Use continuous discovery across cloud, SaaS, on-premises, and directory sources, then correlate each identity with ownership, entitlements, and last activity. The goal is to expose dormant, orphaned, shadow, and service identities before they become access paths. If a control only reviews known accounts, it is not measuring the full identity attack surface.
Why This Matters for Security Teams
Traditional IAM tools are designed to inventory known user populations, not to continuously expose the identities that appear outside directory-first workflows. That gap matters because dormant service accounts, orphaned cloud principals, OAuth grants, and hidden machine identities often sit in the same blast radius as privileged human accounts. Guidance from the NIST Cybersecurity Framework 2.0 emphasizes asset visibility and governance, but identity discovery for non-human environments still requires broader telemetry than most access reviews provide.
NHIMG research shows how large the visibility problem can be in practice: in The State of Non-Human Identity Security, only 1.5 out of 10 organisations reported high confidence in securing NHIs, while 85% lacked full visibility into third-party vendors connected via OAuth apps. That is not just an inventory issue. It is a detection failure that leaves unowned identities available for misuse, privilege creep, and persistence.
In practice, many security teams discover these identities only after an incident review exposes a forgotten token, a stale workload account, or a shadow integration that had already been active for months.
How It Works in Practice
The practical answer is continuous discovery across cloud control planes, SaaS tenants, on-premises directories, secrets stores, CI/CD pipelines, and application logs, followed by correlation into a single identity graph. Security teams need to identify what the entity is, who owns it, where it authenticates, what it can reach, and whether it is still active. This is where traditional IAM tooling often falls short: it may show accounts, but not the operational relationships that reveal whether those accounts are real, current, and legitimate.
Current best practice is to combine source-of-truth feeds with runtime evidence. That means ingesting directory objects, cloud IAM roles, API keys, service principals, OAuth grants, certificates, workload tokens, and secret usage events, then attaching metadata such as business owner, technical owner, last observed use, entitlements, and trust boundary. When available, pair that with signals from workload identity systems and short-lived credentials so that you can distinguish a living workload from an abandoned one.
- Start with broad discovery, then suppress duplicates across providers and accounts.
- Flag identities with no owner, no recent activity, or permissions that exceed their current function.
- Correlate human and machine pathways so delegated access, shared secrets, and automation do not hide the true principal.
- Use a workflow for remediation that can revoke, rotate, or quarantine after validation.
This approach aligns with the access and governance direction in NIST CSF 2.0, but identity discovery must also account for cloud-native exposure patterns. NHIMG’s reporting on Azure Key Vault privilege escalation exposure shows how inherited permissions and secret access paths can conceal the real identity surface if teams only review directory objects. These controls tend to break down when identities are created and consumed entirely by automation because the account lifecycle is shorter than the review cycle.
Common Variations and Edge Cases
Tighter discovery coverage often increases operational overhead, requiring organisations to balance visibility against false positives and remediation friction. That tradeoff is especially visible in SaaS environments, where delegated OAuth apps, vendor-managed integrations, and shared admin tooling can look legitimate until ownership is verified.
There is no universal standard for this yet, but current guidance suggests treating shadow identities, dormant identities, and service identities differently. A dormant human account can often be suspended quickly, while a workload identity may need secret rotation, certificate replacement, or policy reassignment before revocation. Likewise, some identities are intentionally long-lived for regulated systems, so age alone is not enough to justify removal.
Teams should also watch for identities that sit outside directory visibility entirely, such as tokens embedded in scripts, CI variables, or developer tooling. NHIMG has documented how JetBrains GitHub plugin token exposure illustrates the danger of credentials appearing in places traditional IAM does not inspect. The practical rule is simple: if discovery does not include ownership, entitlements, and last activity, it will miss the identities that matter most.
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 |
|---|---|---|
| NIST CSF 2.0 | ID.AM | Identity discovery maps to asset and identity inventory across environments. |
| OWASP Non-Human Identity Top 10 | NHI-01 | Discovery and inventory are core to finding hidden non-human identities. |
| NIST AI RMF | AI governance needs visibility into machine identities and their operational context. |
Build continuous identity inventory feeds and track ownership, activity, and entitlements across all sources.
