SKILLEMALL.ai
GitHub ↗ RU Sign in

BC securing-aws-iam-permissions

Hardens AWS IAM configurations to enforce least-privilege access, covering IAM policy scoping, permission boundaries, IAM Access Analyzer integration, and credential rotation strategies. Use when reducing the blast radius of compromised AWS identities, auditing overly permissive IAM policies, or setting up permission boundaries and Access Analyzer findings review across cloud accounts.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 2 948 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Hardens AWS IAM configurations to enforce least-privilege access, covering IAM policy scoping, permission boundaries, IAM Access Analyzer integration, and…

As a process C 63/100 · Has gaps — weak spots: failures and branches, running it twice, progress reporting

ProcedureAWSGoogle CloudAzureInfrastructuretype 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
B
91/100
safety, quality, tests
Safety 60%
97
Quality 40%
82
Run on models
none yet
Process rating
C
63/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Risky intent intent-offensive-security SKILL.md:51
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      name: 'Brute Force: Password Spraying'
      quoted
    • low Risky intent intent-offensive-security SKILL.md:159
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Attach permission boundaries to IAM roles and users to define the maximum scope of permissions an entity can receive, preventing privilege escalation even if an administrator attaches an overly permis
    • low Risky intent intent-offensive-security SKILL.md:301
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      **Pitfalls**: Replacing policies without a parallel testing period causes service disruptions. Forgetting to scope Lambda:InvokeFunction to specific function ARNs leaves lateral movement paths open.
      detector

    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"
    • note frontmatter-key unknown frontmatter key "mitre_f3"

    Process rating: all ten parameters 63/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 7 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. 24 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2948 tokens
    • high The skill tells the model to perform an irreversible action with no human approval

    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 388: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 24 items
    • +3Output format is stated explicitly
    • +4Has examples (8 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.