Why do API keys and tokens need non-human identity governance?

Because they behave like access-bearing identities, not static configuration values. If they are long-lived, over-scoped, or shared across workloads, they can be reused by attackers exactly as legitimate systems use them. Governance should therefore cover ownership, scope, rotation, monitoring, and retirement.

Why This Matters for Security Teams

API keys and tokens often sit outside the controls applied to employee accounts, yet they can grant equal or greater access to production systems, cloud resources, and sensitive data. Treating them as simple configuration values creates a blind spot: there may be no joiner, mover, leaver process, no explicit owner, and no reliable way to prove who approved their scope. That is why non-human identity governance belongs alongside access governance, not after it.

Security teams also underestimate how quickly token sprawl turns into operational risk. A key embedded in code, copied into a ticket, or reused across multiple services becomes difficult to trace and harder to retire safely. Guidance from the NIST Cybersecurity Framework 2.0 reinforces the need to identify assets, manage access, and monitor for misuse, which maps directly to secrets and token governance. In practice, many security teams encounter token abuse only after an incident review reveals that the token was never owned, rotated, or logged as an identity in the first place.

How It Works in Practice

Non-human identity governance starts by inventorying every API key, access token, service account credential, certificate, and automation secret, then assigning business and technical ownership. The key question is not only where the secret is stored, but what it can do, which workload uses it, how it is authenticated, and how its use is monitored. Mature programmes apply the same lifecycle thinking used for human identities: issuance, approval, use, rotation, revocation, and retirement.

In practice, this means classifying tokens by sensitivity and blast radius. High-risk secrets should be short-lived, tightly scoped, and issued through controlled workflows rather than pasted into application configs. Best practice is evolving toward ephemeral credentials, workload identity federation, and just-in-time access where feasible. The OWASP Secrets Management Cheat Sheet is useful here because it emphasizes secure storage, rotation, and exposure reduction, while CISA identity and access management guidance reinforces least privilege and strong monitoring.

• Maintain a complete inventory of secrets and the workloads that depend on them.
• Bind each secret to a named owner, service, environment, and approved purpose.
• Use least privilege for scopes, roles, and token claims.
• Rotate on a fixed schedule and after every suspected exposure.
• Alert on anomalous use, such as new geographies, unusual frequency, or unexpected API paths.
• Retire secrets promptly when applications are decommissioned or re-architected.

These controls work best when secrets are managed through CI/CD, cloud IAM, or secret managers with audit logging. They become less reliable when developers bypass central controls, copy tokens into local files, or share the same token across multiple microservices because attribution and revocation then become ambiguous.

Common Variations and Edge Cases

Tighter token governance often increases operational overhead, requiring organisations to balance security assurance against deployment speed and service availability. That tradeoff is most visible in legacy systems, where hard-coded credentials, long-lived API keys, and batch jobs may not support frequent rotation without redesign. Current guidance suggests prioritising the highest-risk secrets first, rather than attempting a blanket reset of every credential at once.

There is also no universal standard for how much identity context a token must carry. Some environments rely on opaque secrets plus backend policy, while others use signed short-lived tokens with rich claims. The important point is governance, not token format alone: scope must be constrained, usage must be observable, and ownership must be explicit. In cloud-native and agentic AI environments, this becomes even more important because AI agents and automation services can chain tokens across tools and APIs, increasing blast radius if one credential is exposed.

Regulated environments may need stronger evidence of control effectiveness, especially where customer data or financial workflows are involved. In those cases, token governance should be aligned with NIST Cybersecurity Framework 2.0 for monitoring and response, and with identity assurance practices that support traceability. The practical test is simple: if a token cannot be named, owned, monitored, and retired, it is not governed well enough to be trusted in production.

Related resources from NHI Mgmt Group

• How should security teams handle API keys and tokens as part of identity governance?
• Should organisations govern API keys and service tokens like other non-human identities?
• How should security teams govern non-human identities at scale?
• Why do AI agents make non-human identity governance harder?