What is Aegisora?
Aegisora is a runtime security and execution control layer for autonomous AI agents. It sits at the execution boundary of autonomous systems, so every sensitive action an agent proposes is evaluated against context, policy, risk and authorization before it reaches the real environment.
How it works
Aegisora models the path from intent to consequence as eight stages:
- Request — an agent proposes an action against a tool, system or resource, producing a request record.
- Context — workspace, identity, access and environment are resolved, and security analysis runs on the request.
- Policy — the applicable policy is evaluated against the request.
- Risk — a risk level (LOW, MEDIUM, HIGH or CRITICAL) is assessed from the action and its context.
- Decision — the outcome is resolved as ALLOW, BLOCK or ESCALATE.
- Enforcement — the execution gate opens, stops or pauses.
- Execution — the action runs in the environment, or it does not.
- Evidence — the decision chain is recorded for audit.
Key capabilities
- Runtime execution boundary — control what agents are allowed to do before actions execute.
- Policy engine — evaluate requests against configurable policies.
- Risk assessment — grade actions by risk level using action and context.
- Approvals and escalation — pause sensitive actions for human review.
- Evidence and audit — record decision chains with evidence and audit IDs.
- Developer resources — SDKs, integration guides, API reference and versioned documentation.
Who it is for
Teams building or operating autonomous AI agents that need governance over sensitive actions, with policy enforcement, risk-based decisions and auditable evidence at the point of execution.