HackSkills is an organized knowledge base of installable skills that gives AI agents practical security knowledge across areas such as web security, privilege escalation, reverse engineering, and digital forensics. It is intended for bug bounty work, penetration testing, CTF competitions, and authorized security research. The catalogue entries are the project's own master, category, and topic skills.
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 yaklang/hack-skills --skill attack-surface-mappinggit clone --depth 1 https://github.com/yaklang/hack-skillsWrote 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/yaklang/hack-skills/attack-surface-mapping)<a href="https://agentmods.dev/skills/yaklang/hack-skills/attack-surface-mapping"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/attack-surface-mapping/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/yaklang/hack-skills/attack-surface-mapping"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/attack-surface-mapping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk warn
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 | $0.00106 | $0.02484 |
| Opus 5.5 | $0.00042 | $0.00994 |
| Sonnet 5.5 | $0.00021 | $0.00497 |
| Haiku 4.5 | $0.00011 | $0.00248 |
Grade A, and why
attack-surface-mapping 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attack Surface Mapping
Given one target and one application, draw the surface from what that application already exposes. Then stop. Testing lives in other skills.
This skill is the fast path. Success is a portrait plus a host/API inventory plus a key table plus response-class labels plus an object graph. A probe count is not success.
Field patterns for where the rest of the surface actually lives: SURFACE_PATTERNS.md.
When
- A new URL, a new app, or "I only see a login page"
- Need to know what to test before loading injection / auth / upload skills
- The agent is about to brute directories, spray quotes, or expand to unrelated hosts
Do not use this skill to expand an organization-wide host universe. Map the current application cluster. Finish it. Then, if scope allows, take the next cluster.
Authorization and destruction bounds: hack start gate. Stay in scope.
What must exist (not a file tree)
Before any vulnerability skill, these facts must be retrievable. Persist them in whatever the local workspace already uses for notes and evidence — an existing task folder, a proxy project, session notes, a ticket. Do not invent a new directory layout when one is already in play.
| Fact | Keep |
|---|---|
| Portrait | 3–5 sentences, not an essay |
| Hosts | Business hosts, gateways, API domains this app already named |
| Endpoints | Method, path, params, auth required? |
| Keys | Signing salt, ciphertext id + frontend pubkey, hidden/admin route, hardcoded demo account. Record none per row if absent |
| Response class | Login-gate / differential / unauthenticated exception |
| Object graph | list → detail → attachment / export / approval |
Requests, diffs, and screenshots stay where they were captured when that store is already the working set. Empty inventory plus "I will brute paths next" is a failed mapping.
Fast path
Portrait
→ find the business plane (login is a shell)
→ inventory from the app (JS / traffic / docs), keys not just paths
→ classify responses
→ grow the object graph from responses
→ same-skin / same-gate collapse
→ surface-done → hand off
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.
- 1mo ago First seen · 195 lines · 106 tokens per session scan A b0acdfa1ec5c
attack-surface-mapping is a skill published in the GitHub repository yaklang/hack-skills (2,460 stars, last pushed 1mo ago), licensed MIT. It adds 106 tokens to every session and 2,484 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-14.
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