Topic starter
11/06/2026 10:44 pm
TL;DR: AI agent communication protocols such as MCP and A2A standardise how agents exchange requests, but leave authorization, revocation, and consent largely to implementers, creating broad-token and stale-permission risks, according to Authzed. That gap means agentic systems can scale faster than their governance model, with least privilege and lifecycle control becoming the limiting factors.
Editorial analysis by NHI Mgmt Group, based on content published by Authzed: “Agentic AI is not Secure”.
Key questions
Q: How should security teams govern AI agent authorization in distributed systems?
A: Security teams should govern AI agent authorization as a per-request decision problem, not a one-time entitlement.
Q: Why do AI agents need finer-grained access than standard OAuth scopes provide?
A: AI agents operate on specific tasks, resources, and timing windows, while standard OAuth scopes are usually too coarse to express that precision.
Q: What does revocation need to cover in agentic AI environments?
A: Revocation must cover the original credential, any cached authorization state, and any downstream delegates that inherited authority.
Practitioner guidance
- Define authorization outside the protocol layer Treat MCP and A2A as transport standards only.
- Replace broad scopes with task-scoped permissions Issue credentials that map to one task, one resource set, and one time window.
- Design revocation propagation as a distribution problem Verify that revoked permissions are removed from caches, peer systems, and downstream delegates, not just expired at the issuing service.
Bottom line: AI agent protocols can standardise communication while leaving authorization unresolved, which shifts the burden of control design onto identity teams.
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This topic was modified 1 day ago by NHI Mgmt Group
12/06/2026 7:02 am
Agent communication standardization is not authorization standardization: MCP, A2A, and similar protocols make agent interoperability easier, but they do not define who may do what, for how long, or under which revocation rules. That leaves security teams to solve the core governance problem at the policy layer, not the transport layer. The implication is that protocol adoption can accelerate deployment while leaving the identity model behind.
A few things that frame the scale:
- 53% of security leaders expect AI to run major portions of their infrastructure autonomously within the next three years, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: What is the difference between consent and authorization for AI agents?
A: Consent is the user’s approval of a request, while authorization is the policy decision about whether the request should be allowed. In agentic systems, a clear prompt does not guarantee safe access if the underlying token is broad, long-lived, or passed into a delegation chain without attenuation.
👉 Read our full editorial: Agent communication protocols leave authorization undefined for AI agents
This post was modified 1 day ago by NHI Mgmt Group