CVE-2021-26945 in OpenEXR
Summary
by MITRE • 06/08/2021
An integer overflow leading to a heap-buffer overflow was found in OpenEXR in versions before 3.0.1. An attacker could use this flaw to crash an application compiled with OpenEXR.
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Analysis
by VulDB Data Team • 06/11/2021
The vulnerability identified as CVE-2021-26945 represents a critical integer overflow condition within the OpenEXR image processing library that can lead to heap buffer overflow conditions. This flaw exists in OpenEXR versions prior to 3.0.1 and affects applications that utilize the library for processing high dynamic range image files. The vulnerability stems from insufficient input validation during the processing of image metadata, specifically when handling certain header fields that define image dimensions and data structures. When an attacker crafts a malicious image file with malformed dimensions or excessively large values in the header fields, the integer overflow occurs during calculations that determine buffer allocation sizes. This overflow corrupts adjacent memory regions in the heap, potentially leading to arbitrary code execution or application crashes. The vulnerability is particularly concerning because OpenEXR is widely used in professional image processing workflows, including film production, visual effects, and digital art applications where users may encounter untrusted image files from various sources.
The technical implementation of this vulnerability involves the manipulation of integer arithmetic operations within the image parsing routines of OpenEXR. Specifically, when processing image headers, the library performs calculations to determine the size of buffers needed to store image data based on dimensions specified in the file. When these dimensions are crafted to exceed the maximum representable value for the integer type used in the calculation, an integer overflow occurs. The resulting corrupted buffer size calculation leads to insufficient memory allocation for the actual image data, creating a heap buffer overflow condition. This type of vulnerability is categorized under CWE-190 as Integer Overflow or Wraparound, which is a well-documented weakness in software security practices. The flaw demonstrates poor input validation and inadequate bounds checking in memory allocation routines, which are fundamental security requirements in memory-safe programming practices.
The operational impact of CVE-2021-26945 extends beyond simple application crashes to potentially enable remote code execution in scenarios where vulnerable applications process untrusted image files. Attackers can exploit this vulnerability by crafting specially formatted OpenEXR files that trigger the integer overflow condition when opened or processed by applications using the vulnerable library. This creates a significant risk in environments where users regularly handle image files from unknown or untrusted sources, such as online marketplaces, social media platforms, or collaborative creative workflows. The vulnerability affects not only end-user applications but also server-side applications that process image uploads, making it a critical concern for content management systems, cloud storage providers, and digital asset management platforms. The exploitation requires minimal privileges and can be automated, making it particularly dangerous in large-scale deployment scenarios where multiple applications depend on the same vulnerable library version.
Mitigation strategies for CVE-2021-26945 primarily involve immediate upgrade to OpenEXR version 3.0.1 or later, which includes proper bounds checking and integer overflow protection mechanisms. Organizations should conduct comprehensive vulnerability assessments to identify all applications and systems that utilize the affected library, particularly those in critical workflows such as film production pipelines, visual effects rendering, and digital asset management systems. Additionally, implementing input validation measures at the application level can provide defense-in-depth protection, including sanitizing image file headers before processing and implementing strict size limits for image dimensions. Network segmentation and file access controls should be enforced to limit exposure of vulnerable systems to untrusted image files. The vulnerability also highlights the importance of regular security updates and vulnerability management processes, as it demonstrates how seemingly minor library flaws can have significant security implications. Security teams should monitor for similar patterns in other image processing libraries and ensure that all third-party dependencies are regularly updated to address known vulnerabilities. This case study exemplifies the ATT&CK technique of exploitation through malformed input, specifically targeting memory corruption vulnerabilities in common libraries used across the software development ecosystem.