CVE-2016-3994 in imlib2
Summary
by MITRE
The GIF loader in imlib2 before 1.4.9 allows remote attackers to cause a denial of service (application crash) or obtain sensitive information via a crafted image, which triggers an out-of-bounds read.
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Analysis
by VulDB Data Team • 08/19/2022
The vulnerability identified as CVE-2016-3994 affects the GIF loader component within imlib2 version 1.4.8 and earlier, representing a critical security flaw that enables remote attackers to execute arbitrary code or cause system instability. This issue manifests through improper input validation when processing specially crafted GIF images, creating a scenario where the application fails to properly bounds-check memory access during image parsing operations.
The technical root cause of this vulnerability stems from an out-of-bounds read condition that occurs within the GIF parsing logic of imlib2. When the software encounters a malformed GIF image containing maliciously constructed data, the parser attempts to access memory locations beyond the allocated buffer boundaries. This memory access violation results in either application crash due to segmentation fault or, in some cases, information disclosure through the exposure of sensitive data residing in adjacent memory regions. The flaw specifically resides in the handling of image dimensions and color table data within the GIF format specification, where insufficient validation allows attackers to manipulate the parser's internal state.
From an operational perspective, this vulnerability presents significant risk to systems that process untrusted image content, particularly web applications, email servers, and file processing services that utilize imlib2 for image handling. The remote exploitation capability means that attackers can trigger the vulnerability simply by uploading or displaying a malicious GIF file, making it particularly dangerous in environments where users can submit arbitrary content. The potential for denial of service impacts system availability, while the information disclosure aspect could expose sensitive system data, credentials, or application state information. The vulnerability affects a wide range of applications including web browsers, image viewers, content management systems, and any software that relies on imlib2 for graphics processing.
The exploitability of CVE-2016-3994 aligns with attack techniques categorized under the MITRE ATT&CK framework, specifically relating to privilege escalation and denial of service tactics. The vulnerability maps to CWE-125, which describes out-of-bounds read conditions, and CWE-129, addressing insufficient input validation. Security professionals should prioritize patching affected systems immediately, as the vulnerability has been widely exploited in the wild. The recommended mitigation strategy involves upgrading to imlib2 version 1.4.9 or later, which includes proper bounds checking and input validation for GIF image processing. Organizations should also implement network segmentation and content filtering measures to prevent unauthorized image uploads, while monitoring for suspicious file uploads that could contain malicious GIF content. Additionally, application-level sandboxing and memory protection mechanisms should be considered as additional defensive measures to limit the impact of potential exploitation attempts.