CVE-2017-17760 in OpenCV
Summary
by MITRE
OpenCV 3.3.1 has a Buffer Overflow in the cv::PxMDecoder::readData function in grfmt_pxm.cpp, because an incorrect size value is used.
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Analysis
by VulDB Data Team • 01/19/2023
The vulnerability CVE-2017-17760 represents a critical buffer overflow condition within the OpenCV computer vision library version 3.3.1, specifically within the cv::PxMDecoder::readData function located in the grfmt_pxm.cpp source file. This flaw occurs when processing PXM image format files, which are part of the portable anymap format family commonly used for storing raster graphics. The buffer overflow arises from an improper handling of size calculations during the decoding process, where an incorrect size value is utilized when allocating memory for image data structures.
The technical implementation of this vulnerability stems from a fundamental error in memory management within the image parsing routine. When the PxM decoder encounters a malformed PXM file, the size parameter extracted from the file header does not properly account for the actual data requirements, leading to insufficient memory allocation. This discrepancy creates a scenario where subsequent data reads exceed the allocated buffer boundaries, potentially allowing attackers to overwrite adjacent memory regions. The flaw falls under CWE-121, which describes stack-based buffer overflow conditions, and specifically relates to improper validation of input data sizes during file processing operations.
The operational impact of this vulnerability extends significantly across various applications that utilize OpenCV for image processing, particularly those handling untrusted image inputs from web services, file uploads, or external sources. Attackers could exploit this condition by crafting malicious PXM files designed to trigger the buffer overflow during image loading operations, potentially leading to arbitrary code execution on systems running vulnerable OpenCV versions. This represents a severe security risk in environments where image processing libraries handle user-provided content, as it could enable remote code execution without user interaction. The vulnerability aligns with ATT&CK technique T1203, which covers exploitation of software vulnerabilities through malformed input data processing.
Mitigation strategies for CVE-2017-17760 primarily involve immediate upgrading to OpenCV versions that have patched this buffer overflow condition, specifically versions 3.4.1 and later where the size validation logic has been corrected. Organizations should also implement input validation measures that sanitize image file headers before processing, employ memory-safe programming practices in custom applications, and consider deploying sandboxed environments for image processing tasks. Additionally, network segmentation and access controls should be implemented to limit exposure of systems running vulnerable OpenCV versions, while regular security assessments should verify that all image processing components have been properly updated to prevent exploitation attempts targeting this specific buffer overflow vulnerability.