Human and nonhuman identity controls are diverging fast

At a glance

What this is: This is an identity-governance analysis showing that human and nonhuman controls are diverging as NHIs outscale people and behave in ways standard IAM does not handle well.

Why it matters: IAM, IGA and PAM teams need to separate human and machine governance paths because treating NHIs like users expands attack surface, weakens visibility and creates brittle production controls.

By the numbers:

• Nonhuman identities now outnumber human identities at a ratio of 144 to 1, according to Entro Security’s H1 2025 research, up from 92 to 1 just one year earlier.

Context

Human identity controls and nonhuman identity controls are no longer interchangeable. Human IAM assumes interactive login, session oversight and user behaviour baselines, while machine identities rely on programmatic authentication, persistent access paths and automated execution.

The governance gap matters because service accounts, API tokens, automation credentials and AI agents are now core infrastructure identities. When organisations apply user-centric controls to those identities, they often create either blind spots or overprovisioned access that persists well beyond the workload that needed it.

Key questions

Q: What breaks when organisations manage machine identities like user accounts?

A: The programme loses visibility, ownership, and lifecycle control. Machine identities do not follow human onboarding, MFA, or password-reset patterns, so user-first processes miss the real control points. That leads to orphaned credentials, weak attribution, and a larger attack surface than the access review process is able to detect.

Q: Why do long-lived service account credentials increase breach risk?

A: Long-lived credentials create standing access that remains valid after a workload, integration or operator has changed. That persistence expands the attacker window and makes revocation harder, especially when the identity has broad permissions and no clear owner.

Q: What are the signs that non-human identity governance is starting to slip?

A: Warning signs include reliance on manual upgrade paths, ad hoc secret handling, and fragmented access management across tools and environments. The article mentions caveats, dispatch limits, SSO support, and automated update channels, all of which point to the need for controlled operational discipline. When teams cannot explain how identities are provisioned, updated, and constrained, governance is already weaker than it should be.

Q: How do IAM and IGA teams handle human and non-human access in AI projects?

A: They need one governance model that ties people, service accounts, bots, and tokens to the OpenAI actions they can perform. Without that cross-identity view, reviews become fragmented and auditors cannot see who can do what across the full AI stack.

Technical breakdown

Why human IAM assumptions fail for machine identities

Human IAM was built around people who authenticate interactively, have predictable working patterns and can be reviewed through login and session artefacts. Nonhuman identities behave differently. They authenticate through tokens, keys and service credentials, operate continuously, and are often created by developers or pipelines rather than HR or joiner-mover-leaver workflows. That means the control points shift from login experience to credential issuance, scope, ownership and lifecycle. If the programme still assumes a user behind every identity, it misses the operational reality of workloads and automation. Practical implication: move machine identities out of human-centric governance paths and manage them as a separate identity class.

Practical implication: separate machine identity controls from human IAM workflows and govern them through issuance, scope and lifecycle.

How overprivilege and long-lived credentials expand NHI risk

Machine identities become high-risk when they accumulate broad access and keep credentials alive longer than the workload itself. A token, API key or service account password can persist after the original application, vendor relationship or automation task has changed, creating standing access that attackers can abuse without a human login event. The article also points to persistent overpermissioning, which turns quiet background identities into broad attack paths. The core issue is not just credential exposure. It is the combination of persistent access, poor ownership and weak revocation discipline. Practical implication: treat long-lived NHI credentials as residual access debt and tighten privilege scope at issuance.

Practical implication: reduce standing access by scoping NHI privileges narrowly and revoking credentials when the workload no longer needs them.

Why SaaS and AI growth make NHI governance harder

SaaS expansion and AI agent deployment multiply machine identities faster than traditional IAM processes can inventory them. Every integration, script or automation can introduce a new identity, and many platforms still do not distinguish these identities from human users. That creates identity sprawl, where visibility, ownership and review all degrade at the same time. In practice, the problem is not just volume. It is the mismatch between static governance models and rapidly generated identities that may be ephemeral, third-party or deeply embedded in production. Practical implication: build discovery and classification into your SaaS and automation estate before the sprawl becomes ungovernable.

Practical implication: classify and inventory machine identities continuously across SaaS, automation and AI estates before sprawl hides them.

Threat narrative

Attacker objective: The objective is to abuse persistent machine access to reach critical systems and data while blending into ordinary service traffic.

1. Entry begins when a machine identity is created or reused with credentials that persist beyond the original workload or integration purpose.
2. Escalation occurs when that identity has broad permissions and no effective lifecycle offboarding, giving an attacker or malicious insider durable access to connected systems.
3. Impact follows when the identity is used silently for data access, service disruption or lateral movement across production systems without human-style detection cues.

Breaches seen in the wild

• Dropbox Sign breach 2024: A compromised back-end service account gave attackers Dropbox Sign customer data, including API keys, OAuth tokens and MFA information.
• Cisco Active Directory credentials leak 2025: Kraken leaked Cisco Active Directory hashes, including service and krbtgt accounts; Cisco says they came from its 2022 breach, not a new one.

Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Human and nonhuman identity governance is diverging because the actor behaviour is diverging. Human IAM assumes interactive users, reviewable sessions and predictable login patterns. NHIs and AI agents operate through programmatic access, persistent credentials and automated execution, so the governance model must split along actor type rather than force one control plane to serve both. The practical conclusion is that identity programmes need separate policy, inventory and lifecycle paths for humans and machines.

Persistent machine credentials create identity blast radius, not just exposure risk. Once an API token, service account password or automation credential outlives the workload that created it, the problem is no longer simple authentication. It becomes residual access that can be reused, overextended or silently inherited across systems. That is why machine identity governance has to focus on revocation, ownership and access scope at the point of issuance and change.

Ephemeral infrastructure still leaves durable governance obligations. A short-lived workload does not remove the need for lifecycle control if its credentials are long-lived or if its permissions survive decommissioning. The assumption that access can be reviewed later is fragile when the identity is created by code and consumed by automation. Practitioners need to treat creation, scope and offboarding as one continuous control chain.

Machine identity sprawl is now a SaaS governance problem, not a niche security issue. Third-party platforms and integrations are generating identities faster than many teams can classify them, which means visibility and accountability increasingly depend on vendor cooperation. The governance question is not whether NHIs exist in the estate. It is whether the organisation can still explain who or what owns each one, why it exists and when it should disappear.

OWASP-NHI is becoming the right lens for a category that human IAM never covered well. The article’s emphasis on classification, rotation, offboarding and overprivilege maps directly to the controls that matter most for machine identities. That makes the topic a governance discipline, not just an operational hardening exercise. Practitioners should align controls to the identity type, not to the convenience of existing IAM assumptions.

From our research library:

• NHIs outnumber human identities by 25x to 50x in modern enterprises, according to the Ultimate Guide to NHIs.
• Only 5.7% of organisations have full visibility into their service accounts, according to the Ultimate Guide to NHIs.
• Read next: Guide to NHI Rotation Challenges

What this signals

Machine identity sprawl is now an operational governance problem, not a future risk. As SaaS and automation expand, the number of identities can rise faster than ownership, review and revocation processes can keep pace. That leaves security teams managing an estate where existence is easy to create and difficult to retire.

Human-centric access review will not scale to workloads that never stop running. The practical shift is to govern credentials at issuance and change, because continuous machine activity leaves too little meaningful review artefact after the fact. That is why lifecycle automation and privilege scoping need to move ahead of periodic certification.

Identity blast radius is the better mental model for NHIs than user risk scoring. A single overprivileged service account can expose multiple systems, vendors or data paths without triggering the controls designed for interactive users. The programme should measure how far one machine identity can reach, not how often it logs in.

For practitioners

• Classify human and nonhuman identities separately Tag service accounts, API tokens, automation credentials and AI agents as a distinct identity class in your inventory, then keep them out of user-only review paths.
• Tighten privilege at issuance Scope each machine identity to a single task or workload and avoid broad standing permissions that persist beyond the original business need.
• Automate NHI lifecycle and revocation Create provisioning, rotation and offboarding triggers for machine identities so credentials do not remain valid after a workload, integration or vendor relationship changes.
• Monitor machine activity as machine activity Tune detection for token use, API request volume, unusual resource scope and persistent background access instead of relying on human login baselines.
• Press SaaS providers for identity distinction Confirm that third-party platforms distinguish human users from NHIs and can support attested, just-in-time access for workload credentials.

Key takeaways

• Human and nonhuman identities require different governance models because they behave differently, authenticate differently and fail differently when controls are misapplied.
• The article cites a 144 to 1 machine-to-human ratio and two in five SaaS platforms that still cannot distinguish NHIs from people, which helps explain why sprawl is outpacing review.
• The strongest control shift is toward classification, narrow scoping, automated lifecycle management and short-lived access for machine identities.

Key terms

• Non-Human Identity (NHI): A digital identity assigned to a non-human entity such as a software application, service account, API key, bot, machine, or AI agent that enables it to authenticate and interact with systems without direct human involvement. NHIs now outnumber human identities in most enterprises by 25 to 50 times.
• Machine Identity Sprawl: Machine identity sprawl is the uncontrolled growth of non-human identities across teams, platforms, and business processes. It becomes a governance problem when identities are created faster than they can be inventoried, reviewed, rotated, or retired, leaving security teams with incomplete visibility and weak accountability.
• Just-in-time Credential Issuance: Just-in-time credential issuance creates access only when a request meets policy and then limits how long the credential remains valid. It reduces standing exposure, but it still depends on strong policy, accurate context, and reliable revocation handling.
• Identity Blast Radius: The amount of damage a compromised identity can cause across systems, data, and infrastructure. In NHI environments, it is shaped by permissions, network reach, and administrative capability rather than by the credential alone. Reducing blast radius is a containment strategy that limits lateral movement and data exposure.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity security are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building or maturing an IAM programme, it is worth exploring.