How can organisations make threat prevention work across human and non-human identities?

Why This Matters for Security Teams

Threat prevention fails when human and non-human identities are governed in separate lanes. Attackers do not care whether the next step comes from a contractor, a service account, or an AI agent with tool access. They care about standing privilege, weak revocation, and identities that can be reused faster than defenders can react. NHIMG’s Ultimate Guide to NHIs — Why NHI Security Matters Now shows why the scale is different too: NHIs outnumber human identities by 25x to 50x in modern enterprises, so a human-only prevention model leaves the larger attack surface under-controlled.

This matters because prevention is not just about stopping logins. It is about constraining what an identity can do after authentication, including lateral movement, token reuse, and privilege escalation. That is why current guidance increasingly pairs identity governance with runtime controls such as CISA cyber threat advisories and the NHI patterns documented in the The 52 NHI breaches Report. In practice, many security teams encounter shared-identity abuse only after an automated workflow has already been used to widen access or move laterally.

How It Works in Practice

Organisations make prevention work across both identity classes by using one policy model for access decisions, one monitoring model for suspicious behaviour, and one revocation model when risk rises. The practical shift is from static permission grants to context-aware enforcement. For humans, that means least privilege, phishing-resistant authentication, and step-up controls when behaviour changes. For NHIs, it means short-lived credentials, workload identity, and automated revocation when the task ends or the runtime drifts from expected behaviour.

For non-human identities, the control set should be more explicit because token misuse is often faster than human response. NHIMG’s Top 10 NHI Issues and the Ultimate Guide to NHIs — Key Challenges and Risks both point to the same operational pattern: standing secrets, excessive privilege, and poor offboarding create prevention gaps that monitoring alone cannot close.

• Use a shared identity inventory so humans, services, and agents are visible in the same control plane.
• Apply least privilege to both IAM roles and service credentials, with explicit approval for sensitive actions.
• Issue just-in-time access for high-risk tasks and revoke it automatically when the task completes.
• Detect abnormal sequences, not just failed logins, because NHIs often misuse valid access rather than break in.
• Tie alerting to automated containment so suspicious identities can be limited before credentials are reused elsewhere.

For implementation detail, MITRE ATLAS adversarial AI threat matrix helps model adversarial behaviours, while standards-oriented teams can align detection and response with threat advisories. These controls tend to break down when identities are embedded in CI/CD pipelines and legacy service integrations because ownership, scope, and revocation paths are unclear.

Common Variations and Edge Cases

Tighter prevention often increases operational overhead, requiring organisations to balance faster containment against workflow friction. That tradeoff is especially visible when human access must remain usable during incidents while machine access must remain ephemeral. Best practice is evolving here: there is no universal standard for exactly how much runtime context should influence a deny or step-up decision, so current guidance suggests using policy-as-code and measurable thresholds rather than ad hoc exceptions.

Hybrid environments create the most awkward edge cases. A developer may act as a human today and trigger an automated pipeline that assumes a non-human identity tomorrow. Similarly, an AI assistant may inherit delegated access from a user but execute actions with machine speed. In those cases, prevention should focus on the action being attempted, not just the identity type. That is where one shared response playbook is more effective than separate human and NHI procedures.

The main exceptions involve shared service accounts, third-party integrations, and emergency break-glass access. Those flows often need stricter monitoring but cannot always be fully converted to JIT immediately. Organisations should phase toward revocation automation, stronger ownership, and token boundaries while preserving continuity for critical systems.

Related resources from NHI Mgmt Group

• When should organisations prioritise Zero Standing Privilege for non-human identities?
• How should teams secure non-human identities across cloud and SaaS?
• Why do non-human identities complicate zero trust architecture?
• Why do non-human identities increase zero trust risk?