Skill flagged — suspicious patterns detected
ClawHub Security flagged this skill as suspicious. Review the scan results before using.
Doc Collaboration Watcher
v1.6.0实时监控指定协作文档变更,自动通过飞书、微信、iMessage和WebChat通知相关代理并跟踪确认与响应状态。
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byLewis&Eva@lewistouchtech
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
Name/description (document change watcher + multi-channel notification) align with included files and declared permissions (file read/write, message:send). The single Python script and no external downloads are reasonable for the stated functionality.
Instruction Scope
SKILL.md / README and bin/doc-watcher.py instruct the skill to automatically read ~/.openclaw/config/openclaw.json and to use enabled channels from the user's OpenClaw config. Reading that config is functionally relevant, but SKILL.md/README present 'zero-config' behavior without clearly warning users that local channel configurations (which often hold tokens/credentials) will be read and used. The repo also contains a PUBLISH.md example that embeds a CLAWHUB token string (clh_RVZ_...), which could be a real token or a sensitive placeholder — storing tokens in repo files is a risk. Additionally the runtime script prints local file:// paths in notifications (exposes local paths) and the main loop uses while True: pass (a busy spin), which is a bug/operational concern.
Install Mechanism
No network downloads or arbitrary installers; install is manual (git clone + pip install watchdog). No extracted archives or remote binaries. This is low risk from an install mechanism perspective.
Credentials
The skill declares no required env vars, which is reasonable, but it silently reads the user's OpenClaw config to discover channels. OpenClaw channel configs commonly contain credentials/tokens for messaging integrations; the skill doesn't declare that it will access these secrets, nor does SKILL.md ask the user to review or approve that access. The presence of a CLAWHUB token-like string in PUBLISH.md increases the concern about sensitive data handling in the repo.
Persistence & Privilege
Skill is not always-enabled, does not request platform-wide persistence, and does not modify other skills' configuration. It writes its own log/history under the workspace logs which is expected for this kind of tool.
What to consider before installing
Plain-language checklist before installing/enabling:
- Review your OpenClaw config (~/.openclaw/config/openclaw.json). It will be read automatically and may contain channel credentials (tokens, API keys). Only enable this skill if you are comfortable it can access and use your configured channels.
- Inspect the repo files (especially PUBLISH.md and other docs) for any accidentally committed tokens/keys. The PUBLISH.md contains a CLAWHUB_TOKEN-like string — treat it as sensitive until confirmed otherwise; do not assume it's harmless.
- The current Python script prints notification info and contains a TODO for real message sending; verify the implementation that actually sends messages before enabling in production. Confirm which channels will receive notifications and whether messages may expose local paths (the notifications include file:// links to local files).
- Run the watcher in a sandbox or a test workspace first (not your main workspace). Create test .md files and confirm behavior (and that it doesn't leak data externally).
- Fix or be aware of the busy-loop in main (while True: pass) which will consume CPU; modify to sleep or use a proper event loop before long-running use.
- If you need stricter control, require explicit config (disable 'auto_channels') so the skill only uses channels you specify, or whitelist channels it may use.
If you want, I can:
- Point to the exact lines in files that read the OpenClaw config and show what fields to look for in your openclaw.json,
- Suggest a small patch to replace the busy-loop with a safe sleep, and
- Help redact or rotate any tokens found in the repository.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
