By NHI Mgmt Group Editorial TeamPublished 2026-03-24Domain: Governance & RiskSource: Delinea

TL;DR: Identity risk is outpacing security architecture as agencies and enterprises add human, machine, service, and AI identities, while attackers increasingly abuse valid credentials and stolen passwords, according to Delinea, drawing on Verizon DBIR 2023 and IBM X-Force Threat Intelligence Index 2024. The practical issue is not zero trust in theory, but whether identity programmes can sustain continuous verification and least privilege across a much larger attack surface.


At a glance

What this is: This is an analysis of how exploding identity volume and credential abuse are colliding with federal zero trust mandates.

Why it matters: It matters because IAM, NHI, and PAM teams now have to align governance, verification, and privilege controls across human users, service identities, and AI-enabled actors at the same time.

By the numbers:

👉 Read Delinea's analysis of federal zero trust mandates and identity risk sprawl


Context

Identity risk grows when the number of identities, permissions, and authentication paths expands faster than the controls meant to govern them. In this case, the core problem is not a lack of policy language but a mismatch between modern identity sprawl and architectures designed for smaller, slower, more predictable environments.

For IAM and NHI programmes, the pressure point is zero trust. Continuous verification and least privilege only work when identity inventories are current, privilege scope is visible, and machine, service, and AI identities are governed with the same discipline as human accounts.

That tension is familiar across federal and regulated environments, where mandates now force teams to prove control effectiveness rather than merely document intent. The starting point in the article is typical of many large enterprises: broad tool coverage, fragmented visibility, and too much confidence in compliance-driven identity controls.


Key questions

Q: How should security teams implement zero trust for human, machine, and AI identities together?

A: Start by unifying identity inventory, ownership, and privilege policy across all three identity classes. Then enforce continuous verification at the session and task level, because zero trust fails when each identity type is governed in a separate tool or review process. The control objective is consistent trust evaluation, not separate compliance stories.

Q: Why do valid credentials still create so much risk in zero trust environments?

A: Because a credential can be valid and still be unsafe if it has more privilege than the current task requires. Zero trust reduces that risk only when access is re-evaluated continuously and privilege is minimized at runtime. If access stays static after authentication, the environment still trusts the wrong thing.

Q: How do you know if least privilege is actually working for privileged identities?

A: Look for evidence that elevated access is task-bound, time-limited, and revoked after use rather than left standing. If privileged accounts remain broadly usable between reviews, least privilege exists on paper but not in operation. The best signal is whether sensitive actions require fresh justification and leave clear access evidence.

Q: Who is accountable when zero trust implementation lags behind identity growth?

A: Accountability usually sits with the identity owner, the platform team, and the control owner together, because the failure spans inventory, enforcement, and governance. In regulated environments, programme leaders must be able to show which identities are covered, which are excluded, and which controls prove runtime enforcement. A mandate without evidence is not defensible.


Technical breakdown

Identity sprawl turns authentication into a control problem

Identity sprawl means the environment contains far more human, machine, service, and AI identities than the governance model was built to track. The failure is not simply scale, but multiplicity: each identity class brings different lifecycle rules, different privilege patterns, and different audit evidence. When those identities are managed through separate tools and policies, gaps appear between inventory, entitlements, and actual runtime use. Zero trust depends on knowing what is authenticating, what it can reach, and whether that access is still justified. Practical implication: organisations need one governed view of identity scope before they can make zero trust measurable.

Practical implication: build a unified identity inventory that includes human, NHI, and AI-linked accounts before expanding zero trust enforcement.

Valid credential abuse bypasses perimeter assumptions

Valid credential abuse is effective because the attacker does not need to defeat authentication if the environment already trusts the credential. Once a password, token, or privileged account is accepted as legitimate, detection shifts from perimeter blocking to behaviour analysis, privilege validation, and session scrutiny. This is why identity is now the entry point, not just the endpoint of an attack. Zero trust narrows that advantage only when access decisions are continuously re-evaluated and not assumed safe after login. Practical implication: teams should treat credential authenticity as necessary but insufficient, and pair it with real-time access validation.

Practical implication: add session-level verification and privileged activity monitoring, not just stronger initial authentication.

Zero trust depends on runtime least privilege, not audit artifacts

The article’s real tension is that many identity programmes were built to satisfy audits rather than to stop abuse in motion. Audit evidence can show that policies exist, but it cannot prove that access stayed minimal during execution or that identity paths remained clean across tools. Zero trust requires runtime enforcement, with access narrowed to the specific task, identity class, and trust context. That is especially important for service accounts and AI-enabled identities, where standing access becomes a standing assumption. Practical implication: move from policy documentation to enforcement proofs that show who or what had access, when, and why.

Practical implication: require evidence of runtime least privilege, not just policy approval, for high-risk identities.


NHI Mgmt Group analysis

Identity risk has outgrown the audit-first model that most programmes still rely on. The article points to a familiar pattern: controls were built to prove compliance, while attackers now exploit valid credentials and identity sprawl in real time. That is a governance failure because the model measures whether identity exists, not whether it remains trustworthy throughout use. Practitioners should stop treating identity assurance as a document trail and start treating it as a live control problem.

Zero trust is becoming an identity operating model, not a network overlay. Continuous verification and least privilege only work when identity governance spans human users, service identities, and AI-linked actors in one control plane. If those identities sit in separate tooling or separate review cycles, zero trust becomes partial by design. The practical conclusion is that identity architecture now has to be unified across access, privilege, and lifecycle decisions.

Standing privilege remains the structural weakness that attackers exploit most reliably. The article’s credential-abuse theme reinforces that long-lived access is easier to compromise, reuse, and hide than ephemeral access tied to context. NHI and PAM teams should read this as a warning that entitlement duration is as important as entitlement scope. The programme implication is that persistent access must be the exception, not the default.

Identity blast radius: the size of the damage an attacker can cause once a trusted identity is abused. In environments with many identity classes and fragmented tooling, blast radius expands faster than most teams notice. That is why the question is no longer whether an account is authenticated, but how much it can reach before verification, revocation, or containment can intervene. Practitioners need to manage identity exposure as a blast-radius problem, not a credential-count problem.

Federal zero trust mandates are forcing identity teams to prove control effectiveness, not just policy presence. The article’s mandate framing matters because deadlines expose weak governance faster than internal roadmaps do. Teams that can only show plans will struggle to show operational assurance across ICAM, PAM, and NHI controls. The field implication is clear: identity governance must become evidence-driven, measurable, and cross-domain.

From our research:

  • 1 in 4 organisations are already investing in dedicated NHI security capabilities, with an additional 60% planning to do so within the next twelve months, according to The State of Non-Human Identity Security.
  • 85% of organisations lack full visibility into third-party vendors connected via OAuth apps, which leaves a large share of identity risk outside normal review cycles.
  • For lifecycle and privilege controls, see NHI Lifecycle Management Guide for how provisioning, rotation, and offboarding reduce standing access exposure.

What this signals

Identity blast radius: the practical question for most programmes is not whether zero trust is adopted, but whether access can be contained before it spreads across too many identities and tools. With 1 in 4 organisations already investing in dedicated NHI security capabilities, according to The State of Non-Human Identity Security, the market is signalling a shift from policy alignment to runtime containment.

That shift will force teams to connect zero trust roadmaps with lifecycle controls, entitlement review, and privilege reduction across human, NHI, and AI-linked identities. The organisations that can prove coverage across those layers will be better positioned to absorb mandate pressure without adding more blind spots.

For teams mapping the control stack, the relevant external benchmark is NIST SP 800-207 Zero Trust Architecture, because the article’s central issue is not perimeter defence but continuous trust evaluation.


For practitioners

  • Unify identity inventory across all actor types Create a single inventory that includes human users, service accounts, machine identities, and AI-linked identities, then map each to owner, purpose, privilege, and lifecycle state. A fragmented inventory hides the exact exposure the article warns about.
  • Recast zero trust as a runtime verification programme Measure whether access decisions are continuously re-evaluated during use, not just at sign-in. Pair authentication with session monitoring, entitlement checks, and task-scoped privilege so trusted credentials cannot roam unchecked.
  • Shorten the lifetime of high-risk privileges Review where privileged access is standing by default and replace it with task-bound elevation, tighter expiry, and mandatory re-approval for sensitive operations. The goal is to reduce how long compromised access can remain useful.
  • Tie federal mandate tracking to control evidence Build reporting that shows which zero trust and ICAM controls are actually enforced, where they are exceptions, and which identity classes remain outside coverage. Compliance teams need evidence of enforcement, not just roadmap status.

Key takeaways

  • Identity growth is now faster than the governance model meant to control it, which turns zero trust into an operational discipline rather than a policy slogan.
  • Credential abuse remains the most reliable attacker path because valid access can still be over-privileged, long-lived, and hard to detect in fragmented environments.
  • The control priority is to prove runtime containment across all identity types, not merely to document that zero trust and ICAM initiatives exist.

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 Zero Trust (SP 800-207) and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.

FrameworkControl / ReferenceRelevance
NIST Zero Trust (SP 800-207)Zero trust is the article's central governance model for continuous verification.
NIST CSF 2.0PR.AC-1Identity and access governance underpin zero trust implementation and coverage.
OWASP Non-Human Identity Top 10NHI-03Standing access and identity sprawl are core non-human identity governance risks.

Use PR.AC controls to prove who can access what, and remove excess access on a defined cadence.


Key terms

  • Zero Trust Architecture: A security model that assumes no identity or network location is trustworthy by default. Access is granted only after repeated verification of identity, context, and need, which makes continuous evaluation more important than one-time authentication.
  • Non-Human Identity: Any digital identity used by software, machines, services, or automated workloads rather than people. This includes service accounts, tokens, API keys, certificates, and AI-linked identities that need ownership, lifecycle control, and privilege governance.
  • Standing Privilege: Persistent access that remains available until someone removes it, instead of being granted only for a specific task. In identity programmes, standing privilege increases exposure because compromised credentials stay useful for longer and are harder to contain.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity lifecycle are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are responsible for identity security strategy or NHI governance in your organisation, it is worth exploring.

This post draws on content published by Delinea: Meeting federal zero trust mandates amid exploding identity risk. Read the original.

NHIMG Editorial Note
Published by the NHIMG editorial team on 2026-03-24.
NHI Mgmt Group — the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org