CVE-2017-12140 in ImageMagick
Summary
by MITRE
The ReadDCMImage function in coders\dcm.c in ImageMagick 7.0.6-1 has an integer signedness error leading to excessive memory consumption via a crafted DCM file.
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Analysis
by VulDB Data Team • 12/14/2022
The vulnerability identified as CVE-2017-12140 resides within the ReadDCMImage function of ImageMagick's DICOM coder implementation, specifically in the coders\dcm.c file of version 7.0.6-1. This flaw represents a critical security issue that manifests through improper handling of integer signedness during the processing of DICOM (Digital Imaging and Communications in Medicine) image files. The vulnerability stems from a fundamental error in how the software interprets signed and unsigned integer values when parsing DICOM metadata, creating a scenario where maliciously crafted DCM files can trigger excessive memory allocation patterns.
The technical root cause of this vulnerability lies in an integer signedness error that occurs during the parsing of DICOM file headers and metadata structures. When ImageMagick attempts to read DICOM files, it processes various fields that contain dimension and size information. The flaw emerges when the software incorrectly treats a signed integer value as unsigned during memory allocation calculations, causing the system to allocate far more memory than necessary for processing legitimate DICOM files. This misinterpretation leads to a denial of service condition where the application consumes excessive system resources, potentially leading to system instability or complete resource exhaustion.
From an operational perspective, this vulnerability presents a significant risk to organizations relying on ImageMagick for image processing workflows, particularly in healthcare environments where DICOM files are commonly processed. The impact extends beyond simple resource exhaustion as it can be exploited by attackers to perform denial of service attacks against systems processing DICOM images. The vulnerability affects any system that processes DICOM files through ImageMagick, making it particularly dangerous in medical imaging systems, radiology workstations, and healthcare information systems where such processing is routine. The integer signedness error allows attackers to craft malicious DICOM files that, when processed, cause the application to consume memory proportional to the maliciously specified values rather than the actual file size.
The exploitation of this vulnerability aligns with attack patterns documented in the ATT&CK framework under the adversary technique of resource exhaustion, specifically targeting application-level vulnerabilities that can be leveraged for denial of service. This vulnerability maps to CWE-195, which describes signed to unsigned conversion errors, and CWE-196, which covers unsigned to signed conversion errors, demonstrating the complexity of integer handling in image processing applications. The flaw also relates to CWE-400, which covers resource exhaustion vulnerabilities, as the excessive memory consumption directly leads to system resource depletion. Organizations using ImageMagick in production environments should consider this vulnerability as a high-priority threat, particularly in systems where image processing is automated or integrated into critical workflows.
Mitigation strategies for CVE-2017-12140 primarily involve updating ImageMagick to versions that address this specific integer signedness error, typically through patches released by the ImageMagick development team. System administrators should implement strict input validation and file type checking for DICOM files, particularly when processing untrusted content. Network-level controls such as firewalls and intrusion detection systems can be configured to monitor and restrict access to systems processing DICOM files. Additionally, organizations should implement memory limits and process monitoring to detect and prevent excessive memory consumption patterns that may indicate exploitation attempts. The vulnerability underscores the importance of regular security updates and proper input validation in image processing applications, particularly those handling medical imaging data where system reliability is paramount.