CC performing-log-analysis-for-forensic-investigation
Collect, parse, and correlate system, application, and security logs to reconstruct events and establish timelines during forensic investigations.
Collect, parse, and correlate system, application, and security logs to reconstruct events and establish timelines during forensic investigations.
As a process C 64/100 · Has gaps — weak spots: when it triggers, failures and branches
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 · 7
✓ No critical or high findings
Medium and low: 7
-
low Risky intent
intent-offensive-securityreferences/api-reference.md:18Offensive-security / dual-use content (legitimate for authorised testing; review intended use)| 4648 | Explicit credentials | Lateral movement indicator |
-
low Risky intent
intent-offensive-securityreferences/api-reference.md:28Offensive-security / dual-use content (legitimate for authorised testing; review intended use)| `/var/log/auth.log` | SSH, sudo, su | Failed/successful SSH, privilege escalation |
-
low Risky intent
intent-offensive-securitySKILL.md:33Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- During post-breach investigation to identify initial access, lateral movement, and exfiltration
-
low Risky intent
intent-offensive-securitySKILL.md:105Offensive-security / dual-use content (legitimate for authorised testing; review intended use)# 4648 - Logon using explicit credentials (runas, lateral movement)
-
low Risky intent
intent-offensive-securitySKILL.md:220Offensive-security / dual-use content (legitimate for authorised testing; review intended use)# Look for lateral movement patterns
-
low Risky intent
intent-offensive-securitySKILL.md:246Offensive-security / dual-use content (legitimate for authorised testing; review intended use)2. Privilege Escalation: [timestamp] - New admin account created
-
low Risky intent
intent-offensive-securitySKILL.md:247Offensive-security / dual-use content (legitimate for authorised testing; review intended use)3. Lateral Movement: [timestamp] - Pass-the-hash detected across 3 systems
Files scanned: 4. 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 64/100
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 11 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3024 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)
- -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 146: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 11 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.