yi-john-huang

yi-john-huang / openclaw-secure-stack

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🔒 One-command secure OpenClaw deployment with built-in skills scanner and prompt injection protection

42
7
100% credibility
Found Feb 02, 2026 at 19 stars 2x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A protective layer for the OpenClaw AI agent that adds user authentication, skill safety checks, input cleaning, action reviews, and message handling from chat apps without altering the original software.

How It Works

1
🔍 Discover OpenClaw

You hear about OpenClaw, a smart AI helper that runs skills on your computer, but worry about keeping it safe from bad tricks.

2
📥 Get the Secure Wrapper

You download the secure stack that wraps OpenClaw in safety layers like checks and guards, without changing the original.

3
🛠️ Run Easy Setup

You follow the simple guide to prepare everything, connecting your AI thinking service so it can respond smartly.

4
🚀 Launch Your Assistant

With one easy action, you start your protected AI helper, and it comes alive on your machine.

5
💬 Chat Safely

You talk to your AI through a secure chat, knowing prompts are cleaned and risky actions are reviewed.

6
🛡️ Add Trusted Skills

You check new skills for dangers before using them, quarantining bad ones automatically.

✅ Enjoy Secure AI

Your AI helper works powerfully and safely, handling messages from apps like chat services with full protection.

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AI-Generated Review

What is openclaw-secure-stack?

This Python-based Docker stack delivers one-command deployment for OpenClaw, wrapping the unmodified AI agent in a secure proxy that blocks risks like malicious skills and prompt injection. You get built-in skills scanner using AST analysis to quarantine dangerous code, prompt protection via regex sanitization, pre-execution governance with human approval gates, network isolation through DNS allowlisting, and full audit logging—all without touching OpenClaw itself. Run `./install.sh`, add your LLM keys, and access a hardened `/v1/chat/completions` API endpoint with Bearer token auth.

Why is it gaining traction?

It stands out by securing OpenClaw for self-hosting without code changes, tackling real threats like skill exfiltration or indirect injections that generic proxies miss. Developers dig the comprehensive pipeline—auth, scanning, governance, and Telegram/WhatsApp webhooks with replay protection and rate limiting—plus offline skill scanning CLI for pre-deploy checks. Zero-config hardening like read-only containers and non-root users makes production deployment feel production-ready.

Who should use this?

AI engineers or DevOps folks self-hosting OpenClaw for internal tools, especially those integrating agent skills via webhooks from chat apps. Teams evaluating production AI agents needing compliance audit trails or approval workflows for high-risk actions like file writes or code execution. Not for casual tinkering—ideal if you're bridging LLM APIs with real-world tools securely.

Verdict

Grab it if you're deploying OpenClaw securely; the one-command installer and detailed docs lower the barrier despite 26 stars and 1.0% credibility score signaling early maturity. Solid tests and security audit script show promise, but watch for upstream OpenClaw updates.

(198 words)

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