Burrow – Runtime Security for AI Agents
Natural language policies block risky agent actions before they execute.

Code-based rules beat AI monitoring AI for actual enforcement guarantees.
Developers building production AI agents with LangChain, CrewAI, or AutoGen
Credo AI · Arize Phoenix · LangSmith
So we built Faramesh.
It intercepts tool calls before they execute, evaluates them against a declarative policy, blocks or approves, and logs everything. Works with LangChain, CrewAI, AutoGen, MCP, LangGraph. Open source, no signup. You can clone it and have it running against your agent in a few minutes.
The OpenShell announcement from NVIDIA this week is a good reference point for where Faramesh fits. OpenShell handles what the agent can reach. Faramesh handles what the agent is allowed to do once it gets there. Different layers.
Would love feedback from anyone running agents in production, especially where you've hit cases where access controls weren't enough.
github.com/faramesh-labs/faramesh -- faramesh.dev
Natural language policies block risky agent actions before they execute.
Eight-layer governance pipeline for agents when LangChain just executes blindly.
Zero-trust governance for AI agents before they execute shell, file, or database actions with full audit trails.
Kernel interception stops runaway agents where LangGraph and AutoGen only advise.
Local rule engine blocks AI agents from nuking prod when prompts fail.
OPA policies plus signed tokens beat prompt engineering for agent safety.