SKILLEMALL.ai

CC collecting-volatile-evidence-from-compromised-host

Collect volatile forensic evidence from a compromised host by following the order of volatility, preserving memory, network connections, running processes, and system state with documented chain of custody before they are lost. Use before isolating, shutting down, or remediating a compromised host, especially when fileless or memory-resident malware is suspected, root cause analysis is needed, or the evidence must hold up in legal proceedings.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 8 files · 2 scripts body ≈ 2 234 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Collect volatile forensic evidence from a compromised host by following the order of volatility, preserving memory, network connections, running processes…

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

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
83/100
safety, quality, tests
Safety 60%
87
Quality 40%
78
Run on models
none yet
Process rating
C
62/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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 · 9

    ✓ No critical or high findings

    Medium and low: 9
    • medium Dangerous commands cmd-persistence references/api-reference.md:45
      Persistence mechanism (cron / launchd / scheduled task / autorun registry) (documentation of a security skill)
      ls -la /etc/cron.d/ >> /evidence/crontab.txt
      security skill
    • low Dangerous commands cmd-cron-mention references/api-reference.md:44
      Mentions editing / listing crontab (documentation of a security skill)
      crontab -l > /evidence/crontab.txt
      security skill
    • low Dangerous commands cmd-cron-mention references/workflows.md:78
      Mentions editing / listing crontab (documentation of a security skill)
      [ ] Cron: crontab -l, /etc/cron.*
      security skill
    • low Dangerous commands cmd-persistence scripts/agent.py:39
      Persistence mechanism (cron / launchd / scheduled task / autorun registry) (detector / deny-list definition; string literal in code, not executed)
      "tool_linux": ["crontab -l", "ls /etc/cron.d/"], "tool_windows": "schtasks /query /FO CSV /V"},
      detectorcode literal
    • low Dangerous commands cmd-cron-mention scripts/agent.py:39
      Mentions editing / listing crontab (detector / deny-list definition; string literal in code, not executed)
      "tool_linux": ["crontab -l", "ls /etc/cron.d/"], "tool_windows": "schtasks /query /FO CSV /V"},
      detectorcode literal
    • low Dangerous commands cmd-cron-mention SKILL.md:173
      Mentions editing / listing crontab (documentation of a security skill)
      crontab -l > "$EVIDENCE_DIR/crontab_current.txt" 2>/dev/null  # Linux
      security skill
    • low Risky intent intent-offensive-security SKILL.md:242
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      5. **Lateral Movement in Progress**: Attacker moving between systems. Authentication tokens and network sessions in memory reveal scope.

    A further 2 matches are quotations in this security skill's documentation and are not counted as findings.

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

    Process rating: all ten parameters 62/100

    • 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
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 24 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2234 tokens
    • 100Running it twice. No mutating operations

    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 447: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 24 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.