What Is a Non-Human Identity (NHI)? A Complete Guide

Most of the identities in your environment are not people. Every time software authenticates to another system without a person at the keyboard, it uses a non-human identity. Service accounts, API keys, OAuth tokens, secrets, cloud workloads, and now AI agents are all non-human identities, and they already outnumber human users in most organizations by a wide margin. As teams race to deploy autonomous AI agents, that gap is widening fast.

This guide explains what a non-human identity (NHI) is, the types you are likely running today, why NHIs have become one of the largest security blind spots in the enterprise, and how to manage and secure them. It is written for security leaders, IAM and platform engineers, and developers shipping agentic features who suddenly need to give an AI agent an identity and a tightly scoped set of permissions.

What is a non-human identity?

A non-human identity (NHI), sometimes written as non human identity, is a digital identity that software uses, rather than a person, to authenticate and gain access to systems, data, and other services. A human identity belongs to an employee, contractor, or customer. A non-human identity belongs to a machine actor: an application, a script, a service account, a workload, a bot, or an AI agent.

Definition: A non-human identity is any credentialed machine actor, such as a service account, API key, OAuth token, workload, or AI agent, that authenticates and acts in your systems without a person directly driving it.

The defining trait of an NHI is autonomy from a human session. A person logs in, does some work, and logs out. A non-human identity often runs continuously, authenticates programmatically, and holds standing access that nobody is actively watching. That difference is the root of nearly every NHI security problem.

Types of non-human identities (with examples)

"Non-human identity" is an umbrella term. In practice it covers a wide range of credentials and machine actors. The most common non-human identity examples include:

Type	What it is	Typical use
Service account	An account created for an application or service, not a person	Background jobs, system-to-system access
API key	A static token that authenticates calls to an API	Third-party integrations, internal services
OAuth token	An access or refresh token granting scoped, delegated access	App-to-app authorization, agent delegation
SSH key	A cryptographic key pair for machine-to-machine login	Server access, automation, CI/CD
X.509 certificate	A cryptographic identity used for mutual TLS	Service mesh, workload authentication
Secret	Any sensitive credential string (passwords, tokens, connection strings)	Application configuration, integrations
RPA bot	A robotic process automation agent acting on a system	Automated workflows, data entry
Cloud workload	A container, function, or VM with an attached identity	Cloud-native applications, microservices
AI agent	An autonomous or semi-autonomous AI system that calls tools and APIs	Agentic workflows, copilots, automation

The last row is the one changing the fastest. AI agents are a new and especially dynamic class of non-human identity, and we cover them in depth below.

Why non-human identities matter now

Non-human identities are not new. What is new is their scale and their risk profile. Industry reports consistently show machine identities outnumbering human ones by large multiples. Estimates range from roughly 25 to 1 in many enterprises to over 100 to 1 in cloud-heavy environments, and some organizations report ratios higher still. ManageEngine's 2026 Identity Security Outlook, for example, found organizations reporting machine-to-human ratios that reached into the hundreds.

That population keeps growing, and the credentials behind it leak constantly. GitGuardian's 2026 secrets-sprawl research reported that nearly 29 million new hardcoded secrets were exposed on public GitHub in 2025 alone, a 34 percent increase year over year. It also found that a majority of secrets first exposed back in 2022 were still valid in early 2026. Old secrets do not die quietly.

The inflection point in 2026 is agentic AI. Every AI agent you deploy is a new non-human identity that needs to authenticate, call tools, and access data. A quiet service account does roughly the same thing every day. An agent can spin up sub-tasks, chain calls across systems, and make decisions on its own. Agentic AI turns the non-human identity problem from a slow-growing backlog into a live, accelerating one.

Human vs non-human identity

Treating non-human identities like human ones is where many programs fail. The two behave differently across almost every dimension, which is why human-centric controls such as multi-factor authentication and single sign-on do not map cleanly onto machines.

Dimension	Human identity	Non-human identity
Count per org	Hundreds to thousands	Tens of thousands and up
Authentication	Password, MFA, SSO	API keys, tokens, certs, keys
MFA applicable?	Yes	Generally no second factor
Lifecycle	HR-driven joiner, mover, leaver	Often created ad hoc, rarely retired
Behavior	Has "normal hours" patterns	Runs 24/7, no baseline
Ownership	The person	Frequently unknown or orphaned

There is usually no second factor and no human to challenge. So a compromised non-human identity hands an attacker exactly the access that identity holds, with no friction. That is why non-human identity authentication has to lean on cryptography, short credential lifetimes, and tight scoping rather than on prompting a user.

The non-human identity lifecycle

Securing NHIs starts with managing their full lifecycle, the same way mature programs manage human joiners, movers, and leavers.

Discovery and inventory

You cannot secure what you cannot see. The first step is finding every service account, key, token, and agent across cloud, code, and CI/CD, and recording an owner for each. Most teams are surprised by how many they find.

Provisioning

New identities should be created through a governed process, not ad hoc. Standards such as SCIM help automate provisioning and deprovisioning, and applying that discipline to machine and AI identities (sometimes discussed as SCIM for AI) keeps the inventory authoritative.

Credentials and rotation

Credentials should be vaulted, never hardcoded, and rotated automatically. The strongest pattern is to avoid long-lived secrets entirely in favor of short-lived, automatically issued credentials.

Monitoring

Because NHIs have no normal behavior pattern, monitoring focuses on anomalies: unexpected scopes, new destinations, off-pattern volume. Detailed logs should flow to your SIEM and SOC.

Offboarding and deprovisioning

Identities that are no longer needed must be revoked promptly. Stale, still-valid credentials are one of the most exploited gaps in the enterprise.

Risks and attack vectors

The clearest map of non-human identity attacks is the OWASP Non-Human Identities Top 10, published in 2025, which ranks the most pressing NHI risks using real-world breach data. The ten risks are:

1. Improper offboarding: identities that stay active beyond their useful life.
2. Secret leakage: high-impact credentials exposed in code, logs, or configs.
3. Vulnerable third-party NHI: compromised integrations enabling supply-chain attacks.
4. Insecure authentication: weak protocols enabling takeover or escalation.
5. Overprivileged NHI: identities holding far more access than they need.
6. Insecure cloud deployment configurations: over-privileged CI/CD pipelines.
7. Long-lived secrets: credentials that never expire or rotate.
8. Environment isolation: reusing identities across test and production.
9. NHI reuse: one identity shared across many workloads.
10. Human use of NHI: people borrowing machine credentials, blurring accountability.

A few themes run through the whole list. Long-lived, leaked, and over-permissioned credentials are the root cause of most non-human identity compromise, and orphaned identities give attackers persistence. Permission drift, where an identity quietly accumulates access over time, makes the overprivileged-NHI risk worse the longer an identity lives. The more an identity can do, the more an attacker inherits when it is compromised.

How non-human identity management works

So how do you bring tens of thousands of machine actors under control? That is the job of non-human identity management (NHIM): giving machine identities the same kind of governance humans already have, with a known inventory, governed credentials, least-privilege access, monitoring, and clean offboarding. In practice it combines several capabilities.

• Discovery and inventory across cloud, code, and pipelines, with an owner of record for every identity.
• Secrets vaulting so credentials live in a managed store, never in source code or config files.
• Short-lived, ephemeral credentials issued on demand rather than static secrets. Workload identity frameworks such as SPIFFE issue short-lived, cryptographically verifiable identity documents (SVIDs) so workloads can authenticate without any long-lived secret.
• Just-in-time (JIT) access so an identity holds elevated permissions only for the moment it needs them.
• Delegation for multi-step actions. OAuth 2.0 Token Exchange (RFC 8693) preserves a delegation chain so you can see which actor initiated an action on whose behalf, the foundation of secure agent OAuth flows.
• Identity Security Posture Management (ISPM) and identity observability to continuously assess exposure and flag drift.

Together these turn a sprawl of static secrets into a governed system where every machine actor is known, scoped, observed, and revocable.

Fine-grained permissions and least privilege for NHIs

Inventory and vaulting reduce the chance a credential leaks. Fine-grained permissions reduce the damage if one does. The principle is least privilege: every non-human identity should hold the minimum access required for its task, and nothing more.

For machine identities this is harder than it sounds. Static service accounts tend to be granted broad access once and never trimmed, and over time they accumulate more through permission drift. The fix is to model access with fine-grained authorization, whether through role-based access control (RBAC), attribute-based access control (ABAC), or relationship-based access control (ReBAC), and to express access as fine-grained access policies that can be scoped per workload and revoked instantly.

AI agents push this further. Effective agent permissions are scoped per task and per resource, granted just in time, and revoked when the task ends. An agent that is compromised mid-run cannot then reach beyond the narrow slice of access it was given. This is the heart of AI agent access control, and it is where non-human identity security and agent identity converge. For a worked example in an agent gateway, see our guide to MCP access control.

This is exactly the problem agen.co is built for: giving every AI agent a scoped, least-privilege, revocable identity so autonomous systems can act without becoming your largest standing risk.

AI agents: the fastest-growing non-human identity

AI agents are non-human identities, but they are not like the service accounts that came before them. Traditional NHIs are static and predictable. Agentic AI non-human identities are dynamic, ephemeral, and often self-directed. An agent can decide what to do next, spawn sub-tasks, and call tools and APIs in combinations nobody scripted in advance.

That autonomy changes the identity requirements. Securing an AI agent calls for:

• A real agent identity, not a shared key. Each agent should have its own verifiable identity so its actions are attributable.
• Strong agent authentication rooted in cryptography and short-lived credentials rather than a static token. When agents connect through the Model Context Protocol, this maps onto MCP authentication.
• Single sign-on for agents, so agents authenticate to the systems they use through governed flows instead of copied secrets.
• Scoped, just-in-time permissions per task, the agent-specific application of least privilege described above.
• Governed enrollment. Standards such as OAuth Dynamic Client Registration let agents register as clients through a controlled process rather than being hand-provisioned with long-lived credentials.
• A preserved delegation chain so that when an agent acts on a user's behalf, you can trace the action back to the human who initiated it.

The standards landscape is moving quickly to support this. The Model Context Protocol, the emerging way agents connect to tools, adopted OAuth 2.1 in its 2025 specification, and the IETF's WIMSE work explores treating agents as workloads with SPIFFE-based identities. The direction is clear. Agents should be first-class identities, governed like any other non-human actor, only with tighter, shorter-lived, more closely watched access. Treating agent identity security as an afterthought is how organizations turn a productivity gain into a breach.

Non-human identity governance

Tools alone do not solve the problem. Non-human identity governance is the policy and accountability layer on top of management: deciding who may create an identity, what it may access, how long it lives, and who answers for it.

Good governance rests on a few commitments. Every identity has an owner of record, so there are no orphans. There is an authoritative registry of all non-human identities, not a guess. Access is granted by policy rather than by exception, and every action is auditable. The Non-Human Identity Management Group (NHIMG) and OASIS have advanced this enrollment-and-lifecycle view, the Cloud Security Alliance has published agentic identity governance frameworks, and NIST launched an AI Agent Standards Initiative in 2026 that includes agent identity and authorization. These efforts point to the same conclusion. Non-human identity governance has to be a named program, not a side effect of whoever happened to create the credential. Ungoverned agents are effectively shadow AI, machine actors operating outside any policy or oversight.

Best practices for managing non-human identities

The non-human identity best practices that consistently reduce risk are straightforward to state, even if they take effort to implement:

• Eliminate long-lived secrets. Replace static keys with short-lived, automatically issued credentials wherever possible. This single change closes the most common breach path.
• Vault everything. No secret should live in source code, config files, or a developer's machine.
• Enforce least privilege with fine-grained permissions. Scope each identity to its task and revoke access it no longer needs.
• Use just-in-time access. Grant elevated permissions only for the moment they are required.
• Maintain a complete inventory with owners. Discover every NHI and assign an owner of record.
• Monitor and audit continuously. Send detailed logs to your SIEM and alert on anomalies and drift.
• Automate offboarding. Revoke identities the instant they are no longer needed.
• Treat AI agents as first-class identities. Give every agent its own scoped, governed, revocable identity from day one.

Implementation checklist

Use this checklist to assess where your program stands today:

• We have discovered and inventoried our non-human identities, including AI agents.
• Every NHI has an owner of record.
• No secrets live in code, configs, or repositories.
• Long-lived credentials are being replaced with short-lived ones.
• Permissions are scoped to least privilege and reviewed for drift.
• Just-in-time access is used for elevated permissions.
• NHI activity is logged and monitored for anomalies.
• Offboarding revokes identities promptly and automatically.
• AI agents have their own identities, authentication, and scoped permissions.

Frequently asked questions

What is a non-human identity?

A non-human identity is a digital identity that software, rather than a person, uses to authenticate and access systems. Examples include service accounts, API keys, OAuth tokens, certificates, cloud workloads, and AI agents.

What are examples of non-human identities?

Common non-human identity examples are service accounts, API keys, OAuth tokens, SSH keys, X.509 certificates, secrets, RPA bots, cloud workloads and containers, and AI agents.

What is the difference between a human and a non-human identity?

A human identity belongs to a person and is typically protected with passwords, MFA, and SSO. A non-human identity belongs to a machine actor, usually authenticates with keys or tokens, runs continuously, has no second factor, and is often created ad hoc and rarely retired.

Are AI agents non-human identities?

Yes. An AI agent is a non-human identity, and a particularly dynamic one. Unlike static service accounts, agents are ephemeral and self-directed, so they need their own verifiable identity, strong authentication, and tightly scoped, just-in-time permissions.

Why are non-human identities a security risk?

NHIs usually have no MFA, run unattended, often hold excessive privileges, and are rarely offboarded. A leaked or orphaned credential gives an attacker its full access with no friction, which is why machine identities have become a leading breach vector.

How many non-human identities does an organization have?

Far more than humans. Industry reports put machine-to-human ratios anywhere from roughly 25 to 1 up to more than 100 to 1, with cloud-heavy and AI-heavy organizations at the high end and climbing.

What is non-human identity management (NHIM)?

Non-human identity management is the practice of discovering, governing, securing, and offboarding machine identities, combining inventory, secrets vaulting, least-privilege access, monitoring, and lifecycle controls.

How do you secure non-human identities?

Eliminate long-lived secrets, vault credentials, enforce least privilege with fine-grained permissions, use just-in-time access, maintain a full inventory with owners, monitor continuously, automate offboarding, and treat AI agents as first-class identities.

What is the OWASP Non-Human Identities Top 10?

It is a 2025 list, ranked from real-world breach data, of the ten most pressing NHI risks, including improper offboarding, secret leakage, vulnerable third-party NHI, insecure authentication, overprivileged NHI, insecure cloud configurations, long-lived secrets, environment isolation, NHI reuse, and human use of NHI.

How is securing an AI agent different from securing a service account?

A service account is static and predictable, so a fixed, scoped credential is often enough. An AI agent is dynamic and self-directed, so it needs a verifiable per-agent identity, cryptographic authentication, per-task just-in-time permissions, governed enrollment, and a preserved delegation chain back to the human who initiated the action.

Related resources

Continue deeper into the AI agent identity and access topic:

• What Are AI Agents? The complete guide to how they work, types, and examples.
• What Is Agentic AI? A complete guide to autonomous AI systems.
• What Is an AI Agent Platform? Capabilities, architecture, and how to choose one.
• MCP Access Control: securing AI agent gateways with scoped permissions.
• What Is MCP Authentication? How agents authenticate when connecting to tools.
• MCP Security: risks and best practices for agent-tool connections.
• Shadow AI: what it is, why it is risky, and how to govern ungoverned agents.

Give your AI agents a secure identity

Non-human identities are no longer a back-office cleanup task. With AI agents multiplying the machine population, every autonomous actor needs its own scoped, governed, revocable identity. See how agen.co gives AI agents first-class identities with fine-grained, least-privilege permissions and full auditability, the foundation for AI agent workforce management at scale.