Show HN: ClawZero – execution boundary stops prompt injection exfil in OpenClaw

Most AI agents let the LLM run shell/API/fs with host privileges. Prompt injection = instant RCE. ClawZero adds a deterministic execution boundary between model output and tool execution. Try it yourself: pip install clawzero clawzero demo openclaw --mode compare --scenario shell Result: Standard OpenClaw → COMPROMISED ClawZero → BLOCKED Policy → mvar-security.v1.4.3 Witness → ed25519 signed artifact Attack path vs defense path diagram: https://raw.githubusercontent.com/mvar-security/clawzero/main/docs/assets/comparison.png https://raw.githubusercontent.com/mvar-security/clawzero/mai... Early release. Harness + OpenClaw simulation only — not yet tested end-to-end on live multi-turn agents in production. That's next. If you're running agents (LangChain, CrewAI, AutoGen, OpenClaw, etc.) and want to try it live: Open an issue or email shawn@mvar.io Happy to pair debug and share results. GitHub: github.com/mvar-security/clawzero Powered by MVAR: github.com/mvar-security/mvar Curious what people think about moving enforcement outside the model loop vs prompt filtering / LLM judges — especially if Jensen Huang drops something agent-related at GTC today ;)