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 ShulkwiSEC/bb-huge --skill hackgit clone --depth 1 https://github.com/ShulkwiSEC/bb-hugeWrote 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/shulkwisec/bb-huge/hack)<a href="https://agentmods.dev/skills/shulkwisec/bb-huge/hack"><img src="https://agentmods.dev/badge/skills/shulkwisec/bb-huge/hack/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/shulkwisec/bb-huge/hack"><img src="https://agentmods.dev/badge/skills/shulkwisec/bb-huge/hack.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 | $0.00047 | $0.01912 |
| Opus 5 | $0.00023 | $0.00956 |
| Sonnet 5 | $0.00009 | $0.00382 |
| Haiku 4.5 | $0.00005 | $0.00191 |
Grade A, and why
hack scanned grade A with 0 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 7d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to hack — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HACKING SKILLS / HackSkills
Overview
This is a top-level routing skill for bug bounty, web security, API security, and authorized penetration testing.
Its core role is not to replace all specialized techniques, but to help the agent:
- First determine the testing phase (Recon / Validation / Privilege Escalation / Chain building)
- Then select the correct vulnerability category
- Avoid relying only on baseline model memory; prefer structured methodology
- Prioritize boundary conditions AI often misses but that matter in real engagements
Trust Model
- This knowledge base emphasizes content safety and auditability.
- Use this only within authorized targets, legitimate research, defensive validation, and bug-bounty-approved rules.
- Do not use these techniques for unauthorized attacks.
When to Use This Skill
Use this skill first in the following scenarios:
- You just received a new bug bounty target and do not know where to start
- You need to decide whether to load XSS / SQLi / SSRF / IDOR / JWT / API tracks first
- You want the agent to perform Web/API security testing with a more stable methodology
- You need to route scattered findings to the right attack surface
- You want AI to miss fewer critical test points in security work
Operating Model
Step 1: Start with Recon and context validation
Collect first:
- Target type: classic web, REST API, mobile backend, admin panel, payment flow, file upload, GraphQL
- Identity and permission model: anonymous, regular user, admin, multi-tenant
- Input locations: URL, query parameters, JSON, headers, cookies, filenames, imported files, templates, reflection points
- Output locations: HTML, attributes, JS, PDF, email, logs, background tasks, mobile endpoints
Step 2: Route by observed behavior
| Signal | Priority direction |
|---|---|
| Input reflects into HTML / JS | XSS / SSTI |
| Server actively fetches URL / hostname | SSRF |
| Accepts XML / Office / SVG | XXE |
| Path, filename, or download endpoint is controllable | Path Traversal / LFI |
| Many object IDs appear in APIs | IDOR / BOLA / BFLA |
| Login, reset password, 2FA, sessions | Auth Bypass / JWT / OAuth |
| Multi-step transactions, coupons, pricing, inventory | Business Logic |
| MongoDB / JSON query syntax exposure | NoSQL Injection |
| CLI tools, image processing, importers | Command Injection |
| HTTP parsing anomalies / front-back framing mismatch | Request Smuggling |
Node.js JSON handling / controllable __proto__ |
Prototype Pollution |
| PHP weak comparison / 0e hash / loose conditions | Type Juggling |
| Repeated parameter names / WAF-app parsing mismatch | HTTP Parameter Pollution |
| One-time operations (coupon/inventory/reset) | Race Condition |
| XML/XSLT template processing | XSLT Injection |
| Accessible .git/.svn/.env paths | Insecure SCM |
| CSV/Excel export features | CSV Formula Injection |
| WebSocket protocol upgrades | WebSocket Security |
| Internal package names / supply-chain inventory | Dependency Confusion |
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.
- 7d ago First seen · 163 lines · 47 tokens per session scan A cc093d046689
hack is a skill published in the GitHub repository ShulkwiSEC/bb-huge (22 stars, last pushed 2mo ago), licensed MIT. It adds 47 tokens to every session and 1,912 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to hack, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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GitHub Copilot CLI as optional zero-cost provider via copilot -p programmatic mode.
supabase
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skill-security-framing
URL validation and content sanitization for untrusted sources — use when handling external input safely.
race
Race condition / TOCTOU playbook — limit overrun (one-time codes used twice, gift cards spent twice), single-packet attack (last-byte sync) to force parallel processing, and state-confusion races (file upload + read, order before payment). Use when timing-sensitive logic could be abused — one-time codes, coupons/gift…