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wiki-arsenal

Fast PARALLEL wiki lookup engine over wiki/techniques + wiki/payloads + wiki/tools + wiki/cheatsheets for a surface/service/vuln-class. Two modes - quick (one qmd search, cheap, fire constantly) and deep (4 parallel subagents, one per area, merged ready-to-use arsenal card, cached). This is the fast path arsenal that `arsenal` delegates to; the hunt-* skills each inline their own qmd_query and can hand off here for a parallel lookup. Use for "what do I use against <surface>", "arsenal for <X>", "deep/full arsenal", "tool + payload + technique + cheatsheet for <X>", "fast wiki lookup", "parallel wiki search", any "how do I attack/exploit <service|vuln-class>" where you want the documented tooling + payloads before hand-rolling.

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含まれるファイル(1)

  • SKILL.md4.0 KB

SKILL.md(原文)

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wiki-arsenal

The fast, wiki-first lookup engine for "what do I use against this surface". Runs the four knowledge areas in parallel so a deep lookup is one wall-clock, not four serial reads. arsenal delegates here; the hunt-* skills each carry their own wiki-first qmd_query (MCP-independent) and can hand off here for a fast parallel lookup. Never hand-roll from memory when the wiki has the answer.

Input: a surface, service, or vuln-class (e.g. Jenkins on 8080, SSRF, Kerberoasting).

0. Cache check first (0 tokens on a repeat)

Slug the surface (lowercase, non-alnum -> -). If targets/<active-eng>/arsenal/<slug>.md exists, read and return it. Do not re-spend. (<active-eng> = the dir named in targets/active.md.)

Mode: quick (DEFAULT - fire it constantly)

One mcp__wiki-search__qmd_query over the whole index (add a qmd_search keyword pass when the surface is an exact product/CVE string). Group the hits under the four areas and return each as path -> one-line snippet:

  • Techniques (wiki/techniques/)
  • Payloads (wiki/payloads/)
  • Tools (wiki/tools/)
  • Cheatsheets (wiki/cheatsheets/)

Cost ~1-2k tokens, no subagents. This is what arsenal calls by default and what you fire on every new surface to raise wiki coverage cheaply. Stop here unless the surface is worth deep prep.

Mode: deep (opt-in - "deep"/"full arsenal", or a whole service/target worth prepping)

Dispatch FOUR parallel subagents in a SINGLE message (Agent tool), one per area, with model: haiku - each only reads its area and distils a card, which a lightweight model does well at a fraction of the cost (a full-model fan-out measured ~170k tokens; haiku cuts that hard). Each is told to search only its area, read the top 2-3 matching pages, and return a compact ready-to-use card for its area ONLY (nothing else), citing the page paths it used:

AgentSearchesReturns
toolswiki/tools/the automated tool(s) to run + the exact command line
payloadswiki/payloads/ready-to-send payloads for the vuln-class
techniqueswiki/techniques/the attack steps / chain
cheatsheetswiki/cheatsheets/quick copy-paste commands

Each agent scopes its search to its area: pass a path filter to qmd, or query the whole index and keep only wiki/<area>/ hits, then read those pages. The pages an agent reads stay in that agent's context and are discarded; you ingest only its card.

Merge the four returned cards into one arsenal card, four labelled sections plus a final Sources: line listing every page used.

Persist the deep card

Write the merged card to targets/<active-eng>/arsenal/<slug>.md (create the dir on demand) with frontmatter surface: and generated:. That is the cache step 0 reads next time.

Guardrails (token control)

  • Default is quick (~1-2k tokens). Only go deep on request or for a real service/target.
  • Deep is bounded: exactly 4 agents on model: haiku, each capped to the top 2-3 pages. The cost is isolated to the subagents; your main context only gains the merged card.
  • The cache prevents re-spend on the same surface.

Hand off

The full class-specific methodology lives in the matching hunt-* skill. After the arsenal card, hand off to it (e.g. Skill(hunt-ssrf)) for the actual exploitation loop.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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coverage

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Show per-asset vuln-class coverage gaps for the active engagement so nothing in scope is skipped. Use when asked "coverage", "what haven't we tested", "test gaps", "are we thorough", or before calling an engagement done.

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