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CB implementing-cloud-trail-log-analysis

Implementing AWS CloudTrail log analysis for security monitoring, threat detection, and forensic investigation using Athena, CloudWatch Logs Insights, and SIEM integration to identify unauthorized access, privilege escalation, and suspicious API activity.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 3 251 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Implementing AWS CloudTrail log analysis for security monitoring, threat detection, and forensic investigation using Athena, CloudWatch Logs Insights, and…

As a process B 65/100 · Nearly there — weak spots: failures and branches, running it twice

AnalyzerAWSSecurityAI and agentsPeople and hiringtype 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
89/100
safety, quality, tests
Safety 60%
93
Quality 40%
82
Run on models
none yet
Process rating
B
65/100
Nearly there
Failures and branches w 10
0
Running it twice w 4
30
When it triggers w 12
50
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 · 7

    ✓ No critical or high findings

    Medium and low: 7
    • low Risky intent intent-offensive-security references/api-reference.md:38
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | `AttachUserPolicy` / `PutUserPolicy` | Privilege escalation |
    • low Risky intent intent-offensive-security references/api-reference.md:41
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | `AuthorizeSecurityGroupIngress` | Lateral movement |
    • low Risky intent intent-offensive-security references/api-reference.md:42
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | `DisableKey` | Ransomware indicator |
    • low Risky intent intent-offensive-security SKILL.md:5
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      SIEM integration to identify unauthorized access, privilege escalation, and suspicious
    • low Risky intent intent-offensive-security SKILL.md:161
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      -- Find IAM privilege escalation attempts
    • low Risky intent intent-offensive-security SKILL.md:329
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Privilege escalation attempts:       12
    • low Risky intent intent-offensive-security SKILL.md:341
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      [CT-002] IAM Privilege Escalation

    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 65/100

    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 5 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 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. 22 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3251 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
    • -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
    • +4Description says when NOT to use the skill
    • +3Description length 255: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 22 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: 82.