CVE-2017-12601 in OpenCV
Summary
by MITRE
OpenCV (Open Source Computer Vision Library) through 3.3 has a buffer overflow in the cv::BmpDecoder::readData function in modules/imgcodecs/src/grfmt_bmp.cpp when reading an image file by using cv::imread, as demonstrated by the 4-buf-overflow-readData-memcpy test case.
Be aware that VulDB is the high quality source for vulnerability data.
Analysis
by VulDB Data Team • 12/15/2022
The vulnerability CVE-2017-12601 represents a critical buffer overflow flaw within the OpenCV computer vision library version 3.3 and earlier. This issue specifically affects the cv::BmpDecoder::readData function located in the modules/imgcodecs/src/grfmt_bmp.cpp file, which is responsible for processing bitmap image files. The vulnerability manifests when the library processes malformed BMP image files through the cv::imread function, creating a scenario where memory corruption can occur during image parsing operations. The flaw is particularly concerning as it demonstrates a direct memory overflow condition that can be exploited by malicious actors through crafted image files.
The technical implementation of this vulnerability stems from insufficient input validation within the BMP file parsing routine. When the cv::BmpDecoder::readData function processes bitmap image data, it fails to properly validate the size parameters of various image components such as color table entries, pixel data structures, or file headers. This inadequate validation allows an attacker to construct a specially crafted BMP file that contains oversized data structures or malformed headers. The vulnerability specifically involves a memcpy operation that copies data into a buffer without proper bounds checking, leading to a classic stack-based buffer overflow condition. According to CWE-121, this represents a stack-based buffer overflow vulnerability that occurs when a program copies data into a buffer without verifying that the source data will fit within the destination buffer boundaries.
The operational impact of this vulnerability extends beyond simple memory corruption, as it creates potential pathways for arbitrary code execution within applications that utilize OpenCV for image processing. Any application leveraging cv::imread to load user-supplied or untrusted image files becomes susceptible to this attack vector, including web applications, mobile apps, and desktop software that incorporate OpenCV functionality. The vulnerability's exploitation potential aligns with ATT&CK technique T1203, which describes the use of malicious files to gain code execution, and T1059, which covers the execution of malicious code through legitimate system processes. Attackers can craft malicious BMP files that, when processed by vulnerable applications, trigger the buffer overflow and potentially allow remote code execution or system compromise.
Mitigation strategies for CVE-2017-12601 primarily focus on immediate software updates and input validation improvements. The most effective approach involves upgrading to OpenCV version 3.4.0 or later, where the buffer overflow has been addressed through proper bounds checking and input validation. Organizations should implement comprehensive image file validation routines that verify file headers, size parameters, and data structures before processing any image data. Additionally, applications should employ defensive programming techniques such as using safer string and memory manipulation functions, implementing proper error handling for image parsing operations, and establishing memory protection mechanisms like stack canaries or address space layout randomization. Security teams should also consider implementing network-based intrusion detection systems to monitor for suspicious image file patterns and establish secure coding practices that prevent similar buffer overflow vulnerabilities in custom image processing components. The vulnerability highlights the importance of proper input validation in multimedia processing libraries and demonstrates how seemingly benign file format parsing can become a critical security risk when proper bounds checking is omitted.