TL;DR: One-hour AI agent tasks can leave live CRM tokens active for weeks when no one is assigned to revoke them, according to Newcore. The real control point shifts to authorization time, because review cadences assume access persists long enough to be reviewed.
At a glance
What this is: This analysis argues that periodic access reviews do not fit AI agent token lifecycles, because short tasks can leave standing access live long after the work ends.
Why it matters: IAM and PAM teams need to move governance from retrospective certification to task-scoped, moment-of-use control when agents can acquire and outlive credentials inside a single work session.
By the numbers:
- 68% cannot reliably separate agent activity from human activity in their logs, according to the Cloud Security Alliance cited by Newcore.
Context
Access reviews are a governance control, but they were designed around stable human roles and slow permission drift. When an AI agent receives a token for a one-hour task, the access can outlive the work by days or weeks if no one is assigned to revoke it.
That mismatch is the core issue here: the organisation still has a review process, but the process is too late for a workload that acts and disappears quickly. Treat agent identity lifecycle as a live governance problem, not a quarterly certification exercise.
Key questions
Q: What breaks when AI agent access is reviewed only after the fact?
A: After-the-fact review leaves a gap between action and containment. If an agent can already reach a dataset, API, or SaaS system, the damage may be done before a human sees the alert. Runtime checks reduce that gap by stopping unauthorized actions before they execute.
Q: Why do short-lived agent tokens still create governance risk?
A: Because short-lived does not mean well-governed. A token can expire quickly and still represent an unreviewed approval, an overly broad task scope, or an unaudited delegation chain. The risk shifts from long-term credential theft to runtime misuse and weak accountability over who authorised the access.
Q: How do security teams know if agent governance is actually working?
A: It is working only if the team can answer three questions quickly for any agent: what it can reach, what it did recently, and whether that behaviour matches intent. If any of those answers require manual reconstruction, governance exists on paper but not in operations.
Q: What is the difference between periodic access reviews and authorization-time controls for agents?
A: Periodic reviews ask whether access was still needed after the fact, while authorization-time controls decide whether access should exist right now. For AI agents, that difference matters because the work can start and end before a review cycle runs, so governance has to move to the point of use.
Technical breakdown
Why periodic audits miss agent lifecycles
Periodic audits answer whether an identity still needs access, but that question assumes the identity remains stable long enough for the review window to matter. AI agents often request access for a task, complete it, and stop existing in that operational context before the next review cycle. A review that happens later can only confirm that access once existed, not prevent exposure while the token was still live. The architectural issue is timing: governance is being applied after execution rather than at issuance and use. That makes the control retrospective by design, even when the policy is correct. See the AI Agent Observability, Audit and Incident Response Guide.
Practical implication: Move high-risk agent access decisions closer to issuance and task completion, not the next certification cycle.
Why standing tokens create governance debt
A token that remains valid after the task ends becomes governance debt because it preserves authority with no current business need. In an agent context, that is not just stale access, it is unowned access, since the workflow may have ended and no human is monitoring the credential's lifespan. The result is a gap between entitlement and accountability: the system still trusts the token, but the organisation no longer has an active actor benefiting from it. That is why short-lived credentials matter more than periodic review alone; without expiry, the access state survives beyond the task that justified it. See the AI Agent Authorisation Guide.
Practical implication: Treat unexpired agent tokens as unresolved access debt until their lifecycle is explicitly closed.
Why attribution has to be part of the control plane
When agent activity cannot be clearly separated from human activity, the organisation loses the ability to assign responsibility for actions taken under machine credentials. Logs that stop at an anonymous token do not support meaningful investigation, owner notification, or cleanup. That makes attribution a control requirement, not just a forensic nice-to-have. For AI agents, access governance needs an ownership link between the credential and the person or team accountable for the workflow, because review without attribution cannot tell who should be notified when access persists too long.
Practical implication: Make agent ownership and action attribution mandatory fields in your logging and access governance model.
Threat narrative
Attacker objective: Use retained application-level access to read data and operate through the same permissions the agent was granted for legitimate work.
- Entry occurred when the AI agent was issued a token for a one-hour CRM task, creating legitimate but time-bound access.
- Escalation happened when the token stayed valid after the task ended, leaving standing access available for later use without new approval.
- Impact followed because the access remained live and unexamined for weeks, extending the exposure window beyond the work that justified it.
Breaches seen in the wild
- Salesloft OAuth token breach: hackers stole OAuth tokens to access Salesforce data via Salesloft.
- Internet Archive breach 2024: An exposed GitLab token opened Internet Archive code and 31 million user records; unrotated Zendesk tokens let the attacker back in weeks later.
Read and download The State of NHI & AI Agent Breach Report 2026, covering 200+ breaches impacting Non-Human Identities including AI Agents.
NHI Mgmt Group analysis
Periodic access reviews do not govern agentic access at the right time. The review model assumes access persists long enough to be observed, assessed and removed on a schedule. AI agents can complete a task and leave behind a valid token before the next review window opens. That means the governance failure is not missing review logic, but a lifecycle mismatch between certification cadence and execution speed.
Access review assumes a stable subject; an AI agent is not one. The premise that a reviewer can meaningfully ask whether the same identity still needs the same access works for humans because role state changes slowly. In an agent workflow, access may be born, used and obsolete within a single session. That collapses the assumption behind recertification, and teams have to rethink what a “reviewable” access state even is.
Authorization-time control is the named concept this problem exposes. When access is decided at the moment of use, the organisation controls intent before the token becomes a standing liability. Agent identity authorisation is the operational model that follows from this, because access governance has to travel with the task rather than wait for a later audit.
Ownership becomes the missing governance primitive once the user is a machine. If no one is assigned to revoke an agent token, accountability disappears into the calendar rather than the control plane. That is a structural weakness in many identity programmes: they can certify access, but they cannot reliably own the cleanup of machine-issued privileges. Practitioners need to treat ownership as part of the access lifecycle, not as an afterthought.
This is a lifecycle problem, not just a token problem. The article shows that short-lived credentials still become long-lived risk when the organisation lacks an offboarding path for completed tasks. The policy may look correct at issuance, but if revocation is not coupled to task closure, the control fails at the lifecycle boundary. That is where agent governance now has to be designed.
From our research library:
- Over 70% of organisations lack automated access risk analysis, user access reviews and provisioning and deprovisioning, according to Pathlock's 2025 Digital Transformation and Access Risk Report.
- Read next: Agentic AI Identity Guide
What this signals
Authorization-time governance: agent access has to be judged at request time because the useful life of a token may be shorter than the next review cycle. That pushes identity teams toward task-scoped issuance, automatic expiry and traceable ownership as baseline controls, not advanced maturity.
Periodic certification still has a role, but only as a validation layer over controls that already end access when the task ends. Programmes that leave revocation to quarterly review are effectively accepting a delay between use and governance that agent workflows can exploit.
The practical shift is from asking whether access was appropriate in retrospect to proving that no unowned privilege can survive task closure. That is where AI agent governance, agent observability and incident response, and identity operations now converge.
For practitioners
- Define task-scoped access for agents Issue permissions only for the specific job the agent is performing, and end them when the task closes rather than waiting for a later review cycle.
- Shorten token lifetimes to match execution Set AI agent credentials to expire with the task, so unused access disappears automatically instead of remaining live until quarterly certification.
- Assign an owner to every agent Record a human owner or accountable team for each agent credential so revocation, incident follow-up and audit trail closure have a clear target.
- Move policy checks to authorization time Evaluate each action request before execution, not only at initial authentication, so the control can block access that is no longer justified.
- Keep reviews as verification, not revocation Use periodic access reviews to confirm that real-time controls and expiry rules are working, rather than as the primary removal mechanism.
Key takeaways
- AI agent access becomes risky when token lifetimes outlast the task that justified them, because governance then happens after exposure instead of during execution.
- The article highlights a logging gap as well as a lifecycle gap, with 68% of organisations unable to reliably separate agent activity from human activity in logs.
- The control that matters most is moment-of-use authorization paired with automatic expiry and clear ownership, not quarterly review as the primary offboarding mechanism.
Related NHI Mgmt Group resources: AI Agent Authorisation Guide · AI Agent Observability, Audit and Incident Response Guide · Agentic AI Identity Guide · MCP Security Guide
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 OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST SP 800-53 Rev 5 and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | The article centers on agent access that persists beyond its intended task and becomes a privilege governance problem. |
| Recommendation — Apply ASI03 to constrain agent privileges to task scope and remove them when the task ends. | ||
| OWASP Non-Human Identity Top 10 | NHI-01 — Improper Offboarding | The main failure is that agent credentials outlive the task and are not revoked when work finishes. |
| NHI-07 — Long-Lived Secrets | Unused tokens remaining live for weeks are exactly the long-lived secret condition this article warns about. | |
| Recommendation — Treat completed agent tasks as offboarding events and revoke credentials immediately at closure. Set strict expiries on agent tokens and eliminate credentials that survive beyond task completion. | ||
| NIST SP 800-53 Rev 5 | IA-5 — Authenticator Management | IA-5 directly governs authenticator issuance, lifecycle and revocation for machine credentials. |
| AC-6 — Least Privilege | The article argues that agents should receive only the access needed for the current task. | |
| Recommendation — Use IA-5 to enforce token expiry, rotation and revocation rules for agent credentials. Apply AC-6 so each agent receives only the minimum permissions required for the active workflow. | ||
| NIST CSF 2.0 | PR.AA-05 — Access Permissions, Entitlements and Authorizations | The post is fundamentally about managing authorisations at the moment they are used, not later in review. |
| Recommendation — Use PR.AA-05 to govern agent authorisations continuously and align them with current task intent. | ||
Key terms
- Authorization-time control: A governance model that decides whether access should exist at the moment an action is requested, rather than relying on later review. For AI agents, this is critical because the task may complete before a scheduled audit runs, so the control must travel with execution.
- Task-Scoped Access: Task-scoped access is permission granted for one defined purpose and removed once the task is complete or the session expires. For non-human identities, it reduces standing privilege and limits how long an attacker can exploit a stolen credential.
- Token Lifecycle: Token lifecycle is the full sequence of issuing, refreshing, expiring, revoking, and reauthorizing a credential. For delegated access, lifecycle state is the real indicator of whether a connection is still legitimate, because a valid-looking token can still be stale, disconnected, or out of scope.
- Access Review: A formal process for confirming whether access is still needed and justified. In IAM programs, the review becomes an evidence-bearing control when decisions are recorded, scoped correctly, and traceable to the right reviewer, application owner, or auditor.
Deepen your knowledge
NHI governance, agentic AI identity, and machine identity lifecycle are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are responsible for identity security strategy or NHI governance in your organisation, it is worth exploring.
Published by the NHIMG editorial team on October 21, 2026.
NHI Mgmt Group, the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org