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BD openclaw-security-audit

Security audit and credential hardening tool for OpenClaw instances. Scan for sensitive files, detect credential exposure, check gateway configuration, and migrate credentials to environment variables. Essential for maintaining a secure OpenClaw deployment.

ClawHub Agent Skills author: LuoLuo&Big-fish v1.0.0 MIT-0 9 files body ≈ 997 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, failures and branches

AnalyzerInfrastructuretype 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%
99
Quality 40%
73
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Failures and branches w 10
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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
  • low Dangerous commands cmd-shell-rc harden.py:264
    Writes to a shell startup file (string literal in code, not executed)
    echo "To make permanent, add to ~/.bashrc or ~/.zshrc"
    code literal

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 48/100

  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 40Consistency. Frontmatter name (openclaw-security-audit) differs from the folder (openclaw-safe-audit)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 44 steps
  • 100Execution cost. Instruction body is 997 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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

  • +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
  • +2Single-language instructions
  • +3Description length 257: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 44 items
  • +4Has examples (4 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
This is a local OpenClaw security tool with no external data transfer shown, but it handles real credentials and understates where those secrets are saved or persisted.
LLM: suspicious (high) · VirusTotal: · 29 May 2026