A live inventory of the components an agent can use, including models, tools, memory stores, and knowledge sources. Unlike a static software bill of materials, it reflects runtime changes that alter the agent’s effective exposure during a session.
Expanded Definition
A dynamic agent bill of materials is the operative inventory of what an agent can actually invoke at runtime: foundation models, plugins, tools, memory stores, policies, retrieval sources, and delegated credentials. The key distinction from a traditional software bill of materials is that exposure changes during a session as the agent is granted new tools, switched to different models, or connected to additional data sources. In NHI governance, this matters because the agent’s effective privilege is not fixed at deployment time.
Definitions vary across vendors, but the practical security interpretation is consistent: if the agent’s runtime dependencies can change, the inventory must change with them. That aligns with the broader agentic risk framing in the OWASP Agentic AI Top 10 and the control-focused approach in NHI governance from Ultimate Guide to NHIs. It also complements NIST AI Risk Management Framework guidance on traceability and runtime oversight.
The most common misapplication is treating a one-time build manifest as sufficient, which occurs when teams ignore tool injection, live retrieval, and model switching after deployment.
Examples and Use Cases
Implementing a dynamic agent bill of materials rigorously often introduces operational overhead, requiring organisations to balance real-time visibility against engineering complexity and session latency.
- An internal support agent starts with read-only access, then receives a temporary ticketing tool during escalation, so the bill of materials updates to show the new authorization surface.
- A coding agent connected to Analysis of Claude Code Security may swap from one model endpoint to another based on policy, and that model change should be reflected immediately.
- A retrieval-augmented agent pulling from a sensitive knowledge base, vector store, and incident response runbook needs those sources listed as live dependencies, not assumed from deployment documentation.
- An agent with delegated API keys should show those secrets as active runtime enablers, especially when key scope expands or expires during a task.
- After a compromise pattern seen in the AI LLM hijack breach, responders can compare the recorded runtime inventory with the actual execution path to identify unauthorized tool use.
For implementation depth, the MITRE ATLAS adversarial AI threat matrix helps teams think about how runtime dependencies become attack paths rather than static assets.
Why It Matters in NHI Security
In NHI environments, runtime dependency drift is often the difference between a governed agent and an overprivileged one. A dynamic agent bill of materials gives security teams a way to see when an agent acquires new access, consumes a new data source, or begins using a different execution path that was never approved at design time. That visibility supports least privilege, change detection, incident response, and auditability across agentic workflows.
The risk is not theoretical: NHI Mgmt Group reports that 96% of organisations store secrets outside of secrets managers, and that kind of sprawl becomes more dangerous when agents can discover or consume those secrets dynamically. The same governance gap appears in breach analysis such as the Moltbook AI agent keys breach, where exposed credentials magnified runtime access. A living inventory also supports the operational logic behind the CSA MAESTRO agentic AI threat modeling framework, which treats agent capabilities as part of the threat surface.
Organisations typically encounter the need for this control only after an agent has used an unapproved tool or accessed a sensitive source during an incident, 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 Agentic AI Top 10 and OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | Agent capability drift and runtime tool exposure are core agentic AI risks. | |
| OWASP Non-Human Identity Top 10 | NHI-01 | Live inventories support discovery and visibility of non-human identity exposure. |
| NIST AI RMF | GOVERN | Traceability and oversight require knowing what an AI system can access at runtime. |
Track runtime capabilities continuously and revoke any tool or model path that exceeds approved scope.
