What should teams do when insider risk also involves non-human identities?

Why This Matters for Security Teams

Insider risk programs usually start with people, but the real exposure often sits in service accounts, API keys, automation runners, and other non-human identities. Those identities can quietly read, move, and exfiltrate data without a login prompt, which means human-centric monitoring misses the path entirely. NHI Management Group has documented that 80% of identity breaches involved compromised non-human identities such as service accounts and API keys in its Ultimate Guide to NHIs.

This matters because insider activity rarely stays human-only. A developer with legitimate access may abuse an automation token, or a compromised workstation may be used to mint secrets that later behave like trusted infrastructure. Standard insider risk tooling, such as the NIST Cybersecurity Framework 2.0, provides useful governance structure, but teams must extend it to identities that do not sit in an HR system. The practical question is not whether a person is present at the keyboard, but whether an identity can reach sensitive systems and move data. In practice, many security teams encounter this only after a service account has already been used as the quiet bridge between normal user activity and a material data loss event.

How It Works in Practice

The operational model should be simple: if an NHI can access regulated data, administrative functions, or production systems, it belongs in the same detection and response pipeline as a human user. That means correlating anomalous access, privilege escalation, unusual data movement, token creation, and off-hours activity across both identity types. Current guidance suggests treating these as one investigation graph rather than separate queues, because otherwise an insider can hide behind automation noise.

A workable approach usually combines identity inventory, telemetry, and response playbooks:

• Inventory all service accounts, API-driven access, CI/CD identities, and automation users.
• Tag each NHI by owner, system scope, secret location, and business function.
• Feed NHI events into the same SIEM, UEBA, and case management workflows used for human insiders.
• Alert on impossible travel equivalents for workloads, such as a token used from a new host, new pipeline, or new region.
• Revoke, rotate, or quarantine the NHI when behavior departs from its normal task pattern.

This is where the Top 10 NHI Issues research is especially useful: it reinforces that excessive privilege, poor rotation, and weak visibility are not edge cases but common failure modes. For control design, map the same response expectations to NIST SP 800-53 Rev 5 Security and Privacy Controls so identity, logging, and incident handling remain consistent across humans and machines. These controls tend to break down in environments where secrets are embedded in CI/CD pipelines and ownership is unclear, because responders cannot quickly tell whether an action was operator error, automation drift, or deliberate abuse.

Common Variations and Edge Cases

Tighter monitoring of non-human identities often increases operational overhead, requiring organisations to balance faster detection against more frequent false positives and secret rotation work. That tradeoff is real, especially in environments with thousands of ephemeral workloads or heavily automated release pipelines.

Best practice is evolving, but current guidance suggests a few practical distinctions. Shared service accounts are the hardest case because attribution is weak, so teams should prioritize breaking them into named workloads or scoped secrets wherever possible. Privileged automation accounts used for patching, deployment, or data movement should be monitored more aggressively than low-risk utility tokens. Third-party integrations also need special handling, since the human insider may never touch the credentials directly while still benefiting from the access path.

When NHIs are part of an insider risk case, the investigation should ask four questions: who owns the identity, what business task justifies it, what systems can it reach, and what evidence shows the access was expected. If any of those answers are unclear, the issue is not just insider behavior but weak identity governance. In real environments, that ambiguity usually becomes visible only after an unusual export, a pipeline compromise, or a quiet privilege chain has already crossed the boundary from monitoring problem to incident.

Related resources from NHI Mgmt Group

• How should security teams govern non-human identities at scale?
• How should security teams govern non-human identities for compliance?
• Why do non-human identities create more audit risk than human accounts?
• How should security teams govern non-human identities in Salesforce?