CVE-2018-10601 in Patient Monitorinfo

Summary

by MITRE

IntelliVue Patient Monitors MP Series (including MP2/X2/MP30/MP50/MP70/NP90/MX700/800) Rev B-M, IntelliVue Patient Monitors MX (MX400-550) Rev J-M and (X3/MX100 for Rev M only), and Avalon Fetal/Maternal Monitors FM20/FM30/FM40/FM50 with software Revisions F.0, G.0 and J.3 have a vulnerability that exposes an "echo" service, in which an attacker-sent buffer to an attacker-chosen device address within the same subnet is copied to the stack with no boundary checks, hence resulting in stack overflow.

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Analysis

by VulDB Data Team • 02/15/2020

The vulnerability identified as CVE-2018-10601 affects a critical class of medical devices within the IntelliVue patient monitoring ecosystem, specifically targeting the MP Series monitors and certain MX series models along with Avalon fetal/maternal monitors. These devices operate within healthcare environments where patient safety and data integrity are paramount, making any security flaw potentially life-threatening. The affected hardware operates with software revisions F.0, G.0, and J.3, and represents a significant risk to medical device cybersecurity given the sensitive nature of patient monitoring systems.

The technical flaw manifests through an insecure implementation of an echo service functionality that lacks proper buffer boundary checking mechanisms. When an attacker sends a crafted buffer to a chosen device address within the same network subnet, the system processes this data without validating its size or content against predetermined stack boundaries. This fundamental design oversight allows for direct stack memory corruption through what is essentially a buffer overflow condition, where attacker-controlled data exceeds the allocated stack space and overwrites adjacent memory locations. The vulnerability stems from insufficient input validation and memory management practices that violate established security principles for embedded systems.

The operational impact of this vulnerability extends beyond simple denial of service scenarios, potentially enabling attackers to execute arbitrary code on affected devices. This could result in complete system compromise, allowing unauthorized access to critical patient monitoring data, manipulation of vital signs displayed to healthcare providers, or even complete device shutdown during critical patient care situations. The attack vector requires only network access within the same subnet, making it particularly dangerous in healthcare environments where medical devices often operate on shared networks with limited segmentation. The vulnerability aligns with CWE-121, which describes unsafe use of stack-based buffer, and represents a classic example of how insufficient input validation can lead to memory corruption attacks.

Mitigation strategies for this vulnerability should include immediate software updates from the vendor to patch the buffer overflow condition, network segmentation to isolate critical medical devices from general network traffic, and implementation of network access controls to restrict communication to only authorized devices. Organizations should also conduct comprehensive vulnerability assessments of their medical device inventory to identify similar insecure implementations, while implementing continuous monitoring for anomalous network traffic patterns that might indicate exploitation attempts. The remediation process must be carefully coordinated with healthcare providers to minimize disruption to patient care, following industry best practices outlined in NIST SP 800-82 for industrial control systems security and aligning with healthcare cybersecurity frameworks such as those recommended by the HHS and HITRUST standards. This vulnerability demonstrates the critical importance of applying secure coding practices to embedded medical devices and the potential consequences of inadequate memory management in life-critical systems.

Reservation

05/01/2018

Disclosure

06/05/2018

Moderation

accepted

CPE

ready

EPSS

0.00117

KEV

no

Activities

very low

Sources

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