ClamBot: AI Agent Runs LLM-Generated Code in WASM Sandbox for Security

What ClamBot Does
ClamBot is an AI agent framework that addresses security concerns with existing agent frameworks by running all LLM-generated code in a WebAssembly sandbox instead of using exec() or subprocess calls. The creator built it after trying frameworks that execute arbitrary code directly on the host machine, citing examples like LangChain having a CVE for this approach, AutoGen shelling out with subprocess, and SWE-Agent running bash commands from the model.
Technical Implementation
ClamBot is built on top of amla-sandbox, a WASM sandbox that uses QuickJS in Wasmtime. The LLM writes JavaScript code that runs in a memory-isolated sandbox with zero network access. Every tool call (HTTP, filesystem, cron) must pass through an approval gate back in Python. No Docker or VM is required - it runs as one binary.
Key Features
- Sandbox Security: All code runs in WASM - cannot touch host memory or network
- Approval Gate: SHA-256 fingerprinted approval gate on every tool call with pre-approve patterns (e.g., "allow web_fetch for api.coinbase.com")
- Clam Reuse: Successful scripts get saved as "clams" and can be reused, reducing API costs for repeated requests
- Multi-Provider Support: OpenRouter, Anthropic, OpenAI, Gemini, DeepSeek, Groq, Ollama
- Telegram Integration: Telegram bot with inline approval buttons
- Additional Features: Persistent memory, cron scheduling, SSRF protection that blocks private IPs, secrets never appear in logs/tool args/traces
Example Workflow
User asks: "what are the top movers on binance?" The sandbox executes JavaScript → makes http_request to Binance API → goes through approval gate → returns result. The bot responds with the top 10 movers on Binance by 24h change.
Getting Started
bash git clone https://github.com/clamguy/clambot.git
cd clambot
uv run clambot onboard
uv run clambot agentStack and Scale
The project is built with Python + QuickJS/Wasmtime, contains approximately 10K lines of code, and was inspired by OpenClaw and nanobot. The creator built it because they wanted "an AI agent I could actually trust on my server."
📖 Read the full source: r/openclaw
👀 See Also

free-claude-code adds GLM-5 support via NVIDIA NIM, expands to OpenRouter and Discord
free-claude-code now supports GLM-5 through NVIDIA NIM's free tier (40 requests/min) and adds OpenRouter integration, Discord bot support, and LMStudio local provider compatibility. The tool converts Claude Code's Anthropic API requests to work with alternative model backends.

OpenClaw Janitor Skill for Automated System Management and Security Hardening
A developer created a skill that uses Claude Code to SSH into OpenClaw machines and harden configurations, including sandboxing, OS hygiene, and channel security, while maintaining a project folder with audit instructions in CLAUDE.md.

Two New Open Source Tools for AI Agent Security and Optimization
Two open source tools are available for AI agent developers: AI Agent Defense Kit provides runtime security skills, and AgentGuard (in development) offers cost tracking, security scanning, and activity monitoring.

Agent Factory: Autonomous System Builds AI Agents from Online Problem Discussions
Agent Factory is an autonomous system that scrapes Reddit, HN, GitHub, and Twitter for real problems, scores them on demand, market gap, and feasibility, then builds standalone AI agents for promising ideas. The system uses a minimal Next.js template with 7 tools and runs Claude Code headless via a shell script.