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CC clawwall

Outbound DLP for OpenClaw — hard regex blocks secrets & PII from leaving the machine. Domain control, no LLM.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Stan Liu v0.3.0 16 files · 1 script body ≈ 1 191 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerGitHubAI and agentsData and analyticstype 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
C
73/100
safety, quality, tests
Safety 60%
77
Quality 40%
66
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: clawwall (ClawHub)

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 6

  • high Dangerous commands cmd-persistence setup.sh:279
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl load "$PLIST_FILE" 2>/dev/null || true
Medium and low: 5
  • low Secrets in code secret-high-entropy-token hooks/openclaw/package-lock.json:42
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…wQp+7C4n…9JQ==",
    detector
  • low Secrets in code secret-high-entropy-token plugin/package-lock.json:42
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…w6M+uprW…rLY/w==",
    detector
  • low Dangerous commands cmd-background-process setup.sh:286
    Starts a background / autostarted process
    nohup clawwall > "$CLAWWALL_CONFIG_DIR/clawwall.log" 2>&1 &
  • low Dangerous commands cmd-background-process setup.sh:289
    Starts a background / autostarted process
    nohup python3 -m clawguard > "$CLAWWALL_CONFIG_DIR/clawwall.log" 2>&1 &
  • low Secrets in code secret-aws-key SKILL.md:64
    AWS access key ID (placeholder value)
    -d '{"content": "key=AKIA…PLE"}'
    placeholder

Files scanned: 16. 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")
  • note frontmatter-key unknown frontmatter key "openclaw"

Process rating: all ten parameters 57/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (clawwall) differs from the folder (clawguard-skill)
  • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 8 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Execution cost. Instruction body is 1191 tokens
  • 100Progress reporting. Reports progress

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)
  • +3Description length 109: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 8 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
ClawWall is a disclosed local DLP tool, but its defaults can expose the scanner on the network and allow sensitive outbound data to bypass protection.
LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026