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CC hunt-misc

Hunting skill for misc vulnerabilities. Reference for authorized role, token and workflow-boundary reviews. Historical source count is not independently verified.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 1 file body ≈ 6 751 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Hunting skill for misc vulnerabilities.

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureGitHubGitLabShopifySecuritytype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
86/100
safety, quality, tests
Safety 60%
96
Quality 40%
72
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Running it twice w 4
30
Result and completion w 14
40
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: hunt-misc (sickn33/agentic-awesome-skills)

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 4

✓ No critical or high findings

Medium and low: 4
  • low Risky intent intent-offensive-security SKILL.md:35
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    MISC vulnerabilities span access control failures, information disclosure, session/auth logic bugs, and misconfiguration — the categories that consistently produce the highest payouts because they map
  • low Risky intent intent-offensive-security SKILL.md:38
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - **SaaS platforms with role hierarchies** (Shopify, GitHub, GitLab) — any boundary between owner/admin/staff/guest is a privilege escalation surface
  • low Risky intent intent-offensive-security SKILL.md:141
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    **Privilege escalation via invitation bypass:**
  • low Risky intent intent-offensive-security SKILL.md:276
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    **Scenario A — Privilege Escalation via Unverified Partner Invitation (Shopify-class)**

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6751 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "risk"
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "source_repo"
  • note frontmatter-key unknown frontmatter key "source_type"
  • note frontmatter-key unknown frontmatter key "date_added"
  • note frontmatter-key unknown frontmatter key "license_source"
  • note frontmatter-key unknown frontmatter key "sources"
  • note frontmatter-key unknown frontmatter key "report_count"
  • note edit-residue the text marks something as outdated (lines 185, 232, 317, 318): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 63/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 23 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6751 tokens
  • 100Steps. 87 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 12 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 162: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 87 items
  • +4Has examples (11 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.