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CC performing-hash-cracking-with-hashcat

Cracks password hashes with Hashcat, covering hash-type identification, dictionary/brute-force/rule-based attack modes, custom rule creation, GPU benchmarking, and password-strength/compliance reporting. Use for authorized penetration testing or security audits that need to evaluate password strength or crack captured hashes.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 8 files · 2 scripts body ≈ 727 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Cracks password hashes with Hashcat, covering hash-type identification, dictionary/brute-force/rule-based attack modes, custom rule creation, GPU…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureSecuritytype 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%
71
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Risky intent intent-offensive-security references/standards.md:30
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - Follow penetration testing rules of engagement
    • low Risky intent intent-offensive-security SKILL.md:5
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      and password-strength/compliance reporting. Use for authorized penetration testing
    • low Risky intent intent-offensive-security SKILL.md:31
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      Hash cracking is an essential skill for penetration testers and security auditors to evaluate password strength. Hashcat is the world's fastest password recovery tool, supporting over 300 hash types w
      detector
    • low Risky intent intent-offensive-security SKILL.md:87
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      - Follow rules of engagement for penetration test scope
      detector

    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"
    • note edit-residue the text marks something as outdated (lines 47, 48): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 51/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 26 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 727 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +4No input/output examples
    • -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 327: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 26 items
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.