CVE-2017-10800 in GraphicsMagick
Summary
by MITRE
When GraphicsMagick 1.3.25 processes a MATLAB image in coders/mat.c, it can lead to a denial of service (OOM) in ReadMATImage() if the size specified for a MAT Object is larger than the actual amount of data.
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Analysis
by VulDB Data Team • 12/09/2022
The vulnerability identified as CVE-2017-10800 represents a critical denial of service flaw within GraphicsMagick version 1.3.25 that specifically affects the processing of MATLAB image files. This issue manifests in the coders/mat.c module where the ReadMATImage() function fails to properly validate the size parameters of MAT objects during file parsing operations. The flaw occurs when the size field within a MATLAB file format specification indicates a data size that exceeds the actual available data within the file, creating a scenario where the application attempts to allocate memory resources that cannot be satisfied, ultimately leading to out-of-memory conditions that cause the application to crash or become unresponsive.
This vulnerability operates at the intersection of improper input validation and memory management within image processing libraries, making it particularly dangerous in environments where GraphicsMagick is used to process untrusted image files from external sources. The technical implementation flaw resides in the lack of bounds checking mechanisms that should validate whether the declared data size in the MAT file format actually corresponds to the available data within the file structure. When GraphicsMagick attempts to read such malformed MATLAB files, it allocates memory based on the inflated size specification without verifying the actual data availability, resulting in resource exhaustion that manifests as a denial of service condition.
The operational impact of this vulnerability extends beyond simple application crashes to potentially affect broader system availability in scenarios where GraphicsMagick is deployed as part of larger processing pipelines or web services. Attackers could exploit this weakness by crafting malicious MATLAB image files that contain oversized size fields, causing legitimate applications using GraphicsMagick to consume excessive memory resources or crash entirely. This makes the vulnerability particularly concerning for web applications, content management systems, and automated processing services that rely on GraphicsMagick for image handling operations, as such attacks could be used to disrupt service availability or consume system resources.
From a cybersecurity perspective, this vulnerability aligns with CWE-129, which addresses improper validation of input boundaries, and demonstrates how inadequate bounds checking can lead to resource exhaustion attacks. The flaw also maps to ATT&CK technique T1499.004, which covers network denial of service attacks through resource exhaustion, as the vulnerability enables attackers to consume system resources in a manner that disrupts normal application functionality. Organizations utilizing GraphicsMagick should implement immediate mitigations including updating to patched versions, implementing input validation measures, and deploying sandboxing techniques to isolate image processing operations. Additionally, network-level filtering and rate limiting mechanisms can help reduce the impact of such attacks by preventing rapid exploitation attempts and limiting the damage potential of individual malicious file submissions.