Human access is governed around people, sessions, and behaviour, while machine access is governed around workloads, secrets, and execution paths. Machine identities need stronger lifecycle handling because they operate continuously, scale automatically, and are often embedded in systems that outlive the teams managing them.
Why This Matters for Security Teams
Securing human access and securing machine access are not variations of the same problem. Human access is usually bounded by sessions, prompts, and observable behaviour. Machine access is driven by workloads, secrets, automation paths, and machine identity that can execute continuously without a human in the loop. That difference changes how access is granted, monitored, rotated, and revoked. The risk is not just exposure of credentials, but silent persistence through service accounts, API keys, certificates, and tokens that remain valid long after they should have been retired.
NHIMG research shows the scale of this problem in practice: NHIs outnumber human identities by 25x to 50x in modern enterprises, and 97% carry excessive privileges. The same research also notes that only 5.7% of organisations have full visibility into their service accounts, which means many teams are defending what they cannot fully inventory. For practitioners, the implication is straightforward: human-centric access controls do not map cleanly onto autonomous or always-on systems, especially where secrets are embedded in pipelines or applications. Current guidance from the OWASP Non-Human Identity Top 10 is that machine access must be governed as a distinct identity class.
In practice, many security teams discover machine exposure only after a leaked key, overprivileged service account, or forgotten integration has already been abused.
How It Works in Practice
Human access is typically secured through interactive controls such as MFA, password policy, conditional access, and session monitoring. Machine access needs a different model because the “user” is a workload. The identity primitive becomes the workload itself, with cryptographic proof of what it is, what it is allowed to do, and for how long. That usually means short-lived tokens, certificate-based identity, and policy decisions that happen at request time rather than being fixed at onboarding.
A mature approach separates identity from standing privilege. Instead of assigning broad, durable rights to a service account, the system issues JIT credentials for a single task or bounded window, then revokes them automatically. That approach is consistent with guidance in the Ultimate Guide to NHIs, which treats lifecycle control, rotation, and offboarding as core security functions. It also aligns with the OWASP Non-Human Identity Top 10, which emphasises that secrets sprawl and excessive privilege are recurring failure modes.
- Use workload identity rather than shared credentials wherever possible.
- Prefer short TTL secrets, ephemeral tokens, and automated rotation over static keys.
- Evaluate authorisation with context, such as workload, environment, destination, and action.
- Log issuance, use, and revocation as identity events, not just infrastructure events.
- Continuously inventory service accounts, API keys, certificates, and CI/CD secrets.
For implementation, teams often pair policy-as-code with identity-bound tokens and workload attestation, so the system decides at runtime whether the workload can perform the requested action. These controls tend to break down when legacy applications depend on shared credentials or when long-running batch jobs cannot renew tokens safely because the execution environment was never designed for ephemeral identity.
Common Variations and Edge Cases
Tighter machine-access controls often increase operational overhead, requiring organisations to balance stronger containment against release velocity and uptime requirements. That tradeoff is most visible in environments with legacy middleware, multi-cloud integrations, or vendor-managed jobs that still expect long-lived secrets. In those cases, best practice is evolving rather than settled, and there is no universal standard for exactly how fast every secret should rotate.
Some platforms can support identity-native workloads such as SPIFFE/SPIRE or OIDC-based service authentication, while others require compensating controls like vault-based secret brokerage and aggressive rotation schedules. The key distinction is that machine access should be measured by execution context, not by a person’s role. Human access reviews ask whether a user still needs a permission; machine access reviews ask whether a workload still exists, still needs that secret, and still has the minimum scope required.
NHIMG’s 52 NHI Breaches Analysis is a useful reminder that the failures are usually procedural as much as technical: forgotten credentials, broad entitlements, and weak offboarding. That is why the strongest programs treat machine identity as a lifecycle problem, not just a secrets problem, and why the same control set rarely works equally well for both humans and machines.
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 address the attack and risk surface, while NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-01 | Defines core NHI identity and secrets risks for machine access. |
| NIST CSF 2.0 | PR.AC-1 | Access control differs for people versus workloads and needs mapping. |
| NIST AI RMF | AI RMF helps distinguish autonomous machine behaviour from human access. |
Inventory workloads, secrets, and service accounts, then remove shared or standing machine credentials.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on July 5, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
