A Firewall for AI agents with auditing
Causal DAG tracking catches multi-step exfiltration that per-action security checks completely miss.
A causal firewall for AI agents: blocks multi-step tool-call chains that leak data, even when every call is individually allowed.
Causal enforcement catches multi-step exploits that per-action security misses.
AI agent developers, security engineers building agent systems
Lakera Guard · Protect AI · Portkey
Causal DAG tracking catches multi-step exfiltration that per-action security checks completely miss.
Agent firewall with 16+ injection patterns, sandboxed skill scanning, detects real OpenClaw CVE exposure.
Blocks credential leaks in agent output, not just dangerous input commands.
This feels like the first serious attempt to treat agent-to-agent chatter as a network security problem: 16+ prompt-injection signatures (with recursive base64 decoding), AST static analysis of skills via acorn/estree, and sandboxed dynamic checks are concrete, non-trivial defenses. The repo shows real engineering (Docker, CI, security scans, 181 tests) — the missing piece is real-world performance and adoption, but if you run agent fleets this is worth poking at.
Local firewall blocks agent credential leaks before they leave your machine.
Eight-layer governance pipeline for agents when LangChain just executes blindly.