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BC aoi-openclaw-security-toolkit-core

Fail-closed OpenClaw security toolkit (public-safe). Use to prevent accidental or unexpected data leakage by running local-only checks: default-deny allowlists, lightweight secret/token scans, egress-risk pattern scans, and prompt/document injection pattern scans. Use when preparing GitHub/ClawHub publishing, reviewing skills/scripts for risky behavior, or validating inbound text/doc content before tool execution.

ClawHub Agent Skills author: edmonddantesj v0.1.6 10 files body ≈ 310 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerGitHubInfrastructureAI and agentstype 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
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
78
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Risky intent medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.

For the author

Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Risky intent intent-wallet-secrets rules/prompt_injection_patterns.txt:9
      Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
      api key|token|password|private key|seed phrase|mnemonic

    Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Fail-closed OpenClaw security toolkit (public-safe). Use to preven… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 56/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 4 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 310 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
    • +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
    • +3Description length 417: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 12 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (3 of 4)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

    External checks

    ClawHub: clean
    This is a local security-scanning CLI whose file reads, Git checks, and optional local reports match its stated purpose, with no evidence of exfiltration or automatic remediation.
    LLM: benign (high) · VirusTotal: suspicious · 28 May 2026