knostic

knostic / openclaw-detect

Public

Detection scripts for MDM deployment to identify OpenClaw installations on managed devices.

www.knostic.ai moltbot openclaw security security-scanner security-tools
66
9
100% credibility
Found Feb 03, 2026 at 19 stars 3x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Shell
AI Summary

Lightweight scripts that detect OpenClaw installations on macOS, Linux, and Windows devices for easy deployment in device management systems.

How It Works

1
💡 Discover the checker

You hear about a handy tool that helps spot if OpenClaw is hiding on work computers.

2
📖 Read the guide

Visit the simple instructions to understand how it quietly checks devices without fuss.

3
💾 Get the checker

Download the easy checker program that matches your computer's system.

4
🔍 Run the scan

Launch the checker on a computer and it quickly looks for signs of OpenClaw.

5
See the results
✅
All clear

No OpenClaw detected – everything is clean and safe.

⚠️
Found it

OpenClaw is there – now you can decide what to do next.

🎉 Stay in control

Your devices are now monitored, keeping work computers secure and compliant.

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Star Growth

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AI-Generated Review

What is openclaw-detect?

Shell and PowerShell scripts that scan macOS, Linux, and Windows devices for OpenClaw installations, spotting CLI binaries, app bundles, state directories, config files, gateway services on ports like 18789, and Docker artifacts. Built for MDM tools like Jamf, Intune, and JumpCloud, they output detailed summaries and use exit codes—0 for not installed (clean), 1 for detected (non-compliant), 2 for errors—to flag issues in custom detection scripts intune or SCCM detection scripts. Run via curl for quick deployment detect checks, with env vars for custom profiles and ports.

Why is it gaining traction?

Cross-platform coverage and root-mode multi-user scans beat basic detection rules github tools, while MDM-specific guides for Intune detection scripts exit codes and Jamf Pro simplify rollout over generic anomaly detection github repos. Lightweight one-liners deliver user-facing outputs like "installed-and-running" with CLI versions and service details, hooking ops teams tired of manual intune detection remediation scripts.

Who should use this?

IT admins managing fleets with Intune app detection scripts or Jamf deployment policies. Security engineers enforcing detection and remediation scripts against unauthorized AI gateways. MDM operators at scale using JumpCloud or Workspace ONE for github detection as code in compliance workflows.

Verdict

Useful niche pick for OpenClaw-specific detection engineering, with strong docs offsetting 43 stars and 1.0% credibility score. Test in staging—mature enough for pilots, not yet battle-tested at scale.

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