DC performing-linux-log-forensics-investigation
Perform forensic investigation of Linux system logs including syslog, auth.log, systemd journal (via journalctl), kern.log, auditd, and application logs to reconstruct user sessions, identify unauthorized access and privilege escalation, trace lateral movement, and establish event timelines. Use when investigating a suspected compromise of a Linux system and needing to analyze SSH, sudo, cron, or kernel-level activity from plain-text or systemd journal logs.
Perform forensic investigation of Linux system logs including syslog, auth.log, systemd journal (via journalctl), kern.log, auditd, and application logs to…
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
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
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- 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 · 6
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high Dangerous commands
cmd-destructive-fsreferences/api-reference.md:41Destructive filesystem command (wipes root/home/drive) (documentation of a security skill)| DESTRUCTIVE_COMMAND | rm -rf / |
security skill
Medium and low: 5
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medium Dangerous commands
cmd-persistenceSKILL.md:152Persistence mechanism (cron / launchd / scheduled task / autorun registry) (documentation of a security skill)cat /etc/crontab
security skill -
low Risky intent
intent-offensive-securitySKILL.md:5Offensive-security / dual-use content (legitimate for authorised testing; review intended use)to reconstruct user sessions, identify unauthorized access and privilege escalation,
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low Risky intent
intent-offensive-securitySKILL.md:6Offensive-security / dual-use content (legitimate for authorised testing; review intended use)trace lateral movement, and establish event timelines. Use when investigating a
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low Risky intent
intent-offensive-securitySKILL.md:41Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)Linux systems maintain extensive logs that serve as primary evidence sources in forensic investigations. Unlike Windows Event Logs, Linux logs are typically plain-text files stored in /var/log/ and bi
detector
A further 1 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 56/100
- 0Result and completion. Does not say what the result is
- 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
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 12 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2462 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)
- +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
- -31 of 2 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 462: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (5 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.