Runtime execution evidence is proof of what code paths, classes, or functions actually ran in production. It gives teams a concrete signal for prioritising vulnerabilities, validating whether a finding is exploitable, and linking live behavior back to the repository or build that introduced it.
Expanded Definition
Runtime execution evidence is the operational record that shows which code paths, classes, or functions actually executed in production. In NHI security, this matters because exploitability is not the same as code presence: a vulnerability may exist in a repository, yet never be reachable in the running service, container, or agent workflow.
Definitions vary across vendors, especially where teams blend runtime tracing, telemetry, coverage data, and supply chain attestations. NHI Management Group treats the term as evidence from the live environment that can be tied back to a specific build or source state, helping teams separate theoretical exposure from confirmed execution. That distinction supports better prioritisation for service accounts, agents, API-driven workloads, and code that handles secrets or token exchange.
Practically, runtime execution evidence is most useful when paired with release metadata, dependency inventories, and identity-aware access paths. The most common misapplication is treating a static code scan as proof of runtime exposure, which occurs when teams assume a vulnerable function is reachable without confirming that production ever invoked it.
Examples and Use Cases
Implementing runtime execution evidence rigorously often introduces telemetry and storage overhead, requiring organisations to weigh stronger exploit validation against added instrumentation cost.
- A team confirms a suspected vulnerable parsing function never ran in production, so remediation can be scheduled after truly exposed NHI paths are addressed first.
- An AI agent workflow is traced to show exactly which tools were invoked, helping security teams validate whether a secret-handling routine was actually exercised.
- Production traces are mapped back to a container image digest, allowing engineers to link live behavior to the build that introduced the code path.
- Telemetry from a CI/CD-deployed service shows that an authentication branch ran only under rare error conditions, sharpening incident response and patch priority.
- Evidence from runtime instrumentation supports a review of findings like JetBrains GitHub plugin token exposure by showing whether similar token-handling code ever executed in the affected environment.
For broader control mapping, this approach fits naturally with the NIST Cybersecurity Framework 2.0, especially when evidence is used to improve detection and risk prioritisation rather than merely to document code coverage.
Why It Matters in NHI Security
Runtime execution evidence closes a common blind spot in NHI programs: the gap between what exists in code and what actually runs with live credentials, tokens, certificates, or agent permissions. Without it, teams can overinvest in unexploitable findings while missing reachable behavior that touches secrets or privileged automation. That creates weak prioritisation, noisy remediation queues, and avoidable exposure in service accounts and AI-enabled workflows.
This is especially relevant in environments where long-lived secrets are embedded in code paths or distributed through CI/CD, because runtime confirmation tells defenders whether the risky logic was merely shipped or truly executed. NHI Management Group research shows that 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools, and only 5.7% of organisations have full visibility into their service accounts. Evidence like this becomes actionable when paired with live execution traces and identity context.
Related cases such as Code Formatting Tools Credential Leaks and Hard-Coded Secrets in VSCode Extensions show why runtime proof matters when third-party components can expose or consume secrets unexpectedly. Organisations typically encounter the urgency of runtime execution evidence only after a suspected exposure, at which point proving actual execution 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 AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-10 | Runtime evidence helps verify which NHI code paths actually executed and exposed secrets. |
| NIST CSF 2.0 | DE.CM-8 | Runtime evidence strengthens monitoring by showing what software behavior was truly observed. |
| NIST Zero Trust (SP 800-207) | ID, AC | Evidence of executed paths supports zero trust decisions based on observed access and behavior. |
| OWASP Agentic AI Top 10 | AGENT-07 | Agentic systems need proof of invoked tools and functions to bound execution risk. |
| NIST AI RMF | MAP | Runtime evidence supports mapping actual AI system behavior instead of theoretical behavior. |
Correlate live execution with NHI flows to confirm real exposure before prioritising remediation.
Related resources from NHI Mgmt Group
- What is the difference between compliance evidence and runtime access control?
- Why do agentless tools fall short for runtime cloud security evidence?
- What breaks when audit evidence is still assembled manually after control execution?
- How should security teams handle runtime workload evidence in their SIEM?
