CVE-2016-3945 in LibTIFF
Summary
by MITRE
Multiple integer overflows in the (1) cvt_by_strip and (2) cvt_by_tile functions in the tiff2rgba tool in LibTIFF 4.0.6 and earlier, when -b mode is enabled, allow remote attackers to cause a denial of service (crash) or execute arbitrary code via a crafted TIFF image, which triggers an out-of-bounds write.
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Analysis
by VulDB Data Team • 09/19/2022
The vulnerability identified as CVE-2016-3945 represents a critical security flaw within the LibTIFF library version 4.0.6 and earlier, specifically affecting the tiff2rgba tool's handling of TIFF image files. This issue manifests through integer overflow conditions that occur within two distinct functions: cvt_by_strip and cvt_by_tile, when the tool operates in -b mode. The flaw stems from inadequate input validation and arithmetic overflow handling during the processing of malformed TIFF image data, creating a pathway for malicious actors to exploit the system through carefully crafted image files that can trigger unexpected behavior in the library's memory management routines.
The technical implementation of this vulnerability involves integer overflow conditions that lead to memory corruption during the conversion process of TIFF images to RGBA format. When the tiff2rgba tool processes images with the -b mode enabled, it performs calculations that determine buffer sizes and memory allocation for image data processing. These calculations fail to properly validate input values, allowing attackers to provide crafted TIFF files containing maliciously sized parameters that cause integer overflow during arithmetic operations. The resulting overflow produces incorrect buffer dimensions that subsequently lead to out-of-bounds write operations when the tool attempts to store processed image data, creating a scenario where memory corruption occurs at unpredictable locations within the application's memory space.
The operational impact of CVE-2016-3945 extends beyond simple denial of service conditions to encompass potential remote code execution capabilities, making it particularly dangerous for systems that process untrusted TIFF image data. Attackers can leverage this vulnerability to cause application crashes through controlled denial of service attacks or to execute arbitrary code on systems running vulnerable versions of LibTIFF, potentially leading to complete system compromise. The vulnerability affects any system that utilizes LibTIFF 4.0.6 or earlier versions for TIFF image processing, including web applications, image processing servers, and desktop applications that handle TIFF format files. The exploitability of this flaw is enhanced by the fact that TIFF files are commonly used in various digital media workflows, making the attack surface broad and accessible to adversaries who can simply deliver a malicious TIFF file to trigger the vulnerability.
From a cybersecurity perspective, this vulnerability aligns with CWE-190, which specifically addresses integer overflow conditions, and demonstrates characteristics consistent with ATT&CK technique T1203, involving the exploitation of software vulnerabilities for privilege escalation and system compromise. The vulnerability's classification as a heap-based buffer overflow through integer overflows makes it particularly susceptible to exploitation using modern attack techniques such as return-oriented programming and stack pivot operations that can be employed to achieve remote code execution. Organizations utilizing affected LibTIFF versions should prioritize immediate remediation through patch updates, as the vulnerability can be exploited remotely without requiring user interaction or elevated privileges, making it an attractive target for automated exploitation tools and malicious actors seeking to compromise systems through image processing workflows.
The remediation approach for CVE-2016-3945 requires immediate deployment of LibTIFF version 4.0.7 or later, which includes patches addressing the integer overflow conditions in the affected functions. System administrators should conduct comprehensive vulnerability assessments to identify all systems running vulnerable versions of LibTIFF and implement proper input validation measures for TIFF image processing workflows. Additionally, organizations should consider implementing network segmentation and access controls to limit exposure of systems that process external TIFF image data, while also establishing monitoring procedures to detect potential exploitation attempts through unusual memory access patterns or application crash events that may indicate successful exploitation of this vulnerability.