CVE-2019-5085 in LEADTOOLS
Summary
by MITRE
An exploitable code execution vulnerability exists in the DICOM packet-parsing functionality of LEADTOOLS libltdic.so, version 20.0.2019.3.15. A specially crafted packet can cause an integer overflow, resulting in heap corruption. An attacker can send a packet to trigger this vulnerability.
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Analysis
by VulDB Data Team • 03/10/2024
The vulnerability identified as CVE-2019-5085 represents a critical code execution flaw within the LEADTOOLS libltdic.so library version 20.0.2019.3.15 which processes DICOM (Digital Imaging and Communications in Medicine) packets. This library serves as a foundational component for medical imaging applications, handling the complex data structures and protocols essential for radiological and medical imaging systems. The flaw resides in the packet-parsing functionality that processes incoming DICOM data streams, making it a potential attack vector for adversaries targeting healthcare systems that rely on this imaging software. DICOM protocol compliance is mandatory in healthcare environments, creating a high-value target for threat actors seeking to exploit medical imaging infrastructure.
The technical implementation of this vulnerability stems from an integer overflow condition that occurs during the parsing of DICOM packets. When processing malformed packet data, the library fails to properly validate integer values, leading to an arithmetic overflow that corrupts heap memory structures. This type of vulnerability falls under CWE-190, Integer Overflow or Wraparound, which is a well-documented weakness in software security. The integer overflow specifically manifests when the library attempts to allocate memory based on parsed packet headers that contain maliciously crafted values exceeding the maximum representable integer. The heap corruption resulting from this overflow creates opportunities for memory corruption attacks, potentially allowing attackers to execute arbitrary code with the privileges of the affected application.
The operational impact of this vulnerability extends beyond simple code execution, as it presents a significant threat to healthcare infrastructure security. Medical imaging systems running vulnerable versions of LEADTOOLS could be compromised through remote network-based attacks, potentially leading to data breaches, system disruption, or unauthorized access to sensitive patient medical records. Healthcare organizations that depend on these imaging systems face substantial risk since DICOM protocols are widely implemented across hospitals, clinics, and medical facilities worldwide. The vulnerability's remote exploitability means attackers can target systems without requiring physical access, making it particularly dangerous in networked healthcare environments where imaging systems are often connected to broader hospital networks. This threat is amplified by the fact that many medical devices and systems rely on third-party libraries like LEADTOOLS, creating cascading security implications throughout healthcare IT ecosystems.
Mitigation strategies for CVE-2019-5085 should prioritize immediate patching of the affected LEADTOOLS library to version 20.0.2019.3.16 or later, which includes the necessary fixes for the integer overflow condition. Organizations should implement network segmentation to limit access to medical imaging systems and deploy intrusion detection systems that can identify anomalous DICOM packet traffic patterns. Additionally, input validation should be enhanced at network boundaries to filter out malformed DICOM packets before they reach vulnerable applications. Security teams should conduct comprehensive vulnerability assessments of their entire medical imaging infrastructure, as similar integer overflow vulnerabilities may exist in other components of the healthcare IT stack. The ATT&CK framework categorizes this vulnerability under T1203, Exploitation for Client Execution, and T1071.1003, Application Layer Protocol: Dns Tunneling, as attackers may leverage this flaw to establish persistent access to healthcare networks through compromised imaging systems. Organizations should also consider implementing network monitoring solutions specifically designed for medical imaging protocols to detect and prevent exploitation attempts targeting such critical healthcare infrastructure components.