Non-Human and Agentic Identities are digital identities used by systems, software, and autonomous AI agents rather than people. They include service accounts, API keys, tokens, certificates, and agent credentials that allow machines to authenticate, authorize actions, and access resources across cloud, applications, data, and infrastructure.
What Non-Human and Agentic Identities Are For
Non-human and agentic identities are the access layer that lets software, services, and autonomous agents act in controlled ways without using a person’s account. They are the practical basis for machine-to-machine trust, delegated authority, and system-to-system actions across cloud and application environments.
For AI agents, the identity question is more than authentication alone. It also includes what the agent is allowed to do, which requests need human approval, and how much standing access it should retain once a task is complete. AI Agent Authorisation Guide is a useful companion for understanding that control boundary.
Where These Identities Appear
These identities show up wherever workloads, integrations, or automations need to prove who or what they are. Common forms include service accounts, workload identities, API credentials, tokens, certificates, and delegated agent credentials used by CI/CD, cloud services, data pipelines, SaaS integrations, and autonomous tools.
Their importance grows as organisations move from static application credentials to short-lived, task-scoped, and policy-driven access. That shift reduces broad implicit trust, but it also makes identity inventory and lifecycle ownership harder unless the organisation can track every non-human principal.
For teams formalising this model, Agentic AI Identity Guide explains how agents get, use, and retire identities, while Agent Identity Standards Tracker helps map the evolving standards landscape around agent identity.
Why Non-Human Identity Is Harder to Govern
Unlike human identities, non-human identities often operate at machine speed, in large numbers, and across multiple environments. That makes them easy to create and easy to forget, especially when tokens, keys, and certificates are embedded in code, pipelines, or orchestration layers rather than managed through a central owner.
Agentic identities add another layer of complexity because the same principal may request tools, chain actions, and act across multiple systems. The governance challenge is not only proving identity, but also constraining delegation, limiting reuse, and deciding when an autonomous action is acceptable without direct human intervention.
Zero Trust for AI Agents is relevant here because it frames the need to verify the principal and the request each time, rather than assuming an agent remains safe after initial onboarding.
Identity Controls That Matter Most
Strong practice starts with inventory, ownership, and purpose. Every non-human identity should have a known owner, a defined purpose, a bounded scope, and a clear retirement path. Without that, access sprawl becomes the default and governance turns reactive.
Controls should also favor least privilege, short-lived credentials where possible, and policy decisions tied to the action being requested rather than a broad standing grant. For agents, approval gates and scoped delegation matter because the identity may be technically valid even when the action is not appropriate.
AI Agent Observability, Audit and Incident Response Guide is a strong follow-on for logging, attribution, and revocation, while Shadow AI and AI Agent Discovery Guide helps organisations find identities they did not know existed.
Risk and Threat Considerations
Non-human and agentic identities are attractive targets because a single compromised secret, token, or certificate can unlock machine-scale access. The main risk is not just account takeover, but silent abuse of automation, lateral movement through trusted integrations, and persistence through long-lived credentials that are rarely reviewed.
Failure mechanism: Attackers exploit exposed or over-privileged machine credentials, then reuse the trust those credentials already have with cloud services, APIs, data platforms, or agent toolchains.
Impact: The result can be unauthorized access, data exfiltration, hidden automation abuse, privilege escalation, and difficult post-incident recovery because the compromised identity may be embedded across many systems.
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 and OWASP Agentic AI Top 10 address the attack and risk surface, while NIST SP 800-53 Rev 5 sets the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-02 — Secret Leakage | Non-human identities depend on secrets, tokens, and keys that can be exposed. |
| NHI-05 — Overprivileged NHI | The term centers on non-human principals and the scope of their access. | |
| NHI-07 — Long-Lived Secrets | Non-human identities often rely on credentials that outlive their intended use. | |
| Recommendation — Store and rotate machine secrets so exposed credentials cannot be reused. Constrain machine identities to least privilege and task-scoped access. Replace long-lived machine secrets with short-lived or automatically rotated credentials. | ||
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | Agentic identities can be misused when authority exceeds the task or request. |
| ASI10 — Rogue Agents | Uncontrolled agents create identity and access risk when they operate outside governance. | |
| Recommendation — Bind agent actions to per-request authorization and narrow delegated authority. Detect and disable unmanaged agents before they execute privileged actions. | ||
| NIST SP 800-53 Rev 5 | IA-5 — Authenticator Management | Machine credentials, tokens, and certificates require lifecycle control and protection. |
| IA-9 — Service Identification and Authentication | Service and workload identities are the core subject of non-human identity governance. | |
| AC-6 — Least Privilege | Non-human identities should only receive the permissions needed for their task. | |
| Recommendation — Manage issuance, storage, rotation, and revocation for all authenticators. Authenticate services and workloads with controlled, non-user credentials. Limit each machine identity to the minimum access required to perform its function. | ||
Practitioner Guidance
Why practitioners should care: The hardest part of non-human identity security is usually not the initial credential, it is the lifecycle around it. If ownership, rotation, and retirement are unclear, even well-designed controls degrade quickly as systems scale.
What to watch for: Look for orphaned service accounts, shared credentials, excessive token lifetime, and agents that inherit broad human permissions without a task-specific boundary. These are early signs that identity sprawl is becoming an operational control problem.
Practitioner takeaway: Treat every non-human principal as a governed identity with an owner, a purpose, and a revocation path, not as a convenient technical artifact.
Related resources from NHI Mgmt Group
- Why do non-human identities create special governance problems in agentic systems?
- Should organisations treat agentic security tools like non-human identities?
- What breaks when organisations rely on static credentials for agentic AI and other non-human identities?
- How should security teams implement AI discovery for agentic AI environments without losing control of non-human identities?
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Reviewed and updated by the NHIMG editorial team on October 23, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org