CVE-2016-10266 in LibTIFF
Summary
by MITRE
LibTIFF 4.0.7 allows remote attackers to cause a denial of service (divide-by-zero error and application crash) via a crafted TIFF image, related to libtiff/tif_read.c:351:22.
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Analysis
by VulDB Data Team • 11/15/2022
The vulnerability identified as CVE-2016-10266 represents a critical denial of service flaw within the LibTIFF library version 4.0.7. This issue arises from improper input validation when processing specially crafted TIFF image files, specifically affecting the tif_read.c source file at line 351. The flaw manifests as a divide-by-zero error that occurs during the image parsing process, leading to application crashes and complete service unavailability. The vulnerability is particularly dangerous because it can be exploited remotely through maliciously constructed TIFF files, making it a significant concern for systems that process untrusted image data.
The technical implementation of this vulnerability stems from a lack of proper boundary checking and input sanitization within the TIFF reading functionality. When the LibTIFF library attempts to parse a malformed TIFF image, it encounters a division operation where the denominator becomes zero due to corrupted or maliciously crafted image headers. This specific location in libtiff/tif_read.c:351:22 represents a critical code path where the library fails to validate the integrity of image metadata before performing mathematical operations. The flaw falls under the CWE-369 weakness category, which specifically addresses the division by zero error condition that can lead to system instability and application termination. This vulnerability directly maps to the ATT&CK technique T1499.004, which involves network denial of service attacks through the exploitation of application flaws.
The operational impact of CVE-2016-10266 extends beyond simple service disruption, as it can be leveraged by attackers to perform systematic denial of service attacks against applications that rely on LibTIFF for image processing. Systems commonly affected include web applications, content management systems, image processing servers, and any software that accepts TIFF file uploads or streaming. The vulnerability is particularly concerning for online services that process user-uploaded images, as attackers can craft malicious TIFF files to crash the application and render it unavailable to legitimate users. This type of attack can be amplified through automated tools that generate multiple malicious files to overwhelm systems, making it a potent vector for distributed denial of service scenarios. The flaw's remote exploitability means that no local access is required, making it accessible to attackers from anywhere on the network.
Mitigation strategies for CVE-2016-10266 primarily involve immediate patching of the LibTIFF library to version 4.0.8 or later, which contains the necessary fixes for the divide-by-zero condition. Organizations should implement comprehensive input validation measures that sanitize all image files before processing, including verifying file headers and metadata integrity. Network-level defenses such as content filtering and intrusion prevention systems can help detect and block malicious TIFF files before they reach vulnerable applications. Additionally, implementing proper error handling and application sandboxing techniques can limit the impact of successful exploits by preventing complete application crashes. Security teams should also consider deploying automated monitoring solutions that can detect unusual application behavior indicative of denial of service attacks. The vulnerability highlights the importance of maintaining up-to-date third-party libraries and implementing robust security testing procedures that include fuzzing and input validation checks to identify similar issues before they can be exploited in production environments.