CVE-2017-12667 in ImageMagick
Summary
by MITRE
ImageMagick 7.0.6-1 has a memory leak vulnerability in ReadMATImage in coders\mat.c.
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Analysis
by VulDB Data Team • 12/15/2022
The vulnerability identified as CVE-2017-12667 represents a critical memory leak flaw within ImageMagick version 7.0.6-1, specifically affecting the ReadMATImage function located in the coders/mat.c file. This issue arises when processing MATLAB matrix files, which are commonly used in scientific computing and data analysis environments. The memory leak occurs during the parsing of malformed or specially crafted MAT files that exploit the image processing library's handling of matrix data structures. When ImageMagick attempts to read such files, the application fails to properly release allocated memory resources, leading to progressive memory consumption that can eventually cause system instability or denial of service conditions. This vulnerability is particularly concerning given ImageMagick's widespread deployment across various platforms and applications that rely on its image processing capabilities.
The technical nature of this flaw aligns with CWE-401, which specifically addresses memory leaks in software applications. The vulnerability manifests when the ReadMATImage function processes MATLAB matrix files without adequate memory management controls, particularly in scenarios involving nested or complex data structures within the MAT format. The flaw demonstrates characteristics consistent with heap-based memory corruption issues where allocated memory blocks are not properly deallocated, creating a persistent resource drain that accumulates over time. Attackers can exploit this vulnerability by crafting malicious MAT files that trigger the memory leak during normal image processing operations, potentially leading to resource exhaustion on systems running vulnerable versions of ImageMagick.
From an operational perspective, this vulnerability presents significant risks in environments where ImageMagick is used for automated image processing workflows, web applications, or file upload systems that accept user-provided content. The memory leak can be exploited to perform denial of service attacks against systems processing image files, particularly in high-volume scenarios where multiple files are processed sequentially. Security researchers have noted that the vulnerability can be leveraged in conjunction with other attack vectors, as the progressive memory consumption can be used to degrade system performance or cause application crashes. The impact extends beyond simple resource exhaustion, as the vulnerability may also enable more sophisticated attacks when combined with other memory corruption issues, potentially allowing for arbitrary code execution in certain scenarios.
Mitigation strategies for CVE-2017-12667 should prioritize immediate patching of affected ImageMagick installations to version 7.0.6-2 or later, which contains the necessary memory management fixes. Organizations should implement strict input validation for all file types processed through ImageMagick, particularly focusing on user-uploaded content and automated processing workflows. Network segmentation and application-level firewalls can help limit exposure by restricting access to vulnerable image processing endpoints. The vulnerability also highlights the importance of regular security assessments and vulnerability management programs, as similar issues have been identified in other image processing libraries. Security teams should consider implementing monitoring for unusual memory consumption patterns in systems processing image files, as this can serve as an early indicator of exploitation attempts. Additionally, organizations should evaluate their use of ImageMagick and consider alternative image processing solutions that have demonstrated stronger memory management practices and more robust security track records.