Security teams should use continuous discovery and monitoring that maps every identity type to the systems it can reach, how access was granted, and whether that access is still justified. The goal is to expose dormant accounts, service accounts, contractors, APIs, and autonomous agents before they create breach paths or compliance gaps.
Why This Matters for Security Teams
Hidden access is rarely a single bad account. In hybrid environments it is usually an accumulated exposure problem: dormant employee accounts, contractor identities, service principals, OAuth grants, API keys, and now autonomous agents that can chain tools and act outside the original approval path. Security teams miss the full picture when they review identity silos instead of effective reach across systems, data, and privileges.
This is becoming more urgent as agentic workflows expand the attack surface. NHIMG’s AI Agents: The New Attack Surface research reports that 80% of organisations say AI agents have already acted beyond intended scope, while only 52% can track and audit the data those agents access. That gap is exactly where hidden access turns into breach paths, audit failures, and privilege escalation. Current guidance from the NIST AI Risk Management Framework and OWASP Non-Human Identity Top 10 supports continuous visibility, but there is no universal standard for a complete cross-identity discovery model yet.
In practice, many security teams discover the most dangerous access only after an incident, not through a planned identity review.
How It Works in Practice
Effective discovery starts with an inventory that treats every identity as a first-class subject, not just employees. That means correlating human identities, NHIs, and agents to the resources they can reach, the privileges they actually exercise, and the mechanism that granted access. For humans, this may include HR source-of-truth records, group memberships, privileged roles, and dormant accounts. For NHIs, it includes service accounts, workload identities, API keys, certificates, cloud roles, and third-party OAuth grants. For agents, it includes tool permissions, model-connected accounts, delegated tokens, and any runtime authorisations that let the agent call downstream systems.
The practical goal is to map effective access, not merely assigned access. That usually requires joining IAM, PAM, cloud audit logs, SaaS logs, endpoint telemetry, and application-level authorization events into one graph. Then teams can identify outliers such as identities with no owner, privileges that were never exercised, credentials that outlive the workload, or agents that can reach sensitive systems without a current business justification. The OWASP Agentic AI Top 10 and CSA MAESTRO agentic AI threat modeling framework both reinforce the need to understand runtime tool use and delegation, not just account provisioning.
- Use graph-based discovery to connect identities, entitlements, sessions, and data paths.
- Flag identities with no clear owner, no recent use, or access that exceeds job or workload needs.
- Continuously validate agent permissions against current task scope, not yesterday’s approval.
- Reconcile cloud, SaaS, and on-prem access because hidden reach often spans all three.
NHIMG’s The State of Non-Human Identity Security research also shows that 85% of organisations lack full visibility into third-party vendors connected via OAuth apps, which is a common blind spot in hybrid estates. These controls tend to break down when access is distributed across many SaaS tenants, cloud accounts, and short-lived agent workflows because the evidence is fragmented across systems.
Common Variations and Edge Cases
Tighter discovery usually increases operational overhead, so organisations have to balance completeness against log volume, false positives, and ownership ambiguity. That tradeoff is especially visible when third-party integrations and autonomous agents are involved, because access may be technically valid while still being unjustified.
Guidance is still evolving for a few edge cases. For example, there is no universal standard for how to model ephemeral agent sessions that inherit human intent but act with independent tool authority. Best practice is evolving toward context-aware review: who approved the workload, what data it touched, which tools it used, and whether the session stayed within policy. The same applies to break-glass accounts, shared admin credentials, and legacy service accounts that cannot yet be fully rotated or removed. Security teams should document these exceptions explicitly and monitor them more aggressively rather than leaving them in the same review queue as ordinary access.
For high-risk environments, pair discovery with periodic recertification and runtime monitoring. The point is not to prove every entitlement is harmless, but to surface where access has outlived its purpose. That approach aligns with the intent of NIST AI Risk Management Framework governance expectations and with lessons from NHIMG’s CoPhish OAuth Token Theft via Copilot Studio coverage, where delegated access became the real exposure path.
Related resources from NHI Mgmt Group
- How should security teams run access reviews for non-human identities?
- How should security teams govern non-human identities that have persistent access?
- How should security teams govern non-human identities in cloud environments?
- How should security teams evaluate privileged access management before deploying it across human, machine, and certificate identities?
