CVE-2017-12672 in ImageMagick
Summary
by MITRE
In ImageMagick 7.0.6-3, a memory leak vulnerability was found in the function ReadMATImage in coders/mat.c, which allows attackers to cause a denial of service.
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Analysis
by VulDB Data Team • 12/15/2022
The vulnerability identified as CVE-2017-12672 represents a critical memory leak flaw within ImageMagick version 7.0.6-3, specifically affecting the ReadMATImage function located in the coders/mat.c source file. This memory leak occurs when processing MATLAB matrix image files, creating a condition where allocated memory is not properly released during the image parsing process. The flaw manifests when the software encounters malformed or specially crafted MAT files that trigger the memory allocation routine without subsequent deallocation, leading to progressive memory consumption over time.
This vulnerability operates at the intersection of software security and resource management, where improper memory handling creates an exploitable condition that can be leveraged for denial of service attacks. The technical implementation involves the ReadMATImage function failing to correctly manage memory resources when processing certain data structures within MATLAB matrix files, causing memory fragmentation and eventual system resource exhaustion. The flaw demonstrates characteristics consistent with CWE-401, which describes improper release of memory resources, and represents a classic example of how file format parsing can introduce security risks through memory management errors.
The operational impact of CVE-2017-12672 extends beyond simple resource consumption, as it can be exploited by malicious actors to systematically degrade system performance or cause complete service unavailability. Attackers can craft specific MAT files that, when processed by vulnerable ImageMagick installations, will continuously allocate memory without release, leading to progressive system slowdowns or complete system crashes. This vulnerability affects systems that process user-uploaded images or handle automated image processing workflows, making it particularly dangerous in web applications, content management systems, and file processing services that utilize ImageMagick for image conversion and manipulation.
The exploitation of this vulnerability aligns with ATT&CK technique T1499.004, which covers resource exhaustion attacks through memory consumption, and demonstrates how seemingly benign file format processing can become a vector for system compromise. Organizations running vulnerable versions of ImageMagick face significant risk when processing untrusted image files, as the memory leak can be triggered through various attack vectors including web uploads, automated processing pipelines, or file sharing systems. The vulnerability's impact is particularly severe in cloud environments or shared hosting scenarios where multiple users may be processing images through the same vulnerable service.
Mitigation strategies for CVE-2017-12672 require immediate patching of ImageMagick to version 7.0.6-3 or later, which contains the necessary memory management fixes for the ReadMATImage function. Organizations should implement strict file validation and sanitization procedures, particularly for image processing workflows that handle untrusted input. Network segmentation and access controls can help limit the potential impact of exploitation, while monitoring systems should track memory usage patterns to detect anomalous resource consumption that might indicate exploitation attempts. Additionally, implementing sandboxed processing environments and limiting the maximum memory allocation for image processing tasks can provide additional layers of defense against this memory leak vulnerability.