They operate at machine speed, often without human review, and they accumulate permissions over time. That makes it harder to verify intent, ownership, and scope. Teams need lifecycle governance, discovery, and policy enforcement for orphaned or overprivileged identities, especially where automation and DevOps workflows create frequent change.
Why This Matters for Security Teams
Service accounts, APIs, and machine identities are not just “non-interactive users.” They are the enforcement layer for automation, CI/CD, data exchange, and application-to-application trust. That makes them central to zero trust, because Zero Trust assumes every request must be verified, scoped, and continuously re-evaluated. NIST SP 800-207 Zero Trust Architecture makes the point clearly: trust should not be implicit, even for internal workloads.
The difficulty is that machine identities scale faster than human governance. They are created by code, copied across environments, and often left active long after the owner forgets them. NHIMG’s Ultimate Guide to NHIs notes that NHIs outnumber human identities by 25x to 50x in modern enterprises, and only 5.7% of organisations have full visibility into their service accounts. That gap is why Zero Trust becomes harder to operationalise at machine speed.
In practice, many security teams discover overprivileged APIs and orphaned service accounts only after a failed audit, a secrets leak, or lateral movement has already exposed the weakness.
How It Works in Practice
The core Zero Trust problem is not merely authentication. It is identity lifecycle, authorization context, and continuous verification for workloads that do not behave like people. A service account may be created by Terraform, reused by multiple pipelines, and granted broad access because nobody wants the deployment to fail. An API key may be embedded in a container image, rotated inconsistently, or granted access to production data with no human approval path. NIST SP 800-53 Rev 5 Security and Privacy Controls is helpful here because it reinforces control discipline around access, auditability, and configuration management, but the operational challenge is still identity sprawl.
Current best practice is to treat machine identity as a workload problem, not a user problem. That means:
- Discovering all service accounts, API keys, tokens, certificates, and related secrets across code, CI/CD, cloud, and runtime environments.
- Binding identity to workload provenance, preferably with cryptographic workload identity rather than shared static credentials. Guide to SPIFFE and SPIRE is a useful reference for this model.
- Applying least privilege at request time, not just at provisioning time, using policy-based decisions that can incorporate service, environment, and transaction context.
- Rotating credentials on a short TTL and revoking them automatically when the workload terminates or changes scope.
- Mapping each identity back to an owner, an application, and a business purpose so orphaned assets can be retired.
NHIMG’s Ultimate Guide to NHIs – Standards supports this operational model by framing lifecycle governance, visibility, rotation, and offboarding as core Zero Trust requirements rather than optional hygiene. These controls tend to break down when DevOps teams clone workloads across many ephemeral environments because identity sprawl outpaces inventory, ownership, and revocation workflows.
Common Variations and Edge Cases
Tighter machine identity controls often increase deployment friction, requiring organisations to balance Zero Trust assurance against pipeline speed, uptime targets, and developer autonomy. That tradeoff is real, especially in environments with microservices, ephemeral containers, multi-cloud integration, or third-party automation.
Guidance is still evolving on how much runtime context should be required before a machine identity is allowed to act. Some teams use policy-as-code with strong guardrails and short-lived tokens; others still rely on static access rules because their toolchains cannot yet support dynamic authorization. The current guidance suggests that static allowlists alone are not enough for high-change environments.
Edge cases also matter. Shared service accounts may persist in legacy platforms, but they should be treated as temporary technical debt rather than a target operating model. External APIs and partner integrations can complicate ownership and revocation, so contractual controls and monitoring need to sit alongside technical enforcement. For breach-driven perspective, NHIMG’s 52 NHI Breaches Analysis shows how frequently these identities are involved when control gaps persist. In Zero Trust programs, the hardest failures are not the known service accounts, but the forgotten ones that still have valid secrets and productive access.
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 CSA MAESTRO address the attack and risk surface, while NIST AI RMF, NIST CSF 2.0 and NIST Zero Trust (SP 800-207) set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-01 | Covers discovery and inventory of service accounts and API keys. |
| CSA MAESTRO | C3 | Addresses governance for autonomous and machine-driven access patterns. |
| NIST AI RMF | Supports governance of automated decision-making and accountability. | |
| NIST CSF 2.0 | PR.AC-1 | Access control is central to least-privilege machine identity management. |
| NIST Zero Trust (SP 800-207) | PDP/PEP | Zero Trust relies on policy checks and enforcement for every request. |
Inventory every non-human identity and tie each one to an owner, purpose, and renewal date.
