Runtime signals are observations taken from live system activity while workloads and services are operating. They include identity actions, process behavior, network paths, and other evidence that helps security teams distinguish normal execution from suspicious or risky behavior.
Expanded Definition
Runtime signals are the live evidence generated while a workload, service, or AI agent is executing. In NHI security, they capture identity actions, process state, network destinations, tool calls, and other operating facts that help distinguish expected behaviour from anomalous behaviour. These signals complement configuration data and static inventory, which cannot show how an identity behaves once it is active.
Definitions vary across vendors about which telemetry qualifies as a runtime signal. In practice, NHI practitioners usually treat it as operational evidence that can be correlated across authentication logs, process telemetry, service-to-service traffic, and agent action records. That makes it especially useful for spotting privilege misuse, lateral movement, and policy drift in real time. Standards such as NIST SP 800-53 Rev 5 Security and Privacy Controls frame the underlying logging, monitoring, and audit expectations, even if they do not use this exact term.
The most common misapplication is treating runtime signals as a replacement for identity governance, which occurs when teams rely on alerts without first establishing trusted identity ownership, expected behaviour, and control boundaries.
Examples and Use Cases
Implementing runtime signals rigorously often introduces telemetry volume and correlation overhead, requiring organisations to weigh faster detection against storage, tuning, and analyst effort.
- A service account suddenly begins calling a new cloud API from an unfamiliar subnet, which is flagged because the observed runtime path diverges from the baseline.
- An AI agent approved for read-only retrieval starts issuing write actions through its tool chain, indicating a change in execution authority that should be investigated.
- Secrets usage is observed outside a managed workload boundary, helping teams trace whether an API key was embedded in code or exposed in a deployment pipeline. This aligns with the visibility concerns described in the Ultimate Guide to NHIs.
- Authentication logs show a machine identity succeeding from a new geographic region, while process telemetry confirms that the workload itself should not have moved, pointing to credential replay.
- Network flow and identity telemetry together show that a container is reaching a sensitive datastore during hours when the job normally stays idle, prompting containment and review under NIST SP 800-53 Rev 5 Security and Privacy Controls.
Why It Matters in NHI Security
Runtime signals matter because NHI compromise often becomes visible only after the attacker has already obtained execution rights. Static inventories can tell security teams what identities exist, but only runtime evidence shows how those identities are actually used, whether they are over-privileged, and whether their behaviour matches the intended workload or agent mission. That distinction is critical when identities outnumber humans by 25x to 50x and when 80% of identity breaches involve compromised non-human identities such as service accounts and API keys, according to NHI Mgmt Group’s Ultimate Guide to NHIs.
In governance terms, runtime signals support continuous verification, incident triage, and post-compromise scoping. They help answer practical questions: which identity executed the action, from which process, against which resource, and under what sequence of events. That makes them essential for Zero Trust monitoring, secrets exposure investigation, and agentic AI oversight. They are also a strong complement to monitoring and audit expectations in NIST SP 800-53 Rev 5 Security and Privacy Controls.
Organisations typically encounter the need for runtime signals only after a token is abused, a service account behaves unexpectedly, or an AI agent takes an unauthorised action, at which point runtime visibility becomes operationally unavoidable to address.
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 OWASP Agentic AI Top 10 address the attack and risk surface, while NIST CSF 2.0, NIST Zero Trust (SP 800-207) and NIST SP 800-63 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-05 | Runtime visibility supports detection of anomalous NHI execution and misuse. |
| NIST CSF 2.0 | DE.CM-01 | Runtime signals are core monitoring evidence for continuous security observation. |
| NIST Zero Trust (SP 800-207) | PA-3 | Zero Trust requires ongoing assessment of identity and workload activity. |
| NIST SP 800-63 | Identity assurance depends on observing how credentials are actually used. | |
| OWASP Agentic AI Top 10 | A-07 | Agentic AI controls depend on monitoring tool use and action execution. |
Use runtime signals to continuously verify workload behaviour instead of trusting initial access alone.
