Webcam Motion Monitor

Webcam motion detection and monitoring system for WSL2 with USB/IP passthrough. Use when setting up motion detection on a USB webcam, monitoring camera snaps...

What to check before installing or running this skill: - Do not run it blindly as root. Run as a normal user and inspect the files yourself. - Fixable bugs: snapshot.sh points to motion_detector.py which doesn't exist, and motion detector script lacks a --snapshot CLI; the web preview docstring references port 8080 but server uses 8081. Expect to edit/fix these if you rely on the helper scripts. - Network exposure: web_preview.py binds the HTTP server to 0.0.0.0. If you only want localhost access, change server address to ('127.0.0.1', 8081) or ensure your host firewall prevents external access. Test reachability from other hosts before trusting privacy. - Privacy: the skill encourages storing descriptive person-identification data (MEMORY.md) and queues images for AI analysis. Consider whether you have consent to capture and analyze people on camera. Review and limit retention (MAX_AGE_HOURS / CLEANUP_INTERVAL) and location of saved images. - Image analysis ambiguity: SKILL.md mentions using an 'image tool' and the 'qwen' model but provides no details about where that runs (local vs external) or required credentials. Confirm how analysis will be performed and whether any external API calls or credentials are needed before enabling automatic analysis. - Run initially in a controlled environment (air-gapped VM or isolated WSL instance) to validate behavior and to patch the small inconsistencies. If you accept those issues and restrict network access to the web server, the code otherwise appears to implement the declared functionality rather than exfiltrate data.

Type: OpenClaw Skill Name: webcam-monitor Version: 1.0.3 The skill bundle implements a webcam surveillance system that includes unauthenticated remote streaming and automated person identification. It is classified as suspicious because `web_preview.py` binds a live camera feed to `0.0.0.0:8081` without any authentication, exposing the user's environment to the local network. Furthermore, `SKILL.md` and `watcher_with_cleanup.py` contain highly specific instructions and hardcoded references for identifying individuals (e.g., 'Jade', 'Sarah') based on intrusive personal descriptions (clothing, jewelry, bathrobes), which aligns with the patterns of stalkerware or unauthorized monitoring.