CVE-2016-10094 in LibTIFF
Summary
by MITRE
Off-by-one error in the t2p_readwrite_pdf_image_tile function in tools/tiff2pdf.c in LibTIFF 4.0.7 allows remote attackers to have unspecified impact via a crafted image.
If you want to get best quality of vulnerability data, you may have to visit VulDB.
Analysis
by VulDB Data Team • 09/02/2020
The vulnerability identified as CVE-2016-10094 represents a critical off-by-one error within the LibTIFF library's tiff2pdf conversion utility. This flaw exists in the t2p_readwrite_pdf_image_tile function located in tools/tiff2pdf.c within LibTIFF version 4.0.7. The issue stems from improper boundary checking during the processing of TIFF image data when converting to PDF format, creating a condition where memory access occurs beyond allocated buffer boundaries. Such errors typically arise from insufficient validation of input parameters and can lead to unpredictable behavior including memory corruption, application crashes, or potential code execution.
The technical nature of this vulnerability places it squarely within the CWE-129 category of Improper Input Validation, specifically manifesting as an out-of-bounds read condition. When a remote attacker crafts a malicious TIFF image file with carefully constructed parameters, the vulnerable function processes the image data without adequate boundary checks, allowing the program to access memory locations beyond the intended buffer limits. This type of vulnerability can be exploited through various attack vectors including web applications that process user-uploaded images or automated systems that convert image files to PDF format. The unspecified impact mentioned in the CVE description suggests that depending on the execution context and memory layout, this flaw could potentially enable arbitrary code execution, information disclosure, or denial of service conditions.
From an operational perspective, this vulnerability poses significant risks to systems that utilize LibTIFF for image processing workflows, particularly those handling untrusted input from external sources. The attack surface extends across various applications including document management systems, web servers processing image uploads, content management platforms, and any software that relies on LibTIFF for TIFF to PDF conversion. Organizations using vulnerable versions of LibTIFF may experience system instability, unauthorized access to sensitive information, or complete system compromise if attackers successfully exploit this flaw. The remote nature of the attack means that exploitation does not require local system access, making it particularly dangerous for web-facing applications and services that process user-submitted content.
Mitigation strategies for CVE-2016-10094 should prioritize immediate patching of affected LibTIFF installations to version 4.0.8 or later, which contains the necessary fixes for the off-by-one error. Organizations should also implement defensive measures including input validation and sanitization for all image files processed through LibTIFF utilities, particularly those received from untrusted sources. Network segmentation and access controls can help limit the potential impact of successful exploitation attempts. Additionally, monitoring systems should be configured to detect unusual behavior patterns that might indicate exploitation attempts, including unexpected application crashes or memory access violations. Regular vulnerability assessments and security audits should be conducted to identify and remediate similar issues in other components of the software stack that may be vulnerable to similar memory corruption flaws. The ATT&CK framework categorizes this type of vulnerability under T1203 - Exploitation for Client Execution when it results in code execution, and T1059 - Command and Scripting Interpreter when used in conjunction with other exploitation techniques.