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CC performing-timeline-reconstruction-with-plaso

Builds comprehensive forensic super-timelines using Plaso (log2timeline and psort) to correlate events across file system metadata, event logs, browser history, and registry artifacts into a unified chronological view. Use during complex forensic investigations that need cross-source event correlation, or when standard log analysis is insufficient to establish the sequence of activities for reporting findings.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 2 819 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Builds comprehensive forensic super-timelines using Plaso (log2timeline and psort) to correlate events across file system metadata, event logs, browser…

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

GeneratorDockerInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
96
Quality 40%
76
Run on models
none yet
Process rating
C
62/100
Has gaps
Failures and branches w 10
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Risky intent intent-offensive-security SKILL.md:284
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      **Scenario 1: Ransomware Attack Reconstruction**
    • low Risky intent intent-offensive-security SKILL.md:285
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Process the full disk image with Plaso, filter to the week before encryption was discovered, identify the initial access vector from browser history and event logs, trace privilege escalation through
    • low Risky intent intent-offensive-security SKILL.md:291
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Process disk images from all affected systems into a single Plaso storage file, import into Timesketch for collaborative analysis, search for lateral movement patterns across system timelines, identif
    • low Risky intent intent-offensive-security SKILL.md:327
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      2024-01-16 02:45 - Lateral movement to DC (Event Log)

    Files scanned: 4. 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 "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 62/100

    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (web) 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 2819 tokens
    • 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)
    • -2localhost URLs: will not work for another user
    • -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 413: 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: 76.