CVE-2022-43359 in Gifdec
Summary
by MITRE • 11/08/2022
Gifdec commit 1dcbae19363597314f6623010cc80abad4e47f7c was discovered to contain an out-of-bounds read in the function read_image_data. This vulnerability is triggered when parsing a crafted Gif file.
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Analysis
by VulDB Data Team • 12/05/2022
The vulnerability identified as CVE-2022-43359 resides within the gifdec library, specifically in the read_image_data function where an out-of-bounds read condition occurs during gif file parsing operations. This issue manifests when the library processes a maliciously crafted gif file that exploits improper input validation mechanisms. The gifdec library serves as a gif decoding component commonly integrated into various applications and systems that require gif image processing capabilities, making this vulnerability particularly concerning for widespread exploitation potential. The out-of-bounds read vulnerability represents a critical security flaw that can lead to memory corruption and potentially arbitrary code execution when exploited by malicious actors.
The technical flaw stems from insufficient bounds checking within the read_image_data function which fails to properly validate the dimensions and data structures contained within gif image files. When parsing gif files, the function attempts to read data beyond the allocated memory boundaries, particularly when encountering malformed or crafted gif files with manipulated image dimensions or data offsets. This condition allows attackers to manipulate the parsing process by creating gif files that contain invalid or oversized image data structures, causing the application to read memory locations that do not belong to the intended data set. The vulnerability is classified under CWE-129 as an Improper Validation of Array Index, which directly relates to the lack of proper bounds checking mechanisms in the implementation.
The operational impact of this vulnerability extends beyond simple denial of service conditions to potentially enable more severe exploitation vectors. Applications that utilize the gifdec library for gif file processing become susceptible to memory corruption attacks that could lead to arbitrary code execution, especially when these applications run with elevated privileges or process untrusted gif content from web applications, file uploads, or user-generated content. The vulnerability affects systems where gifdec is integrated as a dependency, including web browsers, image processing applications, multimedia frameworks, and any software that handles gif file parsing operations. The out-of-bounds read condition can result in application crashes, data corruption, or more dangerous scenarios where attackers might leverage the memory corruption to execute malicious code within the context of the affected application.
Mitigation strategies for CVE-2022-43359 should prioritize immediate patching of affected gifdec library versions to address the bounds checking deficiencies in the read_image_data function. Organizations should implement comprehensive input validation mechanisms when processing gif files, including strict validation of image dimensions, data structure integrity, and memory boundary checks. The implementation of defensive programming practices such as bounds checking, memory sanitization, and input sanitization should be enforced across all gif processing components. Additionally, deployment of web application firewalls and content filtering systems can help prevent malicious gif files from reaching vulnerable applications. System administrators should monitor for any signs of exploitation attempts and implement proper logging and alerting mechanisms to detect unusual gif file processing patterns. The vulnerability highlights the importance of maintaining up-to-date third-party libraries and implementing proper security testing procedures including fuzzing and static analysis to identify similar out-of-bounds read conditions in other components. This vulnerability aligns with ATT&CK technique T1203 - Exploitation for Client Execution, as it represents a classic memory corruption exploit that can be leveraged for arbitrary code execution within vulnerable applications.