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CB performing-subdomain-enumeration-with-subfinder

Enumerate subdomains of target domains using ProjectDiscovery's Subfinder passive reconnaissance tool to map the attack surface during security assessments.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 8 files · 2 scripts body ≈ 1 601 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Enumerate subdomains of target domains using ProjectDiscovery's Subfinder passive reconnaissance tool to map the attack surface during security assessments.

As a process B 72/100 · Nearly there — weak spots: when it triggers, failures and branches

ProcedureGitHubAI and agentstype 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
87/100
safety, quality, tests
Safety 60%
93
Quality 40%
78
Run on models
none yet
Process rating
B
72/100
Nearly there
Failures and branches w 10
0
When it triggers w 12
20
Result and completion w 14
60
the three weakest of ten parameters · all ten

How to improve

    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 · 7

    ✓ No critical or high findings

    Medium and low: 7
    • low Risky intent intent-offensive-security references/standards.md:5
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - **PTES (Penetration Testing Execution Standard)** — Intelligence Gathering phase requiring comprehensive asset enumeration
    • low Risky intent intent-offensive-security references/standards.md:25
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - Bug bounty programs define specific scope for subdomain testing
    • low Risky intent intent-offensive-security references/workflows.md:19
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## Bug Bounty Recon Pipeline
    • low Risky intent intent-offensive-security references/workflows.md:20
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      1. Collect target domains from bug bounty program scope
      detector
    • low Risky intent intent-offensive-security SKILL.md:34
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - During the reconnaissance phase of penetration testing or bug bounty hunting
    • low Risky intent intent-offensive-security SKILL.md:38
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - During red team engagements requiring passive information gathering
    • low Risky intent intent-offensive-security SKILL.md:172
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      1. **Bug Bounty Reconnaissance** — Enumerate all subdomains of a target program scope to identify forgotten or misconfigured assets that may contain vulnerabilities

    Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "domain"
    • note frontmatter-key unknown frontmatter key "subdomain"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 72/100

    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 16 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1601 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    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)
    • -43 reference files, but SKILL.md never points to them: the model will not open them
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 156: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 16 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.