CVE-2016-3186 in LibTIFF
Summary
by MITRE
Buffer overflow in the readextension function in gif2tiff.c in LibTIFF 4.0.6 allows remote attackers to cause a denial of service (application crash) via a crafted GIF file.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Analysis
by VulDB Data Team • 07/12/2022
The vulnerability identified as CVE-2016-3186 represents a critical buffer overflow flaw within the LibTIFF library version 4.0.6, specifically within the gif2tiff.c module's readextension function. This issue arises when processing specially crafted GIF files that contain malformed extension blocks, creating a scenario where memory boundaries are exceeded during the parsing process. The buffer overflow occurs due to insufficient input validation and bounds checking in the extension handling code, allowing attackers to manipulate memory allocation and execution flow through carefully constructed malicious input data. The vulnerability is particularly concerning as it exists in a widely used library that processes image formats across numerous applications and systems, making it a prime target for exploitation.
The technical implementation of this flaw stems from improper handling of extension block data within the GIF file format processing pipeline. When the readextension function encounters a malformed extension block, it fails to properly validate the length and content of the extension data before attempting to copy it into fixed-size buffers. This lack of input sanitization creates a predictable overflow condition that can be exploited remotely, as the malicious GIF file can be delivered through any network-based interface that processes TIFF images. The vulnerability manifests as a stack-based buffer overflow, where the attacker-controlled data overflows into adjacent memory regions, potentially corrupting program execution and leading to application termination.
From an operational perspective, this vulnerability creates significant risk for systems that process untrusted image data, particularly those utilizing LibTIFF for image conversion and manipulation tasks. The denial of service impact means that legitimate applications relying on the library can be rendered non-functional through simple malicious file delivery, affecting availability of services and potentially creating opportunities for more sophisticated attacks. The remote exploitation capability amplifies the threat, as attackers can trigger the vulnerability without requiring physical access or local privileges. This makes the vulnerability particularly dangerous in web applications, email processing systems, and content management platforms that automatically process uploaded image files, as the attack surface is extensive and automated exploitation is feasible.
The vulnerability aligns with CWE-121, which describes stack-based buffer overflow conditions, and demonstrates characteristics consistent with ATT&CK technique T1203, which involves exploiting software vulnerabilities for denial of service. Organizations utilizing LibTIFF 4.0.6 should prioritize immediate patching or implementation of input validation measures to prevent exploitation. Mitigation strategies include updating to LibTIFF version 4.0.7 or later, implementing strict input validation for GIF file processing, and deploying network-based intrusion detection systems that can identify and block malicious GIF file patterns. Additionally, application-level sandboxing and restricted processing environments can help contain potential impacts if exploitation occurs, while regular security assessments should verify that no other similar vulnerabilities exist within the image processing pipeline.
The broader implications of this vulnerability highlight the critical importance of proper input validation in image processing libraries, as these components often handle untrusted data from multiple sources. The flaw demonstrates how seemingly benign file format parsing can become a critical security concern when proper bounds checking and memory management practices are not implemented. Organizations should implement comprehensive security testing procedures for all image processing components, including fuzzing and static analysis, to identify similar vulnerabilities in their software stacks. The incident underscores the need for robust memory safety practices and the importance of maintaining up-to-date security patches across all system components to prevent exploitation of known vulnerabilities.