CVE-2017-11170 in ImageMagick
Summary
by MITRE
The ReadTGAImage function in coders\tga.c in ImageMagick 7.0.5-6 has a memory leak vulnerability that can cause memory exhaustion via invalid colors data in the header of a TGA or VST file.
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Analysis
by VulDB Data Team • 12/12/2022
The vulnerability identified as CVE-2017-11170 resides within the ImageMagick image processing library, specifically in the ReadTGAImage function located in the coders/ga.c file. This flaw represents a memory management issue that manifests when processing TGA (Truevision TGA) or VST (Vista) image files with malformed header data containing invalid color information. The vulnerability classifies under CWE-401 as a failure to release memory resources, creating a persistent memory leak condition that can accumulate over time. Attackers can exploit this weakness by crafting malicious TGA or VST files that contain malformed color data in their headers, triggering the memory allocation without subsequent deallocation. The issue is particularly concerning because it operates at the foundational level of image processing, where applications frequently handle untrusted input from various sources including web uploads, email attachments, and file transfers.
The technical exploitation of this vulnerability occurs when the ReadTGAImage function processes image headers containing invalid color specifications that do not conform to the expected TGA format specifications. During parsing of these malformed headers, the function allocates memory to store color data but fails to properly release this memory when encountering invalid color information. This memory leak can be exacerbated through repeated processing of malicious files, leading to progressive memory consumption that eventually results in memory exhaustion. The vulnerability is particularly dangerous in server environments where ImageMagick is used for image processing tasks, as attackers can cause denial of service conditions by repeatedly submitting specially crafted files. The memory leak behavior aligns with ATT&CK technique T1499.004 which describes resource exhaustion attacks targeting memory resources.
The operational impact of CVE-2017-11170 extends beyond simple denial of service conditions, as it can severely affect system stability and availability in production environments. When exploited in web applications, content management systems, or file processing services that utilize ImageMagick, the vulnerability can cause service degradation or complete system crashes. The memory exhaustion effect can be particularly devastating in containerized environments or cloud deployments where memory resources are strictly limited and monitored. Organizations using ImageMagick for image processing workflows face significant risk as this vulnerability can be exploited through various attack vectors including web application uploads, automated file processing pipelines, and batch processing operations. The vulnerability also impacts the broader security ecosystem since many applications rely on ImageMagick for image manipulation, creating a cascading effect where exploitation in one application can affect multiple systems.
Mitigation strategies for CVE-2017-11170 should focus on immediate patching of ImageMagick installations to versions that address the memory leak issue in the ReadTGAImage function. System administrators should implement input validation measures that filter or reject TGA and VST files before processing, particularly in environments where untrusted user input is handled. Network-based protections can include implementing file type validation and content filtering at perimeter defenses to prevent malicious files from reaching systems that utilize ImageMagick. Additionally, monitoring for abnormal memory usage patterns in applications that process images can help detect exploitation attempts. The vulnerability demonstrates the importance of proper memory management in image processing libraries and highlights the need for robust input validation and resource cleanup procedures. Organizations should also consider implementing sandboxing techniques for image processing operations and regularly auditing their image handling code for similar memory management issues. The fix for this vulnerability typically involves proper memory deallocation when invalid color data is encountered, ensuring that all allocated resources are released regardless of processing outcomes.