Start by measuring where users actually work, not where the identity programme assumes they work. Security teams should inventory unmanaged apps, non-federated accounts, and AI tools, then apply policy, offboarding, and monitoring to the uncovered paths first. The goal is to make hidden access visible enough that governance can follow it.
Why This Matters for Security Teams
The access-trust gap appears when identity and access governance describe one environment, but SaaS usage and AI tool adoption create another. That gap matters because attackers rarely need a perfect breach if they can reach an ungoverned OAuth app, a non-federated account, or an over-permissioned AI connector. NHI Management Group’s research on The State of Non-Human Identity Security shows how common this visibility problem is across connected services.
For practitioners, the issue is not just discovery. It is that hidden access paths often sit outside normal provisioning, review, and offboarding workflows, so they persist even when user accounts look clean on paper. This is where SaaS and AI environments diverge from classic enterprise IAM: access is increasingly granted through integrations, tokens, and machine identities rather than only named users. The OWASP Non-Human Identity Top 10 is useful here because it frames the problem as an identity and permission issue, not just a SaaS sprawl problem. In practice, many security teams encounter unauthorized persistence only after a vendor integration, AI connector, or stale token has already been used to move data.
How It Works in Practice
Closing the gap starts with building an inventory of where access actually exists: unmanaged SaaS apps, shadow IT subscriptions, delegated OAuth grants, service accounts, API keys, and AI tools that can read, write, or forward data. The inventory should separate human-authored access from machine-authored access, because a human user and an autonomous tool do not need the same governance model. For SaaS, that often means pulling app and token data from SSO, CASB, directory logs, and email/admin consoles. For AI environments, it also means tracking tool connections, retrieval permissions, and prompt-to-action pathways.
Security teams should then apply control to the uncovered paths first. Current guidance suggests prioritising the highest-risk cases: non-federated accounts, long-lived secrets, external sharing, and AI tools that can execute actions on behalf of users. Aligning this work with Ultimate Guide to NHIs helps teams map the issue to identity lifecycle control rather than treating it as a one-off audit. Offboarding should revoke OAuth grants, API tokens, service-account bindings, and AI connector permissions together, not as separate workstreams.
- Inventory every SaaS and AI integration that can access business data or act in a user context.
- Classify access by federation status, privilege level, ownership, and token lifetime.
- Replace standing access with time-bound approvals where the workflow supports it.
- Monitor token use, connector activity, and abnormal data movement continuously.
- Reconcile access reviews against actual logs, not only directory records.
OWASP guidance on non-human identities and CSA-style SaaS governance both point to the same operational principle: if the access path is not measurable, it cannot be governed. These controls tend to break down when business units can create SaaS and AI integrations without central registration because the identity map becomes stale before review cycles complete.
Common Variations and Edge Cases
Tighter control over SaaS and AI access often increases friction for users and integration owners, so organisations have to balance visibility against business speed. That tradeoff is real, especially in engineering, marketing, and data teams where self-service tools are common and roles change quickly. Best practice is evolving here: there is no universal standard for how to govern every AI connector or embedded app, but the direction is clear toward stronger approval, scoping, and revocation discipline.
Edge cases matter. Some SaaS platforms expose limited admin telemetry, so teams may need to infer access from SSO events, email consent records, or billing data. Some AI tools operate through browser extensions or personal accounts, which makes them difficult to inventory with traditional IAM alone. Others rely on shared service accounts, where individual accountability is weak and offboarding is especially error-prone. In those cases, NHI controls and workflow evidence matter more than directory hygiene.
The most useful operating model is to treat every hidden credential, delegated grant, and AI tool permission as an access path with an owner, a purpose, a lifetime, and a revocation trigger. That approach is consistent with the 52 NHI Breaches Analysis and with OWASP’s emphasis on non-human access risk. It also aligns with the practical lesson that governance must follow actual usage, not organizational assumptions, if the access-trust gap is going to close.
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 | Hidden SaaS tokens and AI connectors are non-human identities needing inventory. |
| NIST CSF 2.0 | PR.AA-01 | Access paths must be identified before governance can be enforced. |
| NIST AI RMF | AI tools that act on behalf of users create governance and accountability risk. |
Discover and classify all machine and delegated identities before applying least privilege.
Related resources from NHI Mgmt Group
- How should security teams govern API keys used for generative AI access?
- How should security teams govern AI agent access when protocols leave authorization open-ended?
- How should security teams govern AI systems used in classified or disconnected environments?
- How do IAM teams decide whether an AI security assistant needs its own access controls?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on June 11, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
