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BC auditing-kubernetes-cluster-rbac

Auditing Kubernetes cluster RBAC configurations to identify overly permissive roles, wildcard permissions, dangerous ClusterRoleBindings, service account abuse, and privilege escalation paths using kubectl, rbac-tool, KubiScan, and Kubeaudit.

ClawHub Agent Skills author: Chace v1.0.0 MIT-0 4 files body ≈ 3 054 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Auditing Kubernetes cluster RBAC configurations to identify overly permissive roles, wildcard permissions, dangerous ClusterRoleBindings, service account…

As a process C 58/100 · Has gaps — weak spots: failures and branches, consistency, running it twice

AnalyzerKubernetesSecuritytype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
94
Quality 40%
82
Run on models
none yet
Process rating
C
58/100
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 · 6

    ✓ No critical or high findings

    Medium and low: 6
    • low Risky intent intent-offensive-security skill-card.md:2
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      Audits Kubernetes RBAC configurations to identify overly permissive roles, wildcard permissions, dangerous bindings, service account exposure, and privilege escalation paths. <br>
      detector
    • low Risky intent intent-offensive-security SKILL.md:4
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ClusterRoleBindings, service account abuse, and privilege escalation paths using kubectl, rbac-tool, KubiScan, and Kubeaudit.
    • low Risky intent intent-offensive-security SKILL.md:33
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - When investigating potential lateral movement or privilege escalation within a Kubernetes cluster
    • low Risky intent intent-offensive-security SKILL.md:183
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # Check for privilege escalation paths
    • low Risky intent intent-offensive-security SKILL.md:184
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      python3 -m kubiscan -pe       # Privilege escalation vectors
      detector
    • low Risky intent intent-offensive-security SKILL.md:192
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Check for unnecessary service account token mounts that could enable lateral movement from compromised pods.

    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"

    Process rating: all ten parameters 58/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (auditing-kubernetes-cluster-rbac) differs from the folder (auditing-k8s-rbac)
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) 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
    • 100Execution cost. Instruction body is 3054 tokens

    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 242: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 22 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)
    • +1License stated

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

    External checks

    ClawHub: clean
    This is a Kubernetes RBAC audit skill that uses disclosed, mostly read-only cluster queries and a local report script, with the main caution being sensitive cluster-wide access.
    LLM: benign (high) · VirusTotal: · 28 May 2026