CVE-2017-17887 in ImageMagick
Summary
by MITRE
In ImageMagick 7.0.7-16 Q16, a memory leak vulnerability was found in the function GetImagePixelCache in magick/cache.c, which allows attackers to cause a denial of service via a crafted MNG image file that is processed by ReadOneMNGImage.
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Analysis
by VulDB Data Team • 01/19/2023
The vulnerability identified as CVE-2017-17887 represents a critical memory leak flaw within ImageMagick's image processing pipeline, specifically affecting version 7.0.7-16 Q16. This issue resides in the GetImagePixelCache function located within the magick/cache.c source file, demonstrating how seemingly minor implementation details can create significant security risks in multimedia processing libraries that handle diverse file formats. The vulnerability manifests when processing specially crafted MNG (Multiple Network Graphics) image files, which are commonly used for animations and complex image compositions. MNG files present unique challenges to image processing systems due to their complex structure and multi-frame nature, making them particularly susceptible to memory management flaws that can be exploited by malicious actors.
The technical exploitation of this vulnerability occurs through a carefully constructed MNG file that triggers the memory leak within the GetImagePixelCache function. When ImageMagick attempts to read and process such a malformed file, the function fails to properly release allocated memory resources, leading to progressive memory consumption that can eventually exhaust system resources. This memory leak is particularly insidious because it occurs during the image reading process, meaning that even a single malicious file can cause sustained memory growth in applications that utilize ImageMagick for image processing. The vulnerability operates at the level of memory management within the caching subsystem, where pixel data is temporarily stored during image processing operations, and the failure to properly clean up these resources creates a persistent memory drain that accumulates over time.
The operational impact of CVE-2017-17887 extends beyond simple resource exhaustion, creating significant denial of service conditions that can affect applications across multiple platforms and use cases. Systems that rely on ImageMagick for image processing, including web applications, content management systems, and digital asset management platforms, become vulnerable to sustained memory consumption attacks that can render services unavailable or significantly degraded. The vulnerability's exploitation requires minimal technical expertise, as attackers only need to craft a specific MNG file to trigger the memory leak, making it particularly dangerous in environments where users can upload or process untrusted image content. This creates a substantial risk for web applications that accept user-uploaded images, as a single malicious file can cause cascading failures throughout the application's memory management system.
Organizations utilizing ImageMagick should implement immediate mitigations to address this vulnerability, including updating to patched versions of the software that resolve the memory leak in the GetImagePixelCache function. The fix typically involves ensuring proper memory cleanup and resource management within the image processing pipeline, particularly when handling complex file formats like MNG that require extensive memory allocation. Additionally, implementing input validation and file format restrictions can help prevent exploitation by blocking potentially malicious MNG files from entering the processing pipeline. Security practitioners should consider deploying network-based detection mechanisms that can identify suspicious MNG file patterns and monitor for memory consumption anomalies that may indicate exploitation attempts. This vulnerability aligns with CWE-401, which specifically addresses improper release of memory, and represents a classic example of how memory management flaws can create persistent denial of service conditions in multimedia processing systems. The ATT&CK framework categorizes this vulnerability under privilege escalation and denial of service techniques, as it allows attackers to consume system resources and potentially gain unauthorized access to services through resource exhaustion attacks.