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BC hunt-misc

Hunting skill for misc vulnerabilities. Built from 225 public bug bounty reports. Use when hunting misc on any target.

elementalsouls/Claude-BugHunter Agent Skills author: elementalsouls 1 file body ≈ 5 830 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Hunting skill for misc vulnerabilities.

As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubGitLabShopifySoftware developmentData and analyticsSecuritytype 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
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
69
Run on models
none yet
Process rating
C
59/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Risky intent intent-offensive-security SKILL.md:3
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    description: Hunting skill for misc vulnerabilities. Built from 225 public bug bounty reports. Use when hunting misc on any target.
  • low Risky intent intent-offensive-security SKILL.md:11
    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:14
    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:117
    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:252
    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 ≈ 5830 tokens (recommended < 5000); move details to references/
  • 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 172, 219, 304, 305): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 59/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 22 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5830 tokens
  • 100Steps. 82 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 10 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)
  • +3Description length 118: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 82 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.