Medical device security gaps are now hospital security gaps

At a glance

What this is: This analysis argues that connected medical devices have become a hospital-wide attack surface because many are unpatched, unmanaged, and able to provide attackers with an internal foothold.

Why it matters: It matters because healthcare security teams need to govern OT and IoT devices with the same discipline they apply to core IT, or those devices will undermine segmentation, incident detection, and containment.

Context

Hospitals now operate large fleets of connected devices that were designed for clinical function, not security. When those devices sit on the same network as identity systems, electronic health records, and backup infrastructure, a weak device can become a pathway into much more sensitive parts of the environment.

The governance gap is not just patching. It is the mismatch between traditional enterprise security tools and unmanaged clinical technology that cannot safely run agents, cannot always be scanned aggressively, and often lives outside standard asset inventories. That creates an identity and access problem as well, because device access and internal network reach become de facto trust decisions.

Key questions

Q: What breaks when medical devices are not included in security governance?

A: Hospitals lose visibility into a large internal attack surface, and attackers can use unmanaged devices as quiet pivot points into EHR, directory, and backup systems. The control failure is not only patching. It is the absence of inventory, segmentation, and safe validation for assets that cannot be governed like standard endpoints.

Q: Why do unpatched medical devices create such a high ransomware risk?

A: They sit inside trusted hospital networks, often with outdated firmware and default access patterns, so compromise on one device can enable lateral movement without re-entering the perimeter. That increases the chance that ransomware operators can find persistence, reach critical systems, and disrupt care delivery from a single weak foothold.

Q: What are the signs that medical device segmentation is failing?

A: Warning signs include clinical devices reaching directory services or backup networks, unusual outbound traffic from device VLANs, and security tools that cannot explain which devices are present or how they are configured. If segmentation is real, those paths should be tightly constrained and observable.

Q: Should healthcare teams prioritise safe device testing over aggressive scanning?

A: Yes, because intrusive scanning can disrupt patient care and still miss the attack paths that matter most. The practical priority is passive discovery plus controlled validation of reachability, credential exposure, and pivot paths, so teams can reduce risk without creating clinical downtime.

Technical breakdown

Why medical devices create unmanaged trust boundaries

Medical devices behave like operational technology, not like standard endpoints. Many run legacy operating systems, expose management interfaces, and cannot tolerate intrusive scanning or endpoint agents. That means they sit outside the control assumptions behind conventional EDR, SIEM coverage, and patch-driven hardening. When a device is trusted simply because it is inside the network, the security model becomes location-based rather than identity-based. In practice, that leaves a large internal zone where access is granted by topology, not by verified device posture or strong authentication.

Practical implication: Treat connected medical devices as a separate trust boundary and govern their access as a distinct asset class, not as ordinary endpoints.

How default credentials and old firmware enable pivot paths

The article points to a predictable attack path: reconnaissance, exposed service discovery, initial access through default credentials or known vulnerabilities, and then lateral movement from the device into clinical systems. This is a classic internal pivot problem. If a device is unmanaged, the attacker does not need to defeat the perimeter again after entry. The device itself becomes the beachhead. In identity terms, the issue is not just authentication failure at the edge. It is the absence of lifecycle control over embedded credentials, firmware, and device access scope.

Practical implication: Inventory device credentials, firmware state, and reachable network paths together so you can remove the conditions that make pivoting possible.

Why clinical networks need safe validation, not aggressive scanning

Standard vulnerability management assumes you can probe assets freely and install controls where needed. Medical environments do not work that way. Aggressive scanning can disrupt care, so security teams often leave devices under-assessed rather than risk operational harm. That creates blind spots in the same place where attackers look for persistence and lateral movement. A safer model combines passive discovery, segmented monitoring, and specialist testing that simulates realistic attacker movement without interrupting clinical operations. The goal is to understand what an intruder could reach before the intrusion becomes a patient safety issue.

Practical implication: Use passive discovery and controlled testing to validate containment paths without relying on scans that could disrupt clinical devices.

Threat narrative

Attacker objective: The attacker wants a reliable internal foothold that can be used to move laterally into higher-value hospital systems and sustain access for ransomware or data theft.

1. Entry starts with reconnaissance of internet-exposed or internally visible medical devices using exposed model data, ports, or default services.
2. Credential or vulnerability abuse follows when the attacker uses default credentials, unpatched firmware, or weak management interfaces to take control of the device.
3. Escalation happens when the compromised device is used as a pivot point into clinical workstations, directory services, or backup systems.
4. Impact is reached when the attacker gains persistence inside the hospital network and can exfiltrate data, disrupt care, or support ransomware deployment.

Breaches seen in the wild

• McHire default password flaw 2025: A forgotten test admin account with the password 123456 and an API flaw exposed McDonald's McHire applicant records to researchers.
• SAP SQL Anywhere Monitor hard-coded credentials (CVE-2025-42890): Hard-coded credentials in SAP SQL Anywhere Monitor scored CVSS 10.0 (CVE-2025-42890); SAP removed the tool, and no exploitation was seen.

Read and download The State of NHI & AI Agent Breach Report 2026, covering 200+ breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Medical device fleets have become a governance problem, not just a clinical engineering problem. Once connected devices share internal networks with identity systems and EHR platforms, their access paths become part of the hospital trust model. That means the security programme has to account for network reach, credential state, and device lifecycle together. Practitioners should treat unmanaged clinical technology as a first-class governance domain, not an exception.

Device identity is the missing control plane in many hospitals. The article shows that the real risk is not simply whether a device is patched, but whether it is known, monitored, and constrained to the minimum network reach needed for its function. That maps to the broader identity security problem of unmanaged identities that cannot be certified, rotated, or offboarded cleanly. The practical conclusion is to govern device trust as an identity and access issue, not only as an asset inventory issue.

Medical device security gaps create attack surface management debt. If a programme cannot safely discover, classify, and validate these assets, it is carrying hidden risk that will surface during an incident. Clinical pivot-path exposure: this is the failure mode where attackers move from a weak device into systems that should never have been reachable in the first place. Security leaders need to assume that any unmanaged path inside the hospital network is already being tested by adversaries.

Segmentation is only meaningful when it is tested against realistic attacker movement. In healthcare, a nominal VLAN boundary is not evidence of containment if a compromised pump can still reach directory services or backup infrastructure. The right question is not whether the device is on a separate subnet, but whether the subnet actually limits blast radius under attack. Practitioners should validate segmentation against concrete pivot scenarios, not architecture diagrams.

The article reinforces that operational safety and cyber safety must be engineered together. Security teams cannot apply enterprise scanning and agent-based controls indiscriminately in environments that support patient care. The answer is a control model that combines passive visibility, safe testing, and restricted east-west movement. Practitioners should build controls that preserve care delivery while reducing the chance that a device compromise becomes a hospital-wide incident.

What this signals

Clinical devices now function as hidden identity and access dependencies. When a device can reach a hospital directory service or backup platform, its network position becomes a trust decision with patient-safety consequences. Security leaders should treat that reach as a governed entitlement, not as an accidental property of the local subnet.

Attack surface management for healthcare has to include non-standard assets. The programme challenge is not simply finding devices, but understanding which ones can move laterally, which ones cannot be scanned safely, and which ones still rely on default or long-lived access patterns. That is where traditional enterprise tooling tends to underperform.

Segmentation only reduces risk when it limits actual blast radius. A medical device network that is merely separated on paper still leaves the hospital exposed if compromised devices can touch identity systems or backup infrastructure. The next step for practitioners is to validate containment against realistic pivot paths, not architectural intent.

For practitioners

• Inventory every connected medical device Build and maintain a complete inventory of pumps, monitors, imaging systems, ventilators, and nurse call devices, including firmware version, ownership, network location, and support status.
• Segment clinical devices from critical systems Place medical device networks on tightly controlled segments that cannot directly reach EHR platforms, directory services, or backup infrastructure without explicit, monitored pathways.
• Replace default and shared device credentials Find devices still using vendor defaults or shared admin accounts and remove those trust assumptions before they become a lateral movement path.
• Use passive discovery and safe validation Combine passive asset discovery with specialist penetration testing that does not disrupt care but still validates realistic pivot paths from device to core systems.
• Monitor for anomalous device-network behaviour Track unusual connections, configuration changes, and outbound traffic from clinical device segments so you can detect pivot attempts before they reach sensitive systems.

Key takeaways

• Connected medical devices have shifted from a peripheral concern to a core hospital attack surface because many are unmanaged, old, and still reachable from critical internal systems.
• The most dangerous failure is not the device itself, but the combination of default access, weak visibility, and network paths that let an attacker pivot from clinical equipment to enterprise systems.
• Healthcare security teams need passive discovery, segmentation, and safe validation designed for patient-care environments, or device compromise will remain a practical route into the hospital.

Key terms

• Clinical Device Network: The part of a hospital environment where connected medical devices communicate with each other and with clinical systems. It often contains assets that cannot run standard agents or tolerate aggressive scanning, so it requires specialised visibility, containment, and access governance.
• Pivot Path: A pivot path is a sequence of systems, services, or identities an attacker can traverse to reach a target. It is useful for security analysis because it makes blast radius measurable and shows where segmentation or privilege reduction will have the biggest effect.
• Unmanaged Asset: A machine, workload, or identity that exists outside the organisation's normal control plane. Unmanaged assets often miss updates, monitoring, or lifecycle governance, which makes them disproportionately useful to attackers and difficult to account for during incident response.
• Segmentation: The practice of dividing an audience into groups so that messages, offers or experiences can be tailored. In identity terms, segmentation depends on reliable attributes, and it fails quickly when the source data is stale, duplicated or poorly governed.

Deepen your knowledge

NHI Mgmt Group covers identity security, NHI governance, and agentic AI through independent research, practitioner guides, and the NHI Foundation Level course, the industry's only accredited NHI security programme. It is built for practitioners who need a clearer control model for identities, access, and governance across modern environments.