Security teams should govern dynamic identities by combining entitlement review with behavioural baselining. The key is to track how access is actually used, not just whether it was approved. That means monitoring scope drift, reuse, and abnormal relationships across systems, especially for service accounts, tokens, and delegated workflows.
Why This Matters for Security Teams
Identities whose behavior changes over time are difficult to govern because approval is not the same as safe use. Service accounts, OAuth grants, delegated workflows, and AI-driven automations can drift far beyond their original purpose after the initial access decision. That makes static entitlement review necessary but insufficient. Current guidance suggests pairing governance with continuous validation, especially where secrets, tokens, and machine-to-machine trust relationships can spread silently across systems.
The practical risk is not just over-privilege, but behavior that becomes normal only because it is repeated. A token may begin as a narrow integration credential and later be reused by new pipelines, copied into scripts, or connected to third parties. NHIMG’s Ultimate Guide to NHIs notes that 97% of NHIs carry excessive privileges, which is exactly why behavior-based governance matters. The NIST Cybersecurity Framework 2.0 reinforces continuous risk management rather than one-time trust decisions.
In practice, many security teams discover scope drift only after a token has already been reused across systems and the original approval record no longer reflects reality.
How It Works in Practice
Effective governance starts with identity inventory, then adds behavioral baselining. Teams should map what each non-human identity is expected to do, where it authenticates, which resources it touches, and what frequency and timing look normal. That baseline becomes the reference for detecting scope drift, unusual call patterns, new destinations, and privilege reuse. For high-change identities, the control objective is not just access review but runtime awareness of what the identity is actually doing.
Practitioners usually combine several mechanisms:
- Review entitlements on a fixed schedule, but treat review as a minimum control rather than the whole program.
- Log token usage, API calls, and delegated actions so the identity’s real blast radius is visible.
- Revoke or rotate credentials when the behavior changes materially, not only when a calendar date is reached.
- Separate long-lived infrastructure identities from short-lived workflow identities wherever possible.
- Use policy-as-code or conditional approval so access can be evaluated against current context, not just a prior ticket.
This is especially important where machine identities are embedded in CI/CD, SaaS integrations, and vendor connections. NHIMG’s Lifecycle Processes for Managing NHIs is useful for aligning inventory, rotation, and offboarding discipline, while the Top 10 NHI Issues highlights why missing rotation and weak monitoring repeatedly show up in incidents. The NIST Cybersecurity Framework 2.0 is a good anchor for tying this work to ongoing detect and respond processes.
These controls tend to break down when identities are shared across teams, embedded in legacy automation, or hidden inside third-party SaaS integrations because ownership and normal behavior are no longer clearly defined.
Common Variations and Edge Cases
Tighter behavioral governance often increases operational overhead, requiring organisations to balance stronger assurance against developer friction and alert fatigue. That tradeoff is real, especially for identities that change frequently by design, such as ephemeral build credentials, data pipeline tokens, and delegated service-to-service access. There is no universal standard for every environment, so best practice is evolving toward risk-tiered treatment rather than a single policy for all identities.
For example, a static service account that changes its access pattern only after a quarterly release may need periodic review plus anomaly detection, while a highly dynamic agent or workflow credential may need much shorter TTLs and near-real-time evaluation. In some environments, behavioral baselining is less useful than strict scoping and fast revocation because the identity’s job changes too often to define a stable pattern. Where third-party connections are involved, full visibility is often the constraint, not policy design. NHIMG research shows that visibility gaps are common, which means governance programs need ownership, logging, and offboarding discipline before they can rely on advanced analytics.
The most reliable approach is to classify identities by volatility, then apply the right mix of review, telemetry, and revocation. That keeps governance practical without pretending every identity can be managed with the same cadence or the same control model.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-01 | Behavior drift and excessive privilege are core non-human identity risks. |
| NIST CSF 2.0 | PR.AC-4 | Least-privilege access must be reviewed as identity behavior changes. |
| NIST AI RMF | GOVERN | Changing identity behavior needs ongoing accountability and risk oversight. |
Inventory each NHI, define its intended use, and continuously verify it still matches actual behavior.
Related resources from NHI Mgmt Group
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on July 4, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
