Original Summary

In practice, damage happens when an agent calls a tool: HTTP, email, DB, files, etc. A hidden instruction in a doc can push the agent to do something the user never asked for — and from the system’s point of view it can still look like a normal tool call. I built a small open pilot for that moment: What it does - Intercepts tool calls before they run - Checks intent + simple data provenance + policy - Returns ALLOW / BLOCK with a reason - Writes an audit log Stack - Risk engine (FastAPI) on localhost - Python SDK (verify_tool_call / decorator) - Optional MCP gateway (stdio) - Docker or pip What it is not - Not a prompt filter - Not a production / enterprise security product - Not a transparent proxy for every existing company agent - Policy is heuristic — tune it; it will not catch everything Try (local sandbox only) ```bash git clone https://github.com/aegotrax-dev/aegotrax.git cd aegotrax docker compose up --build # or: pip install ".[demo]" && agentguard-engine curl http://127.0.0.1:8000/health python examples/sdk_pilot_example.py Site: https://aegotrax.com If you run it, I’d genuinely like feedback: Docker or pip - did install work? Did you get a clear BLOCK in the example? What was confusing or wrong?   submitted by   /u/GameChacking [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/23 21:13:38