They should move to passive network observation and use communication patterns as the basis for identity and policy. That approach lets teams classify devices, detect drift and enforce least-privilege segmentation without modifying equipment that is operationally sensitive or vendor-restricted.
Using passive observation when you cannot instrument the device
When an organisation cannot install agents on a critical device, the practical move is to treat the network as the telemetry source and derive trust signals from how the device actually communicates. That means building identity from observable behaviour such as peers, ports, frequency, timing and protocol patterns, then using those signals to classify assets and enforce policy without altering the endpoint.
This approach is most useful where the device is operationally sensitive, vendor-managed, safety-critical, or simply outside the organisation’s control. It preserves service continuity while still giving security teams enough information to distinguish expected communications from anomalous drift, which is often the only safe path when endpoint tooling is prohibited.
How communication patterns become an identity signal
Passive network observation does not replace device identity in the abstract, but it can establish a working identity for policy purposes. In practice, teams correlate a device’s stable network behaviour with its role, location, business function and allowed dependencies. Over time, that behaviour becomes the basis for segmentation decisions, exception handling and drift detection, especially where the asset cannot run an agent, report state, or support active inspection.
The key is to separate observation from assumption. A device may appear “known” because it repeatedly talks to the same systems, yet still drift if a new destination, unexpected protocol, or altered timing pattern appears. Organisations should therefore treat communication patterns as evidence of normality, not proof of correctness, and use them to drive containment rules that are narrow enough to reduce blast radius but broad enough to avoid breaking fragile equipment.
For teams building this capability, the passive telemetry journey should align with broader device classification and segmentation practices, not ad hoc allow-listing. The goal is to preserve the operational constraint while still enabling policy decisions that are traceable and reviewable, which is why a structured approach matters more than a one-off monitoring project.
What changes once you move from endpoint control to network control
Once the control point shifts to the network, the emphasis changes from host hardening to traffic governance. That means you will usually rely on policy decisions about where the device may talk, what it may talk to, and what deviations should trigger escalation. The strongest programmes use this model to define a baseline, watch for drift, and restrict segmentation in a way that assumes the device may be less observable than a managed workstation.
That is also why a passive model often works best when paired with disciplined asset ownership. If no team can explain the device’s normal communications, then even good monitoring will produce weak policy. The practical outcome should be a narrower allowed set of services, explicit exceptions for vendor dependencies, and a clear review path whenever traffic expands beyond the baseline.
For a broader treatment of identity and trust boundaries across autonomous and semi-autonomous systems, Zero Trust for AI Agents is useful because it frames policy around verification and least privilege rather than assumed trust. Where teams need a more direct identity-and-authorisation lens for delegated access decisions, AI Agent Authorisation Guide shows how to scope access per action instead of granting broad standing privilege.
Why passive observation can still fail
Passive monitoring is resilient, but it is not magical. If baseline traffic is noisy, if multiple device types share the same network segment, or if vendors use changing cloud dependencies, the organisation can mistake expected variability for malicious drift. The bigger failure mode is false confidence: a passive control may seem complete while still missing direct compromise, because it only sees what crosses the wire and not what happens inside the device.
Another common issue is policy brittleness. If segmentation rules are too rigid, operations teams may disable them after the first disruption. If they are too loose, the programme becomes a passive inventory exercise with little enforcement value. The control works best when teams expect controlled exceptions, define who can approve them, and set a process for revalidating behaviour after firmware changes, maintenance windows or vendor updates.
Where teams need stronger threat-context for abnormal traffic and trust abuse, Agentic AI Security Guide is relevant for its treatment of blast radius, tool abuse and layered trust boundaries. For network-led control design, the external framing in NIST Cybersecurity Framework 2.0 supports the same basic discipline of identify, protect, detect, respond and recover around constrained assets.
Risk and Threat Considerations
Critical devices that cannot be instrumented create a visibility gap, and attackers often exploit visibility gaps by hiding inside “normal” communications or abusing trusted pathways. If the baseline is weak, a compromised device can blend in, continue talking to approved destinations, and move laterally through relationships that defenders assumed were safe.
Failure mechanism: The organisation over-relies on unreachable endpoint controls, so it lacks enough telemetry to distinguish legitimate device behaviour from drift, misuse or compromise.
Impact: An attacker or misconfiguration can persist longer, expand laterally, or trigger outages through overbroad segmentation rules, delayed detection, or unsafe vendor exceptions.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
NIST CSF 2.0 and NIST SP 800-53 Rev 5 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | ID.AM-01 — Asset Inventory | Passive observation depends on knowing which critical devices exist and how they are grouped. |
| PR.AA-05 — Least Privilege Access | Network policy should restrict devices to only the communications they need. | |
| DE.CM-01 — Networks and network services are monitored to find anomalies and indicators of potential events | The question centers on passive network observation as the detection mechanism. | |
| Recommendation — Maintain an accurate inventory so passive baselines and segmentation rules map to the right critical devices. Apply least-privilege segmentation to limit each device's allowed destinations and flows. Monitor network traffic for drift, unexpected peers and protocol changes that signal abnormal device behaviour. | ||
| NIST SP 800-53 Rev 5 | CA-7 — Continuous Monitoring | Passive observation is a continuous monitoring approach for uninstrumented critical devices. |
| SC-7 — Boundary Protection | Segmentation based on communications patterns is a boundary protection problem. | |
| AC-4 — Information Flow Enforcement | The answer relies on policy enforced from observed communications rather than endpoint agents. | |
| Recommendation — Use continuous monitoring to track device communications and detect baseline deviations. Enforce boundary controls that only permit the device flows required by its observed role. Enforce approved information flows based on the device's validated communication profile. | ||
Practitioner Guidance
What to prioritise: Start by defining the smallest set of communication patterns that are truly normal for each critical device class, then tie those patterns to an owner who can approve exceptions. If a device cannot be patched or instrumented, the network baseline becomes your control evidence, so it must be specific enough to support enforcement and review.
What to verify: Confirm that you can answer three questions for every protected device: what it normally talks to, what change would count as drift, and who can respond when that drift appears. If you cannot answer all three, the organisation has observation, not control.
Practitioner takeaway: The objective is not to see everything inside the device, it is to make the device’s permitted communications narrow, observable and governable enough that the lack of agents does not become a lack of control.
Related resources from NHI Mgmt Group
- What should organisations do when a critical firewall vulnerability affects devices they cannot patch immediately?
- What breaks when organisations cannot see AI agents across devices and browsers?
- What breaks when organisations cannot correlate AI agents to the business capabilities they were built to support?
- When should organisations prioritise Zero Standing Privilege for non-human identities?