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Glossary

What is Enterprise-Managed Authorization?

A way for an organization’s identity provider to decide which AI agents and applications may access which other applications on a user’s behalf, instead of each user approving each connection. The client obtains an Identity Assertion JWT Authorization Grant (ID-JAG) from the identity provider and exchanges it for an access token at the target application. Okta calls the pattern Cross App Access, and MCP adopts it as its enterprise-managed authorization extension.

In depth

Enterprise-managed authorization moves the decision “may this agent access that application for this user?” from a consent screen in front of the user to the enterprise identity provider. It works in three steps. The user signs in to the AI client through the organization’s identity provider, as with any single sign-on. When the client needs to reach another application, it asks the identity provider, using OAuth token exchange, for an ID-JAG: a short-lived signed assertion naming the user, the client and the target application’s authorization server. The identity provider issues it only if its policy allows that client to reach that application for that user. The client then presents the ID-JAG to the target application’s authorization server as a JWT bearer grant and receives an ordinary access token. The grant is specified in the IETF OAuth working group’s Identity Assertion JWT Authorization Grant draft.

Why it matters

When every AI agent connection is a separate OAuth consent clicked by an individual user, IT cannot see which agents can reach which applications, cannot apply policy to those connections and cannot revoke them in one place, while long-lived refresh tokens accumulate across applications. Enterprise-managed authorization puts the decision where access policy already lives: the identity provider. Disabling a user or an agent there cuts off its access to every connected application. Ferentin supports it in both directions: its MCP gateway accepts ID-JAGs issued by your identity provider, and it uses them to connect to upstream applications that support the pattern.

Common use cases

  • Letting identity administrators approve which AI agents may reach which applications
  • Connecting MCP clients to enterprise MCP servers without a per-user consent screen
  • Revoking an agent’s access to every connected application from the identity provider
  • Recording which agent accessed which application on behalf of which user

How Ferentin handles it

Ferentin is the trust layer for AI agents. The platform centralizes identity, policy enforcement and audit across LLMs, MCP servers and AI tools. Enterprise-Managed Authorization is one of the primitives this trust layer is designed around. See the platform overview for how it fits into the service edge, control plane and observability plane.

Related terms

Workload Identity Federation

A way for software, such as an AI agent running in a cloud function, Kubernetes pod or CI job, to obtain short-lived access tokens by presenting the identity its platform already issued it, instead of holding a long-lived secret. The workload exchanges a signed identity token from its cloud provider, cluster or CI system for an access token scoped to what it may do. There is no static API key to leak or rotate, and each token traces back to a specific workload.

Scoped Access

A permission model for agentic AI in which a token carries two distinct claims: a coarse-grained capability claim recording what the client requested, and a fine-grained permission claim populated at issuance by an RBAC engine that reflects what the user actually holds. Treat the first as intent and the second as authority. Scoped access also implies short TTLs on elevated grants (typically fifteen minutes for admin-tier tokens), per-resource permission checks on every tool call, distinct treatment of service-account agents from human users, and a self-escalation denylist that prevents service accounts from minting their own admin grants. Named as one of the four control primitives in Anthropic’s 2026 CISO guidance for agentic AI.

Identity-Centric AI Security

A security approach where access to AI resources is governed by verified identity rather than network location or API keys. Every user, team and AI agent has a distinct identity, and access policies are evaluated based on who is making the request, not just where the request originates.

MCP Gateway

A centralized control plane for Model Context Protocol traffic. An MCP gateway secures, manages and routes connections between AI agents and MCP servers, enforcing zero-trust access controls and providing visibility into every tool invocation.

Zero Trust AI

A security model for AI systems where no request is implicitly trusted. Every inference call, tool invocation and agent action must be authenticated and authorized against fine-grained policies before execution. Zero Trust AI applies identity verification, least-privilege access and continuous monitoring to all AI interactions.

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