Topic starter
25/08/2026 6:10 pm
TL;DR: Least privilege must be treated as an operating model spanning humans, non-human identities, and AI agents, with the strongest signal being its emphasis on AI agent security across multiple platforms, according to Veza. The central issue is that governance based on static permissions and periodic review cannot keep pace with runtime identity behaviour.
Editorial analysis by NHI Mgmt Group, based on content published by Veza: “Product”.
Key questions
Q: Should organisations use the same controls for humans, NHIs, and AI agents?
A: No. The control family may overlap, but the operating assumptions differ. Human identity controls focus on authentication and user context, while NHIs need lifecycle and credential governance, and AI agents require both NHI controls and runtime oversight for autonomous action. The correct model is shared governance with actor-specific enforcement.
Q: Why do quarterly access reviews fail for AI agents and NHIs?
A: Quarterly reviews fail because they assume access stays stable long enough for a human to inspect it.
Q: What breaks when least privilege is missing?
A: When least privilege is missing, a single compromised identity can reach far more systems and data than the task requires.
Practitioner guidance
- Define least privilege by actor type Separate human, NHI, and AI agent entitlement models so each is governed by the access patterns it actually uses rather than a shared policy template.
- Map runtime privilege paths Trace how permissions are combined during execution, including delegated calls, tool use, and workload-to-workload access, then mark where scope expands beyond the original task.
- Rework access reviews for dynamic identities Use review processes to validate whether access boundaries still make sense, but move enforcement to issuance and runtime controls where identities act too quickly for periodic certification.
Bottom line: Least privilege is no longer just a permissioning principle. In mixed human, NHI, and AI environments, it has to be managed as a living governance model.
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This topic was modified 17 hours ago by NHI Mgmt Group
25/08/2026 6:11 pm
Least privilege has become a governance maturity model, not a static design rule. The article is right to shift the conversation away from one-time permission assignment toward continuous control over who or what can act, when, and with which scope. That shift matters because modern identity estates mix humans, NHIs, and AI agents in the same operational paths. Practitioners should treat least privilege as a living control that must be measured across the full identity lifecycle.
A few things that frame the scale:
- Gartner predicts that more than 50% of successful cyberattacks against AI agents through 2029 will exploit access control weaknesses.
A question worth separating out:
Q: What is the difference between access review and runtime enforcement for AI agents?
A: Access review checks whether access was approved, while runtime enforcement checks whether the agent is staying inside its effective scope while it acts. For AI agents, both matter, but runtime enforcement is the control that catches privilege expansion during execution.
👉 Read our full editorial: Veza's identity security maturity model reframes least privilege
This post was modified 17 hours ago by NHI Mgmt Group