CVE-2017-14450 in SDL2_image
Summary
by MITRE
A buffer overflow vulnerability exists in the GIF image parsing functionality of SDL2_image-2.0.2. A specially crafted GIF image can lead to a buffer overflow on a global section. An attacker can display an image to trigger this vulnerability.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Analysis
by VulDB Data Team • 03/07/2023
The vulnerability identified as CVE-2017-14450 represents a critical buffer overflow flaw within the SDL2_image library version 2.0.2, specifically affecting the GIF image parsing component. This vulnerability falls under the CWE-121 category of stack-based buffer overflow, though in this case it manifests in a global section, making it particularly concerning for memory corruption attacks. The flaw resides in how the library processes GIF image files, particularly when handling certain metadata or image data structures that exceed predetermined buffer boundaries.
The technical implementation of this vulnerability stems from inadequate input validation and bounds checking within the GIF parsing routine. When SDL2_image encounters a malformed GIF file, the parsing function fails to properly verify the size of incoming data segments before copying them into fixed-size buffers. This oversight allows an attacker to craft a specially designed GIF image that contains oversized data fields, causing the program to write beyond allocated memory boundaries into adjacent global variables or memory sections. The global nature of the affected buffer means that the overflow can potentially corrupt critical program state information, leading to arbitrary code execution or application crashes.
The operational impact of this vulnerability extends beyond simple denial of service scenarios, as it creates a potential attack vector for remote code execution. An attacker can deliver a malicious GIF image through various means including web browsers, email attachments, or file sharing platforms, requiring only that the target system attempts to display the image using an application linked against the vulnerable SDL2_image library. This makes the vulnerability particularly dangerous in environments where users frequently interact with untrusted image content, such as web browsers, media players, or any application that processes GIF files. The vulnerability affects any software that utilizes SDL2_image for image processing, including numerous games, multimedia applications, and system utilities.
Mitigation strategies for CVE-2017-14450 should focus on immediate library updates to version 2.0.3 or later, where the buffer overflow has been addressed through proper bounds checking and input validation. System administrators should prioritize patching all affected applications and ensure that the SDL2_image library is updated across all systems where it is deployed. Additionally, implementing input sanitization measures at network boundaries, such as web application firewalls or content filtering systems, can provide an additional layer of protection against malicious GIF files. The vulnerability demonstrates the importance of proper memory management practices and highlights the need for thorough input validation in multimedia processing libraries. From an ATT&CK perspective, this vulnerability maps to T1059 for execution through image processing components and T1203 for exploitation of memory corruption vulnerabilities, making it a significant concern for threat actors seeking to leverage multimedia processing flaws for system compromise. Organizations should also consider implementing runtime protections such as stack canaries or address space layout randomization to mitigate potential exploitation attempts, though the most effective defense remains the application of the vendor-provided security patches.