CVE-2022-43595 in OpenImageIO
Summary
by MITRE • 12/23/2022
Multiple denial of service vulnerabilities exist in the image output closing functionality of OpenImageIO Project OpenImageIO v2.4.4.2. Specially crafted ImageOutput Objects can lead to multiple null pointer dereferences. An attacker can provide malicious multiple inputs to trigger these vulnerabilities.This vulnerability applies to writing .fits files.
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Analysis
by VulDB Data Team • 08/31/2025
The vulnerability identified as CVE-2022-43595 represents a critical denial of service weakness within the OpenImageIO project's image output closing functionality. This flaw affects version 2.4.4.2 of the OpenImageIO library, which is widely used for image processing and manipulation across various applications and systems. The vulnerability specifically targets the handling of .fits file writing operations, which are commonly used in scientific imaging and astronomical data processing. The affected library is responsible for managing image output operations, including the proper closure of image streams and resources when writing files to disk. When processing specially crafted ImageOutput Objects, the library fails to properly validate input parameters before attempting to close image output streams, leading to multiple null pointer dereferences that cause the application to crash or become unresponsive.
The technical implementation of this vulnerability stems from inadequate input validation within the image output closing mechanism. When the library attempts to process malformed or malicious .fits file structures, it fails to properly check for null pointers before dereferencing object references during the cleanup phase of image output operations. This flaw manifests as multiple null pointer dereferences occurring during the image output closing sequence, where the system attempts to access memory locations that have not been properly initialized or allocated. The vulnerability is particularly concerning because it can be triggered through multiple input vectors, allowing attackers to craft various malicious ImageOutput Objects that will all lead to the same crash condition. The flaw is classified under CWE-476 as a null pointer dereference, which represents a fundamental programming error that can lead to system instability and denial of service conditions.
The operational impact of CVE-2022-43595 extends beyond simple application crashes, as it can be leveraged to create persistent denial of service conditions in systems that rely on OpenImageIO for image processing. Attackers can exploit this vulnerability by providing malicious .fits files or crafted ImageOutput Objects to applications that utilize OpenImageIO for image handling, potentially causing service disruptions in environments such as scientific computing clusters, astronomical data processing systems, or any application that handles .fits file formats. The vulnerability is particularly dangerous in automated processing pipelines where multiple files are processed sequentially, as a single malicious input can cause the entire processing chain to fail. Systems that depend on consistent image processing workflows may experience complete service outages, requiring manual intervention to restore normal operations and potentially leading to data loss or processing delays in time-sensitive applications.
Mitigation strategies for CVE-2022-43595 should focus on immediate patching of the OpenImageIO library to version 2.4.4.3 or later, which contains the necessary fixes for the null pointer dereference conditions. Organizations should implement input validation measures at the application level to filter or reject suspicious .fits file structures before they reach the OpenImageIO library components. Network-level protections can include implementing file type validation and content scanning to prevent malicious inputs from reaching vulnerable systems. Additionally, system administrators should consider implementing monitoring and alerting mechanisms to detect unusual application behavior or crash patterns that may indicate exploitation attempts. The vulnerability aligns with ATT&CK technique T1499.004 for network denial of service and represents a classic example of how improper error handling in image processing libraries can create security risks. Regular security assessments and vulnerability scanning should be conducted to identify other potential weaknesses in image processing stacks that may be similarly affected by input validation flaws. Organizations should also consider implementing sandboxing or containerization techniques to limit the impact of potential exploitation attempts and maintain operational continuity even when individual applications are compromised.