CVE-2025-50129 in Image Decoding Library
Summary
by MITRE • 08/26/2025
A memory corruption vulnerability exists in the PCX Image Decoding functionality of the SAIL Image Decoding Library v0.9.8. When decoding the image data from a specially crafted .tga file, a heap-based buffer overflow can occur which allows for remote code execution. An attacker will need to convince the library to read a file to trigger this vulnerability.
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Analysis
by VulDB Data Team • 09/03/2025
The vulnerability identified as CVE-2025-50129 represents a critical memory corruption flaw within the SAIL Image Decoding Library version 0.9.8, specifically affecting the PCX image decoding component. This issue stems from insufficient input validation and boundary checking during the processing of specially crafted .tga image files, creating a pathway for attackers to exploit heap-based buffer overflow conditions. The vulnerability is particularly concerning because it enables remote code execution when the affected library processes maliciously formatted image data, making it a significant threat to systems that rely on this library for image processing operations.
The technical implementation of this vulnerability occurs during the image decoding process when the library fails to properly validate the size and structure of incoming image data. When processing a maliciously crafted .tga file, the decoding routine attempts to write data beyond the allocated memory boundaries, resulting in a heap-based buffer overflow condition. This memory corruption can be leveraged by attackers to overwrite critical memory regions, potentially allowing them to execute arbitrary code with the privileges of the process running the SAIL library. The flaw is classified as a heap-based buffer overflow under CWE-122, which falls under the broader category of memory safety vulnerabilities that have been extensively documented in the cybersecurity community. The vulnerability operates at the intersection of software security and image processing protocols, making it particularly dangerous in environments where image files are processed without proper sanitization.
The operational impact of this vulnerability extends across multiple attack vectors and system environments where the SAIL library is deployed. Attackers can exploit this weakness remotely by enticing victims to process maliciously crafted image files through applications that utilize the vulnerable library, such as image viewers, web browsers, or content management systems. The attack surface is broadened by the fact that many applications and services rely on standardized image processing libraries, meaning a single vulnerable component can compromise entire application ecosystems. This vulnerability directly maps to techniques described in the MITRE ATT&CK framework under the T1059.007 sub-technique for remote code execution through memory corruption attacks. The potential for unauthorized code execution makes this vulnerability particularly dangerous in server environments, desktop applications, and any system where user-supplied image data is processed without adequate input validation.
Mitigation strategies for CVE-2025-50129 must address both immediate remediation and long-term architectural improvements to prevent similar vulnerabilities from emerging in the future. The primary recommendation involves upgrading to a patched version of the SAIL Image Decoding Library where the buffer overflow conditions have been resolved through proper input validation and memory boundary checking. Organizations should also implement comprehensive input sanitization measures, including validating file formats, checking image dimensions, and implementing strict size limits for decoded image data. Network-level defenses such as web application firewalls and content filtering systems can provide additional protection by scanning image files for known malicious patterns before they reach applications that utilize the vulnerable library. Security teams should also consider implementing runtime protections such as address space layout randomization and stack canaries to make exploitation more difficult. The vulnerability highlights the importance of regular security assessments and dependency updates, particularly for widely-used libraries that handle untrusted input data. Organizations should conduct thorough vulnerability assessments to identify all systems using the affected library and implement comprehensive monitoring to detect potential exploitation attempts. This vulnerability serves as a reminder of the critical need for memory safety practices in image processing libraries and the importance of adhering to secure coding guidelines that prevent buffer overflow conditions.