CC performing-endpoint-forensics-investigation
Performs digital forensics investigation on compromised endpoints including memory acquisition, disk imaging, artifact analysis, and timeline reconstruction. Use when investigating security incidents, collecting evidence for legal proceedings, or analyzing endpoint compromise scope. Activates for requests involving endpoint forensics, memory analysis, disk forensics, or incident investigation.
Performs digital forensics investigation on compromised endpoints including memory acquisition, disk imaging, artifact analysis, and timeline reconstruction.
As a process C 55/100 · Has gaps — weak spots: result and completion, failures and branches, progress reporting
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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.
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
- 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 · 8
✓ No critical or high findings
Medium and low: 8
-
medium Dangerous commands
cmd-persistencescripts/agent.py:89Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)r"HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Run",
code literal -
medium Dangerous commands
cmd-persistencescripts/agent.py:90Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)r"HKCU\SOFTWARE\Microsoft\Windows\CurrentVersion\Run",
code literal -
low Risky intent
intent-offensive-securityassets/template.md:33Offensive-security / dual-use content (legitimate for authorised testing; review intended use)| Lateral movement | | | |
-
low Risky intent
intent-offensive-securityreferences/workflows.md:22Offensive-security / dual-use content (legitimate for authorised testing; review intended use)├── Malware analysis (if samples found)
-
low Risky intent
intent-offensive-securitySKILL.md:217Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Lateral movement
A further 3 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-keyunknown frontmatter key "domain" - note
frontmatter-keyunknown frontmatter key "subdomain" - note
frontmatter-keyunknown frontmatter key "nist_csf" - note
frontmatter-keyunknown frontmatter key "mitre_attack"
Process rating: all ten parameters 55/100
- 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
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 20 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1849 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
- +3Output format is not stated: the model decides each time
- -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
- +4Description says when NOT to use the skill
- +3Description length 396: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (8 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.