AI agents are diagnosing network faults, parsing firewall logs, querying routing devices, and making financial decisions in production environments.
But every agent that touches a sensitive resource must be treated as a privileged identity. And that identity needs to be governed just as carefully as any human user’s.
Based on my discussions with customers there are four distinct models for managing agentic AI access. Each designed for a different architecture and risk posture.
🤝 Option 1 — Human-In-The Loop Model
Every AI agent needs its own identity but in this model, the AI agents work on-behalf-of a human user. A human user authenticates via SSO such as Cisco Duo first. This human identity is captured by platform such as Britive. And then Britive uses “human-in-the” loop model to checkout scoped authorization (called profile) for the AI Agents or AgenticOps AI App. So one human identity can acts on behalf of multiple AI agents in that session.
Simple to set up. Fully auditable. The human stays accountable.
🔗 Option 2 — App-Level OIDC Federation
Here, the AgenticOps AI application itself becomes an OIDC identity provider, federated directly with a tool like Britive. Think of how GitHub Actions works. No stored credentials, just a short-lived JWT. This short lived JWT appears as “AgenticOps AI Service Account” in Britive. This “AI Service Account” identity then “checkout” scoped profilse, access necessary systems such as routers, switches, firewall, etc. And then, the access that expires the moment the task is done.
Same pattern. Applied to your AI agents. Humans can be added in the loop at the time of sensative profile checkout for approval or ticketing. The ownership can also be assigned to one or multiple humans for the “AgenticOps AI Service Account” for assurance and visibility.
🗝️ Option 3 — Static Key Onboarding with Dynamic Checkout
The most straightforward path. Each agent is onboarded in a tool like Britive with static credentials for authorization needs. In this model, the SSO is bypassed. Because there is no human in the loop. The humans can be added in the loop depending on the type of resource access and how sensitive it is. The actual resource access remains dynamic, scoped, and time-limited via Britive’s profile checkout model.
A practical bridge for teams moving toward fully federated identity. In this model the AI Agents always have static keys in Britive. It is a one time key setup with rotation and expiration option.
🛡️ Option 4 — SPIFFE / SPIRE Workload Identity
This is the idea that came from Kubernetes world. It is open standard protocol. It is yet to become and main stream option for agentic AI workloads. Its like a “Certification Authority” in the middle where AI Agents would first register. AI Agents register with a SPIRE server and receive a cryptographically verifiable workload identity. Britive trusts the SPIRE server. Or you can think of it as Britive forms a federation with SPIRE server. There are no shared secrets, no credentials to rotate, just attested identity tied to the runtime environment itself.
Why does this matter?
Picture an AIOps platform troubleshooting a live network incident. A chain of agents one analyzing firewall security logs, another correlating routing anomalies, a third querying switch configurations. All need real, granular access to production devices.
Those agents can’t carry broad, permanent credentials. They need exactly the right access, exactly when they need it, and nothing more once the job is done. That’s what Britive is built for.
Zero standing privilege. Full auditability. Access models that protects your AI agents whereever they are.
Comments are closed