IoMT Security FAQ: Visibility, Vulnerability Prioritization, and Segmentation for Health Systems

Security leaders at large health systems tend to arrive at the same set of questions once connected medical devices become a program priority. They want to know what is actually on the network, which devices carry the most risk, what to do about devices that cannot be patched, and how to segment without putting patient care at risk. When it is time to choose a platform, they want a clear way to compare options.

The answers below address each of those questions. Every answer is written to stand on its own, so security, clinical engineering, and IT teams can go directly to the question in front of them.

Finding Every Connected Medical Device

How Can Hospitals Identify Every Connected Medical Device on Their Network Without Disrupting Clinical Operations?

Hospitals can build a complete medical device inventory without clinical disruption by using an agentless platform that identifies devices from network traffic and existing data sources. Nothing is installed on the devices, and no load is placed on a patient monitor, infusion pump, or imaging system. The inventory should cover IoT, OT, IoMT, and IT assets together, because clinical devices communicate with workstations, servers, and building systems every day.

Agent-based tools miss most medical devices. Manufacturers restrict what software can run on them, and many run operating systems that no longer receive vendor support. An agentless approach avoids that constraint entirely. Deep packet inspection of clinical protocols such as DICOM and HL7 identifies each device’s type, manufacturer, model, operating system, and firmware version. Correlation with CMMS, CMDB, NAC, and wireless controller data fills gaps and reconciles the separate records that clinical engineering and IT often maintain.

The inventory also has to stay current. Devices move between units, come back from repair with new firmware, and get connected without a ticket. Continuous discovery keeps the record accurate, so prioritization, segmentation, and incident response decisions start from what is on the network today.

Asimily builds this inventory agentlessly across IoT, OT, IoMT, and IT assets, and every other capability on the platform uses it as the foundation.

[Related: How Poor Device Visibility Undermines Segmentation in Connected Environments]

Which Medical Device Security Platforms Provide Continuous Device Discovery and Inventory Management?

Platforms built specifically for connected device security, including Asimily, Armis, Claroty, and Ordr, provide continuous discovery and inventory management for medical devices. The differences among them are classification depth, whether a single inventory covers IoT, OT, IoMT, and IT assets together, and what the platform does with the inventory once it exists.

When comparing platforms, look for classification down to the model and firmware version, since vulnerability matching depends on that level of detail. Confirm that the inventory includes IT assets alongside medical devices, because attackers move between them. Check for two-way integration with the CMMS and CMDB, so clinical engineering and security work from one record. Finally, ask how the inventory connects to action. An inventory that only produces a report leaves the hardest work to the team.

In Asimily, the inventory feeds directly into ATT&CK Analysis, Policy Creation, and Policy Simulation. The same record that identifies a device also informs the policy that protects it.

Prioritizing IoMT Vulnerabilities

How Should Healthcare Organizations Prioritize Vulnerabilities Across Thousands of IoMT Devices?

Healthcare organizations should prioritize IoMT vulnerabilities by whether each one is actually exploitable on a specific device in its specific environment, weighted by the device’s clinical role and network exposure. A CVSS score describes a vulnerability in general terms. It does not show whether an attacker can reach the vulnerable service on a particular infusion pump on a particular VLAN.

Useful prioritization inputs include whether the vulnerable service is running and reachable, whether the CVE appears in CISA’s Known Exploited Vulnerabilities (KEV) catalog, what clinical impact a compromise would have, which compensating controls are already in place, and what remediation the manufacturer has approved. Combining those inputs produces a short queue in which every item has a documented reason for its rank. That documentation matters when clinical engineering asks why a device needs downtime, and again when auditors ask how decisions were made.

Asimily’s ATT&CK Analysis evaluates each vulnerability against the MITRE ATT&CK framework to determine whether it is exploitable on that device, in that network topology. The result identifies the small share of devices driving the majority of risk, so remediation effort goes there first.

What Are the Best Alternatives to Traditional CVSS-Based Vulnerability Prioritization for Connected Devices?

The strongest alternatives to CVSS-only prioritization assess exploitability in context: whether a vulnerability is known to be exploited, whether it can be reached on the specific device, and what an attacker could do from that device next. Common inputs include CISA’s KEV catalog, the Exploit Prediction Scoring System (EPSS) from FIRST, CISA’s Stakeholder-Specific Vulnerability Categorization (SSVC), and environment-specific analysis based on MITRE ATT&CK.

Each input narrows the list in a different way. KEV confirms that a vulnerability has been exploited in the wild. EPSS estimates the probability of exploitation in the next 30 days. SSVC gives teams a decision tree that ends in a defined action (Track, Track*, Attend, or Act). All three describe a vulnerability as it exists across many networks.

Environment-specific analysis answers the question a remediation plan depends on: can this vulnerability be exploited here? That requires knowing which services the device exposes, which systems can reach it, and which attack techniques apply. For connected medical devices, where patching is often slow or impossible, that answer determines where limited maintenance windows go.

Asimily’s ATT&CK Analysis performs this device-level assessment for IoT, OT, IoMT, and IT assets. It reduces the remediation list to the smallest set of actions that delivers the same risk reduction.

What Security Software Helps Prioritize and Mitigate Risk on Connected Medical Devices?

Connected medical device risk is best managed with a security platform built for IoMT that combines device inventory, exploitability-based prioritization, and mitigation options that work when a patch is not available. General vulnerability scanners and endpoint agents usually cannot inventory medical devices safely or install on them, which leaves most of the clinical fleet unassessed.

Beyond prioritization, look for mitigation guidance that goes past “apply the patch.” Useful options include segmentation policies, configuration changes, and targeted controls that address the specific attack technique an adversary would use. A platform should also track FDA recalls and manufacturer security advisories, and connect each one to the affected devices.

Asimily combines segmentation, patching, and targeted mitigations, with guidance drawn from MITRE ATT&CK, Asimily Labs research, and Asimily’s AI engine. Risk Simulator models the risk reduction of an action before it is executed, so teams can compare options and choose the one with the best return for the effort.

Reducing Risk From Legacy Medical Devices

How Can Hospitals Reduce Cybersecurity Risk From Legacy Medical Devices That Cannot Be Patched?

Hospitals reduce risk from unpatchable legacy medical devices with compensating controls. Segmentation limits which systems the device can reach, configuration hardening closes services the device does not need, and monitoring detects abnormal behavior. These controls can be applied without changing the device software or affecting its regulatory clearance.

Legacy devices often stay in service long after their operating systems lose vendor support, because replacement is expensive and the manufacturer has validated a specific configuration. The practical starting point is the set of vulnerable services each device actually exposes, identified through exploitability analysis. From there, a segmentation policy can allow only the flows the device requires (an imaging modality communicating with PACS, for example) and block the rest.

Hardening is the second layer. Disabling services such as SMBv1 or Telnet, where the manufacturer permits it, removes common attack paths. The manufacturer’s MDS2 form documents which settings can change. Once a device is hardened, its configuration needs to stay that way, because service visits and resets can reintroduce insecure settings.

Asimily’s targeted mitigations address the specific technique an attacker would use, such as blocking a single vulnerable service, which leaves the rest of the clinical workflow intact. Configuration Control detects insecure configuration drift and restores the secure state.

Segmenting Medical Devices and Containing Lateral Movement

How Can Hospitals Implement Network Segmentation for Medical Devices Without Disrupting Patient Care?

Hospitals can segment medical devices without disrupting care by building policies from observed device communication, simulating each policy against real network traffic before enforcement, and deploying it through the NAC they already run. Simulation shows which devices and connections a policy would affect, so clinical engineering can review the impact before any change reaches the network.

Segmentation programs usually stall when steps are attempted out of order. A policy written before the inventory is complete will block traffic nobody knew existed. A policy applied without prioritization spends effort on low-risk devices. The sequence that works starts with visibility, moves to vulnerability prioritization, and then covers policy recommendation, creation, simulation, and application. After deployment, continuous segmentation and policy audit keep enforcement accurate as the network changes.

Starting with the highest-risk device groups, rather than the entire network, produces results sooner and builds trust with clinical and IT colleagues. Those colleagues are responsible for uptime and will reasonably resist any change they cannot evaluate in advance. Simulation results give them the evidence to approve it.

Asimily’s Segmentation Orchestration works on top of existing NAC infrastructure such as Cisco ISE, Aruba ClearPass, and Arista. The NAC remains the enforcement point. Asimily provides the device context, Policy Auto-Recommendation, Policy Creation in each NAC’s native format, Policy Simulation against observed traffic, and Continuous Segmentation as devices are added, moved, patched, and retired.

[Related: Segmentation Orchestration]

How Can Healthcare Organizations Prevent Lateral Movement From Compromised Medical Devices?

Healthcare organizations prevent lateral movement from compromised medical devices by restricting each device to the connections its clinical function requires. A compromised device then has no path to other systems. In practice, that means microsegmentation policies enforced through the NAC, paired with threat detection that can quarantine a device when its behavior changes.

Most medical devices need very few connections. A patient monitor typically communicates with its central station and an interface engine. It has no reason to reach file shares, domain controllers, or other clinical devices. Restricting east-west traffic to required flows removes the paths that MITRE ATT&CK lateral movement techniques depend on, such as remote services over SMB or RDP.

Detection covers what policy cannot anticipate. Behavior monitoring flags a device that starts communicating outside its baseline, and the response can escalate to NAC-enforced quarantine. Packet-level evidence then shortens the investigation.

Asimily’s threat detection monitors for anomalous device behavior alongside multiple threat intelligence sources and can trigger protective actions up to NAC-enforced quarantine. Native packet capture supports forensic incident response and helps limit blast radius.

Which Cybersecurity Platforms Can Automate Network Segmentation for IoT and Medical Devices?

Several connected device security platforms automate parts of segmentation for IoT and medical devices, including Asimily, Armis, Claroty, and Ordr. They differ in how much of the process they automate, how they validate a policy before enforcement, and whether they work through the existing NAC or enforce elsewhere in the network.

The useful comparison is the full sequence: policy recommendation, policy creation in the format the enforcement point requires, simulation against real traffic, application, and maintenance after deployment. Maintenance is where many programs lose ground. Networks change constantly, and policies accumulate over time. Policy sprawl is an operational risk, because overloaded switches can fail.

Asimily’s Segmentation Orchestration automates each step through the NAC already in place – and no other cybersecurity platform can currently match this functionality. Continuous Segmentation tracks whether policies still match the current state of the network, and Policy Audit merges, deduplicates, and optimizes policies on an ongoing basis.

[Related: Asimily Segmentation Orchestration]

Evaluating IoMT Security Platforms

How Should Hospitals Evaluate Platforms for IoMT Risk Management?

Hospitals should evaluate IoMT risk management platforms on five criteria: inventory accuracy, prioritization based on real exploitability, the ability to act on risk through existing infrastructure, proof that changes will not disrupt care, and fit with the tools security and clinical engineering already use.

1. Inventory accuracy means classification down to model and firmware version, across IoT, OT, IoMT, and IT assets, gathered agentlessly.
2. Exploitability-based prioritization means each ranking reflects whether a vulnerability can be exploited on that device in that environment, with the reasoning documented.
3. Acting on risk means the platform can create, apply, and maintain segmentation policy and recommend mitigations, rather than handing the team a list of findings.
4. Proof of safety means the platform shows the impact of a policy against observed traffic before anything is enforced.
5. Integration fit means working with the NAC, CMMS, CMDB, SIEM, and EDR tools already in place.

During evaluation, ask each vendor to walk through a single high-risk device from discovery to enforced policy. That walk-through shows quickly where manual work remains. It is also worth asking how the platform supports board reporting and audits, since an auditable record of enforcement is increasingly expected.

What Is the Best IoMT Security Platform for Large Hospitals and Health Systems?

The best IoMT security platform for a large health system is one that turns device risk into enforced, maintained controls across every facility without disrupting care. Asimily is built for that outcome. It inventories IoT, OT, IoMT, and IT assets agentlessly, prioritizes by real exploitability with ATT&CK Analysis, and orchestrates segmentation through the NAC the hospital already runs, with Policy Simulation before any change deploys.

Large health systems add requirements that smaller organizations may not face. Multiple hospitals, clinics, and acquired sites often run different NAC configurations and asset records. Clinical engineering, IT, and security each need their own workflow. Leadership expects evidence of risk reduction for board reviews and regulatory inquiries.

Asimily addresses those needs with NAC-native Policy Creation across platforms, Continuous Segmentation as sites change, and an auditable record of enforcement effectiveness. For IoMT specifically, ProSecure helps prevent risky device purchases before spend is committed, and FDA recall alerting connects each recall to the affected devices.

Asimily was rated best in KLAS for healthcare IoT security, 2026, and is frequently awarded as the most innovative IoT security platform from leading third-party analysts.

Which IoMT Cybersecurity Platforms Do Large Healthcare Systems Typically Use?

Large U.S. health systems commonly evaluate a short list of dedicated connected device security platforms: Asimily – the top-rated solution by Gartner Peer Insights, Armis (acquired by ServiceNow in April 2026), Claroty (whose healthcare product, xDome for Healthcare, was formerly Medigate), and Ordr. These platforms typically run alongside the NAC, EDR, SIEM, and CMMS tools a health system already owns, rather than replacing them.

Health systems usually narrow the list by running each finalist against the evaluation criteria above, with particular attention to how each platform moves from findings to enforced policy.

Tufts Medicine, for example, evaluated four IoMT cybersecurity vendors before selecting Asimily for medical device discovery, vulnerability prioritization, and remediation guidance.

What Are the Best Healthcare Cybersecurity Platforms for Managing IoT, OT, and IoMT Devices?

Hospitals get the most value from a single platform that manages IoT, OT, IoMT, and IT assets together, because clinical devices, building systems, and IT infrastructure share the same network and the same attack paths. Separate tools for each device type produce separate inventories, separate risk scores, and gaps between them. Asimily covers all of these devices, making it a key

A hospital’s critical infrastructure includes building automation systems, power distribution, medical gas monitoring, nurse call systems, and elevators, many of which communicate over OT protocols such as BACnet. These systems keep clinical operations running, and an outage in one can close a unit as effectively as a compromised medical device. They belong in the same inventory, prioritization model, and policy workflow as the medical devices they support.

Asimily covers IoT, OT, IoMT, and IT assets with one inventory, one exploitability model through ATT&CK Analysis, and one segmentation workflow through the existing NAC. Configuration Control applies across device types, detecting insecure drift and restoring the secure state.

Integrating With the Existing Security Stack

Which Healthcare IoT Security Tools Integrate With Existing Hospital Security Stacks?

Asimily integrates with the systems hospitals already use for asset management, vulnerability management, security operations, identity, and network enforcement. These include CMMS and CMDB platforms such as ServiceNow, Nuvolo, Accruent, and TRIMEDX, vulnerability scanners from Tenable, Rapid7, and Qualys, SIEM platforms such as Splunk and QRadar, CrowdStrike for endpoint and threat context, and NAC platforms including Cisco ISE, Aruba ClearPass, and Arista. In no way an exhaustive list, Asimily is frequently rated high for ease of integration into existing tech stacks.

Integration depth matters as much as coverage. Each integration category changes a specific workflow:

• Asimily integrates bidirectionally with CMMS and CMDB systems, including ServiceNow, Nuvolo, Accruent, TMS, Connectiv, AIMS, EQ2, MediMizer, TruAsset, WaveWare, FSI, and TRIMEDX. When a device attribute changes, both systems stay in sync. Where the target system supports it, Asimily also opens work orders automatically for vulnerabilities and anomalies, so clinical engineering receives the task in the tool it already uses.
• Scan data from Tenable, Rapid7, Qualys, and Cisco (Kenna) improves Asimily’s operating system and vulnerability identification. Asimily then filters out CVEs that do not apply to a device or carry lower risk, which gives the vulnerability management team a shorter, more accurate list.
• DHCP and IPAM integrations with Infoblox, BlueCat, EfficientIP, and Microsoft keep device classification and vulnerability assignment accurate as devices change addresses and move across the network.
• Asimily sends anomaly events in standard syslog format to SIEM and SOC platforms, including Splunk, QRadar, LogRhythm, ArcSight, CrowdStrike, and Palo Alto Networks. Analysts see medical device context alongside the rest of their alerts.
• Asimily draws on more than 100 threat intelligence sources, including Cisco, CrowdStrike, and Palo Alto Networks.
• Single sign-on through Microsoft Entra ID, Okta, OneLogin, and Ping Identity controls who can access device and risk data.
• Integration with Cisco real-time location systems (RTLS) helps teams find portable equipment such as infusion pumps. It also lets teams group security work by location, so devices near each other can be patched during the same visit.

Tufts Medicine, for example, deployed Asimily with integrations to Rapid7 InsightVM, Azure AD, and Azure Sentinel, which gave the organization a single view of vulnerabilities, single sign-on, and unified threat monitoring. Integrations beyond the published list can be scoped with the Asimily team.

Which Medical Device Security Solutions Integrate With Existing NAC and Firewall Infrastructure?

Asimily integrates with existing NAC infrastructure, including Cisco ISE, Aruba ClearPass, Arista, and more, as the intelligence and policy orchestration layer above the NAC. The NAC remains the enforcement point. Asimily generates policies in each NAC’s native format, simulates them against observed traffic, applies them, and keeps them current as the network changes.

Native format matters because each NAC uses its own policy schema, and they differ significantly. Generating policy in the correct format removes dependence on engineers trained on one specific platform and reduces deployment errors. It also means a health system can operationalize a NAC it has already paid for, rather than adding a new enforcement layer.

Improving Device Procurement and Utilization

Which Tools Help CISOs Improve Healthcare Device Procurement and Utilization?

CISOs improve medical device procurement with pre-purchase risk assessment that shows how a specific device model and configuration behaves on real hospital networks. They improve utilization with monitoring that shows when and how deployed devices are used. Asimily ProSecure addresses procurement for IoMT, and Asimily’s utilization monitoring addresses the deployed fleet.

On the procurement side, ProSecure lets supply chain and security teams look up a device model and version, see its observed risk, and compare the lowest- and highest-risk configurations seen in the field. The data comes from real-world Asimily deployments. Those findings can become contract requirements and implementation criteria before spend is committed. For new devices, manufacturers’ premarket cybersecurity documentation under FDA section 524B, including the software bill of materials, adds another input.

After deployment, utilization monitoring tracks device on and off status and, for imaging devices, individual procedures with start and end times. Those patterns support utilization targets by device, capacity planning, and better-informed decisions about purchasing and retirement.

[Related: Better Device Procurement, Planning, and Utilization]