CVE-2021-3933 in OpenEXR
Summary
by MITRE • 03/25/2022
An integer overflow could occur when OpenEXR processes a crafted file on systems where size_t < 64 bits. This could cause an invalid bytesPerLine and maxBytesPerLine value, which could lead to problems with application stability or lead to other attack paths.
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Analysis
by VulDB Data Team • 03/27/2022
The vulnerability identified as CVE-2021-3933 represents a critical integer overflow condition within the OpenEXR image processing library that affects systems with 32-bit size_t definitions. This flaw manifests when the library processes maliciously crafted image files that trigger arithmetic operations resulting in overflow conditions. The vulnerability specifically targets environments where the size_t data type is smaller than 64 bits, creating a scenario where legitimate memory calculations exceed the maximum representable value for the data type, thereby corrupting critical internal variables. The affected OpenEXR implementation fails to properly validate input parameters during file parsing operations, particularly when determining memory allocation sizes for image data processing.
The technical exploitation of this vulnerability occurs through manipulation of image file headers and metadata fields that control memory allocation calculations. When the library encounters crafted values in these fields, the arithmetic operations used to compute bytesPerLine and maxBytesPerLine variables result in integer overflow conditions. This overflow produces invalid memory allocation sizes that can cause memory corruption, buffer overflows, or memory access violations. The vulnerability stems from inadequate input validation and lack of proper bounds checking during the parsing phase of image file processing, allowing attackers to craft malicious files that trigger these arithmetic overflows. The flaw is categorized under CWE-190 as an integer overflow condition and aligns with ATT&CK technique T1203 for exploitation of input validation weaknesses in image processing applications.
The operational impact of CVE-2021-3933 extends beyond simple application instability to potentially enable more sophisticated attack vectors including remote code execution or privilege escalation. When applications using the vulnerable OpenEXR library process malicious image files, the corrupted memory allocation values can lead to memory corruption that attackers might exploit to execute arbitrary code. The vulnerability affects any application that relies on OpenEXR for image processing, including professional video editing software, digital content creation tools, and image rendering applications. Systems running on 32-bit architectures are particularly susceptible, though the issue can manifest on 64-bit systems when the size_t type is constrained. The instability introduced by this vulnerability can cause applications to crash or behave unpredictably, potentially leading to denial of service conditions that impact legitimate users and operations.
Mitigation strategies for CVE-2021-3933 should prioritize immediate patching of affected OpenEXR library versions, with security updates addressing the integer overflow conditions in memory allocation calculations. Organizations should implement input validation measures that specifically check for suspicious values in image file headers and metadata fields, particularly those related to image dimensions and memory allocation parameters. Application developers should employ defensive programming techniques including bounds checking, overflow detection, and proper error handling during image processing operations. Network segmentation and file validation controls can help prevent the execution of malicious image files in critical systems. Additionally, monitoring systems should be configured to detect unusual memory allocation patterns or application crashes that might indicate exploitation attempts. The vulnerability highlights the importance of proper integer handling in security-critical applications and demonstrates the necessity of comprehensive input validation in multimedia processing libraries that handle untrusted data sources.