Long-lived tokens assume access remains valid until a person revokes it, but agent behaviour changes the risk model because the actor can decide and act at runtime. That makes persistent delegation harder to justify, especially when the task is narrow and short-lived. Session-bound authorization reduces the exposure window and fits the way agents actually execute work.
Why Long-Lived User Tokens Become a Governance Problem for AI Agents
Long-lived user tokens were designed around human workflows: a person signs in, uses a service for a while, and eventually revokes access. AI agents do not behave that way. They act at runtime, chain tools, retry tasks, and may continue operating after the original intent has changed. That creates a governance gap between who approved access and what the autonomous workload is actually doing. Current guidance increasingly treats this as an agentic authorization problem, not just a credential hygiene problem, as reflected in the OWASP Top 10 for Agentic Applications 2026 and NIST AI Risk Management Framework.
The practical risk is not only theft. A token that remains valid for weeks or months becomes standing authority for a goal-driven system that can explore paths the approver never anticipated. NHIMG’s OWASP Agentic Applications Top 10 and Top 10 NHI Issues both point to the same pattern: persistent secrets and broad delegation are hard to justify once an identity can act independently. In practice, many security teams discover the issue only after an agent has already used an overbroad token outside the task that originally justified it.
How Governance Should Work for Autonomous Workloads
For AI agents, static role assignments are usually too coarse. Best practice is evolving toward intent-based authorization, where the decision is made at request time using the task, target resource, data sensitivity, and current risk context. That is a closer fit for CSA MAESTRO agentic AI threat modeling framework and the NIST Cybersecurity Framework 2.0, which both emphasize risk-managed, continuously evaluated controls rather than one-time trust decisions.
Operationally, this means replacing long-lived user tokens with JIT, ephemeral credentials that are issued for a single task or short session, then revoked automatically when the task completes. The token should represent the workload identity, not a human’s broad account session. Where possible, use cryptographic workload identity such as SPIFFE or OIDC-backed service identities so the platform can prove what the agent is, while authorization policy decides what the agent may do right now. NHIMG’s Ultimate Guide to NHIs — Lifecycle Processes for Managing NHIs is useful here because lifecycle control matters as much as access control.
- Issue credentials per task, not per user session.
- Bind tokens to workload identity and narrow scopes.
- Evaluate policy at request time with full context.
- Revoke or expire access automatically on completion.
- Log every tool call for audit and rollback.
This guidance tends to break down in legacy SaaS environments that only support broad OAuth grants and coarse scopes, because the agent cannot be cleanly constrained to the specific operation it was assigned.
Where the Tradeoffs and Edge Cases Show Up
Tighter session-bound authorization often increases operational overhead, so organisations have to balance stronger control against integration effort and runtime complexity. There is no universal standard for this yet, especially when agents need to work across many tools, complete multi-step goals, or collaborate in multi-agent pipelines. In those cases, the main question is not whether the agent has a token, but whether the token is still appropriate for the current intent.
One important exception is machine-to-machine automation that is deterministic and narrowly scoped. A fixed service credential may be acceptable there if the workload is not autonomous in the agentic sense. The governance bar changes once the system can decide, branch, or pursue subgoals on its own. That is why Salesloft OAuth token breach is relevant as a cautionary example: long-lived delegated access turns a single credential issue into broad downstream exposure. The same pattern is visible in The State of Secrets Sprawl 2026, which found that 64% of valid secrets leaked in 2022 are still valid and exploitable today. For AI agents, that persistence is exactly the problem.
Practitioners should treat long-lived user tokens as temporary migration tooling, not a durable control model for autonomous systems. The safer path is short-lived credentials, explicit workload identity, and policy that follows the action instead of the person.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10 and CSA MAESTRO address the attack and risk surface, while NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | AAI-02 | Agentic systems need runtime authorization, not static user delegation. |
| CSA MAESTRO | MAESTRO maps threat modeling to autonomous agent behaviour and control gaps. | |
| NIST AI RMF | AIRMF governs accountability, risk, and continuous oversight for AI systems. |
Assign ownership and review controls for agents as continuously managed AI risk assets.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on June 6, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
