Human and non-human identities need different control models

At a glance

What this is: This blog post explains why human and non-human identities need different control models, with the main finding that NHI access is often mismanaged because human-centric IAM assumptions do not fit machine credentials and service identities.

Why it matters: It matters because IAM, IGA and PAM teams need to govern API keys, tokens, service accounts and machine identities with lifecycle and visibility controls that are designed for non-human behaviour, not employee login patterns.

By the numbers:

• 54% of executives have reported that inappropriate access rights granted to non-human identities have led to security issues.

Context

Human identity controls are built around people, login events and review cycles. That model breaks down when the subject is a service account, API key or token that can be created, copied and used outside normal human workflows.

This article focuses on the governance gap between human IAM and NHI management. The central issue is not just that NHIs are growing in number, but that they carry access patterns, visibility problems and lifecycle risks that require different controls.

Entro Security frames the problem as a security management issue rather than a tooling issue: organisations need to know what their NHIs are, who owns them and how much access they actually retain over time.

Key questions

Q: How should teams govern non-human identities in AI-heavy environments?

A: Teams should govern non-human identities the same way they govern other privileged assets: assign ownership, minimise scope, rotate credentials regularly, and monitor for abnormal use. The key difference is speed. AI-driven workflows can exploit exposed access quickly, so detection and revocation must be automated and tied to lifecycle controls.

Q: What problem does ownership attribution solve for service accounts and API keys?

A: It closes the gap between exposure detection and accountable remediation. Many organisations can find the secret, but not the human who introduced it, maintains it, or can safely replace it. Ownership attribution gives security teams a practical way to assign action without relying on informal knowledge that disappears during staff changes.

Q: What are the signs that NHI governance is failing in an enterprise?

A: Common warning signs include unclear ownership for service accounts, secrets stored in code or configuration instead of managed vaults, infrequent rotation, and weak offboarding of API keys. Other red flags are excessive permissions, third-party exposure without controls, and low visibility into where non-human identities exist or how they are used across the stack.

Q: How do organisations reduce the risk from standing NHI access?

A: Organisations reduce risk by limiting access scope, centralising secret governance, and establishing clear lifecycle ownership for every machine identity. Standing access becomes dangerous when it is invisible and persistent. The goal is to make NHI credentials easy to find, hard to overuse and simple to revoke when the workload changes.

Technical breakdown

Why human IAM assumptions fail for non-human identities

Human IAM assumes an interactive subject, a known user population and reviewable login behaviour. Non-human identities do not behave that way. API keys, OAuth tokens, service accounts and machine identities can be provisioned for applications, reused across systems and left active long after their original purpose changes. That creates a control mismatch: MFA, password rules and user-centric access reviews are designed for people, not for secrets and delegated machine access. Once NHIs are treated like human users, organisations lose the ability to govern them at the right point in their lifecycle.

Practical implication: build separate control paths for NHI inventory, ownership and lifecycle governance instead of extending human IAM workflows unchanged.

Why visibility and inventory are the first governance problem

The article makes clear that many organisations do not know how many NHIs they have, which means they cannot manage entitlement scope with confidence. Discovery is harder because NHIs are spread across applications, cloud platforms, backups, legacy systems and supply chain integrations. Without inventory, teams cannot tell whether an identity is active, dormant, over-provisioned or orphaned. Visibility is therefore not just a reporting requirement. It is the precondition for any meaningful access control, because you cannot review, rotate or retire an identity that you cannot reliably find.

Practical implication: establish authoritative NHI discovery and ownership records before trying to tighten access or automate remediation.

How secrets and least privilege change the control model

For NHIs, the security boundary is usually the secret or token, not the user session. That means credential rotation, scope limitation and centralised secrets governance matter more than the checks used for employees at sign-in. Least privilege still applies, but it has to be expressed as narrow machine permissions, limited token scope and controlled reuse across services. The article’s examples show why over-provisioned machine identities create outsized risk: once an NHI has too much access, compromise or misuse can affect systems without the friction that human controls would normally introduce.

Practical implication: move NHI governance toward secret-centric controls, constrained scopes and regular entitlement review.

NHI Mgmt Group analysis

NHI governance is a separate control discipline, not a subset of human IAM. Human-centric controls assume a person, a login and a review cycle. NHIs break that assumption because they are often created for applications, distributed through automation and left active across multiple systems. The implication is that identity programmes need distinct ownership, visibility and lifecycle rules for machine access.

Visibility is the decisive control gap for NHIs. An organisation cannot govern what it cannot inventory, and the article’s central risk is hidden or poorly understood machine identities. When teams lack a complete view of API keys, service accounts and tokens, they cannot assess exposure, scope or drift. The practitioner conclusion is that discovery comes before policy enforcement.

Standing access for NHIs creates persistent blast radius. Once a service identity is over-provisioned, it can outlive the business need that justified it and remain usable across backups, integrations and cloud workloads. That is why secret governance and least privilege matter together. The conclusion for practitioners is to treat every non-human credential as a standing path to impact unless its scope is actively constrained.

Human review cadences are too slow for machine access realities. Regular access audits help, but they do not solve the problem if identities are created and reused faster than review cycles can see them. This is where NHI security diverges from employee IAM: the control point must move closer to issuance, ownership and rotation. Practitioners should redesign governance around the lifecycle of the secret, not just the identity record.

Secret management is the operating model behind NHI security. The article’s strongest practical message is that controlling the secret is often more important than managing the label attached to it. That shifts the governance conversation from authentication experience to credential stewardship, with direct implications for cloud access tokens, API keys and machine accounts. The practitioner conclusion is to centralise secrets oversight and make ownership explicit.

From our research library:

• NHIs outnumber human identities by 25x to 50x in modern enterprises, according to the Ultimate Guide to NHIs.
• Read next: Top 10 NHI Issues

What this signals

Machine identity governance now sits alongside human IAM as a distinct operating discipline. The practical shift for security teams is to stop treating API keys, service accounts and tokens as edge cases. Once NHIs outnumber human identities by 25x to 50x in modern enterprises, the operating model has to cover ownership, visibility and lifecycle with the same seriousness as user access.

Secret-centric control is the right lens for NHI risk. Human authentication controls can improve assurance for employees, but they do not solve the problem of long-lived machine access. For programmes that still rely on user-era assumptions, the next step is to rework governance around inventory, rotation and revocation rather than around sign-in experience.

For practitioners

• Map every non-human identity Create and maintain an authoritative inventory of API keys, service accounts, OAuth tokens and machine identities, including owners, purpose and current access scope.
• Separate NHI and human governance workflows Do not reuse employee access review, password policy or MFA workflows as the primary control model for machine identities and secrets.
• Tighten secret scope and rotation Reduce token and key permissions to the minimum required for the workload and review rotation, revocation and reuse on a defined schedule.
• Assign explicit ownership for every NHI Make one team or named owner accountable for each machine identity so orphaned credentials and legacy access do not persist unnoticed.
• Monitor for over-provisioned machine access Use continuous monitoring to identify NHIs that retain broader permissions than their current function requires, especially across legacy systems and cloud integrations.

Key takeaways

• Non-human identities need a different control model because they do not behave like employee accounts and cannot be governed reliably with user-centric IAM assumptions.
• The article ties NHI access problems to real security outcomes, including the reported 54% figure for executives who have seen inappropriate NHI access rights cause issues.
• The strongest control response is to combine inventory, ownership, least privilege and secret governance so machine access can be found, reviewed and removed on time.

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.
• Secrets Governance: Secrets governance is the discipline of controlling where credentials are stored, who can use them, how long they remain valid, and how they are removed. It links discovery, rotation, offboarding, and auditability so that a secret does not outlive the legitimate need for access.
• Standing Access: Standing access is persistent privilege that remains available without fresh approval or contextual checks. In NHI environments, standing access usually appears as long-lived tokens, reusable service accounts, or broad roles attached to automation. It is convenient operationally, but it expands risk when conditions change or secrets leak.
• Identity Inventory: Identity inventory is the process of discovering and recording every identity that can access systems or data. For NHIs, it includes owner, purpose, privilege scope, lifecycle status, and where the credential is used. Without inventory, governance, audit evidence, and incident response all become partial and unreliable.

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.