CVE-2022-35002 in JPEGDEC
Summary
by MITRE • 08/17/2022
JPEGDEC commit be4843c was discovered to contain a segmentation fault via TIFFSHORT at /src/jpeg.inl.
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Analysis
by VulDB Data Team • 08/17/2022
The vulnerability identified as CVE-2022-35002 represents a critical segmentation fault within the JPEGDEC library component, specifically manifesting at the TIFFSHORT function within the /src/jpeg.inl source file. This issue arises from improper handling of certain input data structures that leads to memory access violations during image processing operations. The flaw exists in the commit be4843c of the JPEGDEC project, indicating a regression or new code addition that fails to properly validate input parameters before processing.
The technical implementation of this vulnerability stems from inadequate bounds checking and memory management within the image decoding pipeline. When the TIFFSHORT function processes specific malformed or edge-case input data, it attempts to access memory locations outside the allocated buffer boundaries, resulting in a segmentation fault that terminates the application process. This type of vulnerability falls under the CWE-125 vulnerability category, which describes out-of-bounds read conditions that can lead to memory corruption and potential exploitation. The flaw demonstrates characteristics consistent with memory safety issues that are commonly exploited in cyber attacks targeting multimedia processing libraries.
The operational impact of CVE-2022-35002 extends beyond simple application crashes, as it represents a potential denial-of-service vector that could be exploited by malicious actors to disrupt services. Systems relying on JPEGDEC for image processing, including web applications, mobile platforms, and embedded systems, may become vulnerable to controlled crashes that could be leveraged to exhaust system resources or disrupt service availability. This vulnerability aligns with ATT&CK technique T1499.004, which covers network denial of service attacks through resource exhaustion, and demonstrates how seemingly benign image processing functions can become attack vectors. The segmentation fault occurs during the decoding process, making it particularly dangerous in environments where automatic image processing is performed without proper input validation.
Mitigation strategies for this vulnerability should focus on immediate code-level fixes including comprehensive input validation, bounds checking, and memory boundary enforcement within the TIFFSHORT function. Developers should implement proper error handling mechanisms that gracefully manage malformed input data rather than allowing the application to crash. The fix should include bounds checking for all array accesses and proper initialization of memory structures before processing. Additionally, organizations should consider implementing sandboxing mechanisms around image processing components, applying input sanitization layers, and regularly updating to patched versions of the JPEGDEC library. Security monitoring should include detection of segmentation fault patterns in image processing services, and defensive coding practices should be enforced through code reviews and automated static analysis tools. The vulnerability also highlights the importance of maintaining up-to-date security patches and implementing proper software supply chain security measures to prevent exploitation of known vulnerabilities in third-party libraries.