Static scanning looks for flaws in code or configuration before deployment, while behaviour-based governance evaluates what the agent actually does after deployment. For autonomous systems, the second control is decisive because risk often appears only when the agent reasons, adapts, and executes inside a live environment.
What static scanning tells you, and what it cannot tell you
Static appsec scanning is strongest before deployment. It inspects source code, dependencies, build artefacts, or configuration to find known defect patterns such as injection risk, insecure defaults, secrets in code, and missing hardening. It is useful because it shifts discovery left, but it only sees what is present in the artefact, not what the running system actually does.
That distinction matters for agents because many failures are not obvious in the source tree. An agent can be technically well built and still behave unsafely once it receives live context, invokes tools, follows prompts, or chains actions across systems. Behaviour-based governance is about that runtime reality, not just code quality.
Why behaviour-based governance is different for agents
Behaviour-based governance evaluates the agent in operation, including what it can access, which actions it actually attempts, how it responds to unexpected inputs, and whether it stays inside its intended authority. For agentic systems, this is the control that shows whether policy is being followed in practice rather than assumed from design.
That makes it a closer fit for autonomous software than static review alone. The relevant question is not only “is the implementation secure?” but “does this agent remain bounded, attributable, and controllable when it reasons, adapts, and executes?” NHIMG’s Agentic AI Security Guide and AI Agent Authorisation Guide both reinforce this runtime focus on tool use, policy decisions, and least-privilege access.
How the two controls complement each other in practice
The best operating model is layered. Static scanning catches predictable weaknesses before release, while behaviour-based governance catches policy drift, unsafe autonomy, and harmful action paths after release. One is primarily about preventing known bad patterns from shipping; the other is about constraining and observing real execution.
For agents, that complement is especially important because behaviour can change with context. A model may pass static review and still misuse a tool, overstep its permissions, or follow a manipulated instruction path. Behavioural controls therefore become a validation layer for runtime authority, not a replacement for secure engineering.
The practical implication is that teams should treat static scanning as necessary but insufficient for agents. Once an agent can act, the control question shifts from “did we write safe code?” to “did we bound safe behaviour across the live decision loop?” NHIMG’s AI Agent Observability, Audit and Incident Response Guide and Zero Trust for AI Agents are useful complements here because they emphasise logging, attribution, continuous verification, and removal of standing privilege.
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 addresses the attack and risk surface, while OWASP ASVS, OWASP SAMM and NIST SP 800-53 Rev 5 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP ASVS | V15 — Secure Architecture | Static appsec scanning targets code and configuration defects before deployment. |
| V8 — Authorization | Agent governance depends on runtime permission boundaries and action limits. | |
| V16 — Security Logging and Error Handling | Behaviour-based governance needs auditability and action attribution after deployment. | |
| Recommendation — Verify pre-release controls for injection, unsafe logic, and insecure design before deployment. Enforce authorization checks that bound what the agent can do at runtime. Log agent actions and failure states so runtime behaviour can be reviewed and investigated. | ||
| OWASP SAMM | GOVERN — Governance | Behaviour-based governance is a software security governance practice for released systems. |
| Recommendation — Define governance checkpoints for when autonomous behaviour requires approval and oversight. | ||
| NIST SP 800-53 Rev 5 | SA-11 — Developer Testing and Evaluation | Static scanning is part of pre-deployment security testing and evaluation. |
| AU-2 — Audit Events | Runtime governance depends on defining which agent actions must be recorded. | |
| AC-6 — Least Privilege | Agent behaviour must be constrained by runtime access boundaries. | |
| Recommendation — Test software artifacts before release to catch security defects early. Identify and record agent events that matter for accountability and review. Restrict agent privileges to the minimum needed for each task. | ||
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | Autonomous agents can exceed intended authority at runtime even when code looks sound. |
| Recommendation — Apply per-action policy checks to stop agents from exceeding delegated authority. | ||
Practitioner Guidance
What to prioritise: Use static appsec scanning to reduce obvious implementation defects, then add behaviour-based controls where the agent has tool access, delegated authority, or side effects that matter. If the agent can change data, trigger workflows, or spend money, runtime governance is not optional.
Decision rule: If a failure would only be visible after the agent acts, static scanning alone is the wrong control. If the main risk is unsafe runtime choice, policy violation, or overreach, you need behavioural monitoring, approval gates, and rollback or kill-switch options in addition to pre-deployment testing.
What to verify: Confirm that you can attribute each significant agent action, reconstruct the decision path, and show which policy or permission allowed it. If you cannot produce that evidence, you do not yet have meaningful behaviour-based governance.
Practitioner takeaway: Static scanning reduces the chance that bad code ships, but behaviour-based governance is what proves an agent stays safe once it is live and empowered.
Related resources from NHI Mgmt Group
- What is the difference between role-based access and API key governance for NHI security?
- What is the difference between attack surface management and NHI governance?
- What is the difference between human IAM controls and NHI governance?
- What is the difference between static IAM and intent-based security for agents?