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CC investigating-ransomware-attack-artifacts

Forensically preserve memory and disk, collect ransom notes and encrypted file samples, and identify the ransomware variant using tools such as ID Ransomware, Volatility, and Chainsaw/Hayabusa to determine the initial access vector and recovery options. Use immediately after discovering ransomware encryption, when scoping the incident forensically, or when documenting evidence for law enforcement and insurance claims.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 3 712 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Forensically preserve memory and disk, collect ransom notes and encrypted file samples, and identify the ransomware variant using tools such as ID Ransomware…

As a process C 62/100 · Has gaps — weak spots: when it triggers, failures and branches, running it twice

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
85/100
safety, quality, tests
Safety 60%
90
Quality 40%
78
Run on models
none yet
Process rating
C
62/100
Has gaps
Failures and branches w 10
0
When it triggers w 12
20
Running it twice w 4
30
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 · 10

    ✓ No critical or high findings

    Medium and low: 10
    • low Risky intent intent-offensive-security references/api-reference.md:1
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # API Reference: Investigating Ransomware Attack Artifacts
    • low Risky intent intent-offensive-security references/api-reference.md:7
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | `/api/v3/files/{hash}` | GET | Look up ransomware sample by MD5/SHA-256 |
    • low Risky intent intent-offensive-security references/api-reference.md:8
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | `/api/v3/files` | POST | Upload ransomware sample for analysis |
    • low Risky intent intent-offensive-security references/api-reference.md:11
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## ID Ransomware
    • low Risky intent intent-offensive-security references/api-reference.md:15
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (documentation table row)
      | `https://id-ransomware.malwarehunterteam.com/` | POST | Upload ransom note or encrypted sample for variant ID |
      table
    • low Risky intent intent-offensive-security SKILL.md:2
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      name: investigating-ransomware-attack-artifacts
    • low Risky intent intent-offensive-security SKILL.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      description: Forensically preserve memory and disk, collect ransom notes and encrypted file samples, and identify the ransomware variant using tools such as ID Ransomware, Volatility, and Chainsaw/Hay
    • low Risky intent intent-offensive-security SKILL.md:8
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - ransomware
    • low Risky intent intent-offensive-security SKILL.md:55
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # Investigating Ransomware Attack Artifacts
    • low Risky intent intent-offensive-security SKILL.md:58
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - Immediately after discovering ransomware encryption on systems

    Files scanned: 4. 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 frontmatter-key unknown frontmatter key "mitre_f3"

    Process rating: all ten parameters 62/100

    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 4 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3712 tokens
    • 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)
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 421: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 12 items
    • +3Output format is stated explicitly
    • +4Has examples (6 code blocks)
    • +1License stated

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