We built Aegisora 2.0 — an execution security layer for AI agents

AI agents are moving from generating text to actually taking actions — calling APIs, using tools, accessing data, and executing workflows.

That creates a problem: model-level safety isn't enough when an agent can directly affect real systems.

We built Aegisora 2.0, an open-source runtime security layer that puts security and policy enforcement directly in the execution path of AI agents.

Every action can be evaluated and allowed, blocked, or escalated before execution, with the decision and execution lifecycle recorded for auditability.

The core idea is simple:

Don't just secure the model. Secure what the agent is allowed to do.

We're building Aegisora for developers building autonomous agents, agentic workflows, and AI infrastructure.

GitHub:
https://github.com/aegisora-ai/aegisora

Release:
https://github.com/aegisora-ai/aegisora/releases

We're especially interested in feedback from people building production AI agents: Where do you currently enforce permissions, policies, and execution controls?