IronCurtain — Secure Runtime for AI Agents

Practical Notes

• Enforces policy at the boundary (not by trusting the model to follow instructions)
• Supports both a Docker-mediated mux mode and a builtin sandboxed mode (per README)
• GitHub stars/forks (verified): see Source & Thanks

When an agent is autonomous, the biggest failure mode isn’t “bad answer” — it’s uncontrolled side effects.

IronCurtain’s framing is useful even if you don’t adopt it fully:

• Assume the model is untrusted.
• Put enforcement outside the model (policy engine + controlled tool boundary).
• Make risky operations explicit and reviewable (writes, pushes, network calls).

A pragmatic adoption path:

1. Use the built-in agent mode first for small tasks.
2. Move to Docker-mediated mux mode when you want stronger isolation.
3. Treat policies as code: version them, review them, and keep a default-deny posture for mutations.

FAQ

Q: Is it a model or a wrapper? A: It’s a runtime/policy boundary that runs an agent and mediates tool calls.

Q: Do I need Docker? A: Docker is strongly recommended for the strongest isolation, but some modes run without it.

Q: What should I lock down first? A: Network access and write operations: make them explicit and require approval/escalation.