A detection approach that evaluates what a package does rather than relying only on known signatures or public reports. In software supply chains, it is used to spot suspicious actions such as unexpected file changes, credential access, or propagation behaviour. This helps close the gap before community detection catches up.
Expanded Definition
Behaviour-based scanning evaluates observable actions, not just known indicators, signatures, or prior intelligence. In software supply chains, that means examining how a package behaves during install, execution, or dependency resolution, then flagging actions that are inconsistent with its stated purpose. This matters because malicious packages often appear benign until they attempt file modification, credential access, network propagation, or environment inspection. Behaviour-based scanning is therefore a detection layer for unknown or rapidly mutating threats, and it is especially useful where public reputation data lags behind attacker innovation.
Definitions vary across vendors because some tools treat behaviour-based scanning as dynamic analysis, while others include sandboxing, policy enforcement, or runtime telemetry. In NHI and agentic AI contexts, the same idea extends to packages, agents, and automation components that can touch secrets or invoke tools. For broader control alignment, practitioners often map this capability to NIST Cybersecurity Framework 2.0 detection and monitoring outcomes, while using Ultimate Guide to NHIs for identity-specific governance context. The most common misapplication is assuming a package is safe because it lacks known malware signatures, which occurs when teams skip behavioural checks for newly published or lightly reviewed dependencies.
Examples and Use Cases
Implementing behaviour-based scanning rigorously often introduces execution overhead and false-positive tuning, requiring organisations to weigh deeper inspection against build speed and developer friction.
- A CI pipeline detonates a newly introduced package in a sandbox and blocks it after it attempts to read cloud credential files outside its declared function.
- A dependency is allowed to install, but the scanner flags unexpected child-process creation and outbound beaconing that suggest a loader or dropper pattern.
- An internal package passes signature checks, yet behaviour analysis identifies mass file encryption attempts that indicate ransomware-like activity.
- An agent tool bundle is inspected before deployment and rejected because it tries to enumerate secrets stores and tokens, which is incompatible with its documented purpose.
- A release gate uses behaviour telemetry alongside NIST Cybersecurity Framework 2.0 criteria to stop packages that create persistence or lateral movement paths.
NHIMG research shows that 79% of organisations have experienced secrets leaks, and 77% of those incidents caused tangible damage. That makes behavioural inspection especially relevant when a package or agent interacts with credentials during build or runtime. The broader governance lesson from Ultimate Guide to NHIs is that identity exposure often hides inside trusted automation rather than public-facing software.
Why It Matters in NHI Security
Behaviour-based scanning matters because NHI compromise rarely begins with a loud signature match. It often begins with a trusted automation path, a dependency update, or an agent workflow that is allowed to read secrets, call APIs, or modify code. Once an NHI or package is compromised, the blast radius can expand quickly across CI/CD systems, vaults, and deployment environments. That is why behaviour inspection is a practical control for spotting misuse of long-lived credentials, suspicious tool invocation, and propagation behaviour before an attacker fully establishes persistence.
NHIMG reports that 96% of organisations store secrets outside secrets managers in vulnerable locations, and only 5.7% have full visibility into their service accounts. Those conditions make behavioural controls more valuable, not less, because static reviews alone cannot reveal how a component will behave once it is executed. Behaviour-based scanning also supports Zero Trust thinking by assuming that code and automation must continuously prove they are acting as expected. Organisations typically encounter the need for behaviour-based scanning only after a suspicious package has already touched secrets or propagated through a build path, at which point the control 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, CSA MAESTRO and OWASP Agentic AI Top 10 address the attack and risk surface, while NIST CSF 2.0 and NIST Zero Trust (SP 800-207) set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-02 | Behavioural inspection helps detect secret misuse and abnormal NHI activity. |
| NIST CSF 2.0 | DE.CM-8 | Continuous monitoring of code behaviour aligns with detecting anomalous activity. |
| NIST Zero Trust (SP 800-207) | SC-7 | Zero Trust requires continuous verification of component behaviour and access paths. |
| CSA MAESTRO | Agentic systems need runtime guardrails against unsafe tool use and data access. | |
| OWASP Agentic AI Top 10 | Agentic AI guidance addresses unsafe tool invocation and autonomous misuse patterns. |
Scan packages and agents for suspicious secret access, persistence, and propagation before release.
Related resources from NHI Mgmt Group
- How should security teams combine agentless and agent-based Kubernetes scanning?
- How should security teams govern AI agents that can change behaviour based on prompt context?
- Who is accountable when behaviour-based access controls block or challenge a session?
- How should security teams choose between agentless and agent-based secrets scanning?
