SKILLEMALL.ai
GitHub ↗ RU Sign in

CC AWS Penetration Testing

This skill should be used when the user asks to "pentest AWS", "test AWS security", "enumerate IAM", "exploit cloud infrastructure", "AWS privilege escalation", "S3 bucket testing", "metadata SSRF", "Lambda exploitation", or needs guidance on Amazon Web Services security assessment.

davila7/claude-code-templates Agent Skills author: davila7 MIT 2 files body ≈ 2 383 tokens Open the sourcegithub.com↗ analyzed 6 d ago

This skill should be used when the user asks to "pentest AWS", "test AWS security", "enumerate IAM", "exploit cloud infrastructure", "AWS privilege…

As a process C 59/100 · Has gaps — weak spots: result and completion, consistency, running it twice

ProcedureAWSGitHubInfrastructuretype 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%
89
Quality 40%
88
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
40
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: RA-Skills

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 · 11

    ✓ No critical or high findings

    Medium and low: 11
    • low Risky intent intent-offensive-security references/advanced-aws-pentesting.md:1
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (test fixture / example file)
      # Advanced AWS Penetration Testing Reference
      fixture
    • low Risky intent intent-offensive-security references/advanced-aws-pentesting.md:12
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (test fixture / example file)
      - [VPC Enumeration & Lateral Movement](#vpc-enumeration--lateral-movement)
      fixture
    • low Risky intent intent-offensive-security references/advanced-aws-pentesting.md:383
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (test fixture / example file)
      ## VPC Enumeration & Lateral Movement
      fixture
    • low Risky intent intent-offensive-security references/advanced-aws-pentesting.md:416
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (test fixture / example file)
      ### Lateral Movement via VPC Peering
      fixture
    • low Risky intent intent-offensive-security SKILL.md:2
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      name: AWS Penetration Testing
    • low Risky intent intent-offensive-security SKILL.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      description: This skill should be used when the user asks to "pentest AWS", "test AWS security", "enumerate IAM", "exploit cloud infrastructure", "AWS privilege escalation", "S3 bucket testing", "meta
      quoted
    • low Risky intent intent-offensive-security SKILL.md:9
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # AWS Penetration Testing
    • low Risky intent intent-offensive-security SKILL.md:13
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction
    • low Risky intent intent-offensive-security SKILL.md:25
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - IAM privilege escalation paths
    • low Secrets in code secret-high-entropy-token SKILL.md:117
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      TOKEN=$(curl -X PUT -H "X-aw…ds: 21600" \
      quoted
    • low Exfiltration net-credential-use SKILL.md:121
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -H "X-aw…en:$TOKEN" \
      security skill

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 59/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 4 mutating operations with no state check
    • 40Consistency. Frontmatter name (AWS Penetration Testing) differs from the folder (aws-penetration-testing)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web, git, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 19 steps
    • 100Execution cost. Instruction body is 2383 tokens
    • 100Progress reporting. Reports progress
    • low 17 top-level sections: this looks like several domains in one skill

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 283: enough signal without eating the budget
    • +4Structure: 33 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (20 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.