. Mobile app APIs (deep links, cert pinning bypass)
Phase 3: Hunt
For each endpoint/classification:
- Read the applicable hunting skill (e.g., skills/hunting/xss/SKILL.md)
- Follow the detection patterns and bypass techniques
- Test both authenticated and unauthenticated states
- Chain findings (Bug A → Bug B → Bug C for impact amplification)
Phase 4: Validate
- Confirm every finding with a reproducible PoC
- Run the 7-Question Gate
- Deep-validate with curl commands
- Check for false positives (scan the same payload 3x minimum)
- Assess actual impact, not theoretical
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 141 lines · 0 tokens per session scan B 1eef43e702b4
methodology is a skill published in the GitHub repository sanjaysaini1952/BugBounty-Arsenal (2 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,359 tokens. A static security scan graded it B with 2 findings (cloud metadata endpoint, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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