A runtime-observed SBOM is a software bill of materials generated from what actually executed during a build, not only from declared manifests. It captures dynamically fetched dependencies, malicious post-install behavior, and other build-time additions that static scans can miss, making it more accurate for supply chain assurance.
Expanded Definition
Runtime-observed SBOM is a supply chain inventory built from what actually executed during software creation or testing, rather than what a manifest claims should exist. That distinction matters because modern builds often pull in transitive packages, post-install scripts, generated artifacts, and ephemeral tooling that static analysis can miss. In NHI security, the same pattern appears when build pipelines and agentic workflows execute with credentials that are not fully visible in declarations.
Definitions vary across vendors on whether runtime observation stops at the build container, extends into test execution, or includes policy checkpoints for code signing and provenance. The operational value is strongest when a runtime-observed SBOM is treated as evidence of executed components, not a replacement for dependency declaration. It should complement source-based SBOM practices, provenance records, and controls described in the NIST Cybersecurity Framework 2.0.
The most common misapplication is assuming a static manifest is sufficient, which occurs when teams trust package declarations even though build scripts fetch additional code at runtime.
Examples and Use Cases
Implementing runtime-observed SBOM rigorously often introduces pipeline overhead and evidence-management complexity, requiring organisations to weigh stronger assurance against slower builds and more operational tooling.
- A CI job installs a helper library from a remote source during build, and the runtime-observed SBOM records the actual fetched artifact rather than the declared dependency only.
- A malicious post-install script adds a backdoor component to an agent build, and the SBOM captures the executed payload for later investigation.
- A container build uses generated code and ephemeral toolchains, so the runtime-observed SBOM documents transient components that would never appear in a source manifest.
- An organisation compares runtime-observed output against the guidance in the Ultimate Guide to NHIs to identify where service-account usage and secret exposure emerge during builds.
- A security team uses the runtime evidence alongside the NIST Cybersecurity Framework 2.0 to verify that supply chain controls detect unapproved runtime additions.
Why It Matters in NHI Security
Runtime-observed SBOM matters because NHI compromise often begins in the build and delivery path, where service accounts, API keys, and automation credentials are used to fetch dependencies, publish artifacts, or trigger downstream jobs. When those actions are invisible in the declared bill of materials, defenders lose the ability to trace what code actually had access to secrets or execution authority. That gap is especially serious in agentic AI and automation pipelines, where tool access can expand quietly during execution.
NHI Management Group reports that 96% of organisations store secrets outside secrets managers in vulnerable locations, and 92% expose NHIs to third parties, which makes runtime supply chain visibility directly relevant to secret exposure and dependency trust. A runtime-observed SBOM helps connect build evidence to identity risk, especially when paired with identity governance and NHI lifecycle controls.
Organisations typically encounter the need for runtime-observed SBOM only after a build artifact is suspected of carrying unapproved code or abused credentials, at which point the term 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-07 | Runtime visibility reduces hidden NHI usage across build and delivery paths. |
| NIST CSF 2.0 | ID.SC-4 | Supply chain risk management depends on knowing what actually executed. |
| NIST Zero Trust (SP 800-207) | SA-3 | Zero trust requires strong assurance about software and execution provenance. |
| NIST AI RMF | GV.1-3 | AI risk governance relies on traceability of components used at execution time. |
| OWASP Agentic AI Top 10 | A04 | Agentic systems can fetch tools dynamically, creating hidden runtime dependencies. |
Record executed build components and link them to service-account activity for NHI inventory accuracy.
Related resources from NHI Mgmt Group
- What breaks when runtime policies are guessed instead of observed?
- What is the difference between runtime protection and NHI lifecycle management?
- What is the difference between code scanning and runtime identity monitoring?
- Why are runtime environments riskier than repository scans for NHI governance?
