CVE-2019-16347 in ngiflib
Summary
by MITRE
ngiflib 0.4 has a heap-based buffer overflow in WritePixels() in ngiflib.c when called from DecodeGifImg, because deinterlacing for small pictures is mishandled.
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Analysis
by VulDB Data Team • 06/07/2024
The vulnerability identified as CVE-2019-16347 represents a critical heap-based buffer overflow within the ngiflib library version 0.4, specifically manifesting in the WritePixels() function located in ngiflib.c. This flaw occurs when the library processes GIF images through the DecodeGifImg function, creating a significant security risk that can be exploited by malicious actors. The vulnerability stems from improper handling of deinterlacing operations for small picture dimensions, where the library fails to properly validate or allocate memory boundaries during image processing operations. The heap-based nature of this overflow indicates that attackers can manipulate memory allocation patterns to overwrite adjacent heap regions, potentially leading to arbitrary code execution or system instability.
The technical implementation of this vulnerability involves the ngiflib library's approach to handling GIF image deinterlacing, particularly when dealing with images that have small dimensions. During the DecodeGifImg process, the library attempts to reconstruct interlaced GIF images by processing multiple passes of pixel data. When the image dimensions are small, the deinterlacing algorithm fails to correctly calculate the required buffer sizes, leading to an overflow condition where more data is written to a heap-allocated buffer than its allocated capacity permits. This memory corruption can be triggered through specially crafted GIF files that exploit the specific edge case involving small image dimensions and interlacing patterns. The vulnerability specifically affects the WritePixels() function which serves as the core pixel processing routine, making it a primary target for exploitation.
The operational impact of CVE-2019-16347 extends beyond simple memory corruption, potentially enabling attackers to achieve arbitrary code execution on systems processing vulnerable GIF images. This vulnerability can be exploited in various contexts including web applications, image processing software, and any system that utilizes ngiflib for GIF file handling. The exploitability of this vulnerability increases when the affected library is used in server applications or services that process user-uploaded GIF files, as attackers can craft malicious GIF files to trigger the buffer overflow. The heap corruption can lead to denial of service conditions, data corruption, or more severe consequences including privilege escalation depending on the execution environment. This vulnerability particularly affects systems where ngiflib is integrated into larger applications such as web browsers, image viewers, or content management systems that handle GIF format processing.
Mitigation strategies for CVE-2019-16347 should prioritize updating to a patched version of ngiflib where the buffer overflow has been addressed through proper input validation and memory allocation checks. System administrators should immediately assess their environments to identify all applications utilizing ngiflib version 0.4 or earlier, particularly focusing on web applications, image processing tools, and any software that handles GIF file formats. The implementation of input sanitization measures including GIF file validation and size checking can provide additional protection layers. Security professionals should also consider implementing network-based intrusion detection systems to monitor for suspicious GIF file processing patterns that may indicate exploitation attempts. Additionally, the vulnerability aligns with CWE-121, heap-based buffer overflow, and can be mapped to ATT&CK technique T1059.007 for execution through malformed image files, making it a significant concern for organizations implementing comprehensive cybersecurity frameworks. Organizations should also implement proper memory safety practices and conduct regular vulnerability assessments to identify similar issues in other image processing libraries and components.