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analyzing-linux-kernel-rootkits

Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.

Quality

69%

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SecuritybySnyk

Medium

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Fix and improve this skill with Tessl

tessl review fix ./skills/analyzing-linux-kernel-rootkits/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content has a clear structure and names the right tools, but it omits executable command syntax, validation checkpoints for the forensic workflow, and any links to the bundled reference and script that would make it actionable. Wiring the existing bundle into the body and adding verification steps would raise every dimension.

Suggestions

Link references/api-reference.md from the Steps section so the actual 'vol -f ... <plugin>' command syntax is reachable, and replace the phantom 'rootkit_analyzer.py' example with the real scripts/agent.py or direct vol commands.

Add validation checkpoints to the workflow: verify the memory dump is complete (hash the evidence), confirm the ISF symbol table matches the target kernel before running plugins, and cross-check hidden-module findings across /proc, /sys, and Volatility before reporting.

Trim or condense the large fabricated Example Output block to reduce token weight without losing illustrative value.

DimensionReasoningScore

Conciseness

The body is mostly lean (tight overview, short steps, no padded concept explanations), but the ~65-line fabricated Example Output block consumes significant tokens without teaching procedure, fitting 'mostly efficient but could be tightened'.

3 / 5

Actionability

Steps name concrete plugins and tools, but the body lacks the actual 'vol -f ... linux.check_syscall' command syntax (which lives only in the unlinked reference) and the example invokes a 'rootkit_analyzer.py' script that is not in the bundle and is never defined, leaving key executable details missing.

3 / 5

Workflow Clarity

A clear four-step sequence is present, but for an evidence-handling/forensic workflow there are no validation checkpoints (dump integrity, ISF match confirmation, cross-check of findings), and the rubric caps such workflows at 3.

3 / 5

Progressive Disclosure

Sections are well-organized and a real references/api-reference.md and scripts/agent.py exist, but the body never links or signals them while the example references a non-existent rootkit_analyzer.py, so navigation to the bundled detail is missing.

3 / 5

Total

12

/

20

Passed

Description

75%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific and distinct with strong natural trigger keywords, but it omits any explicit 'when to use' guidance, which caps completeness. Adding a 'Use when...' clause would lift the weakest dimension.

Suggestions

Add an explicit trigger clause such as 'Use when investigating Linux memory dumps for kernel rootkits, hidden modules, or hooked syscalls' to satisfy the 'when' half of completeness.

Include common synonyms or file extensions users might say (e.g., 'memory forensics', '.lime dumps', 'LKM rootkits') to round out trigger-term coverage.

DimensionReasoningScore

Specificity

Lists multiple concrete actions with named tools and outcomes — 'Detect kernel-level rootkits', 'Volatility3 linux plugins (check_syscall, lsmod, hidden_modules)', 'rkhunter system scanning', '/proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures' — matching the comprehensive-coverage anchor.

5 / 5

Completeness

The 'what' is clear and concrete, but there is no 'Use when...' clause or equivalent explicit trigger guidance, so per the rubric guideline completeness is capped at 3.

3 / 5

Trigger Term Quality

Strong natural keywords (rootkits, Linux memory dumps, Volatility3, rkhunter, hooked syscalls, hidden kernel modules) that analysts would say, but common synonyms and conversational trigger variants are missing, fitting 'good keyword coverage; a few natural terms missing'.

4 / 5

Distinctiveness Conflict Risk

A clearly defined niche (Linux kernel rootkits via Volatility3 memory forensics and rkhunter) with distinct triggers and minimal overlap with other skills.

5 / 5

Total

17

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

mukul975/Anthropic-Cybersecurity-Skills

Path

skills/analyzing-linux-kernel-rootkits/SKILL.md

Reviewed

Table of Contents

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