CVE-2017-7599 in LibTIFF
Summary
by MITRE
LibTIFF 4.0.7 has an "outside the range of representable values of type short" undefined behavior issue, which might allow remote attackers to cause a denial of service (application crash) or possibly have unspecified other impact via a crafted image.
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Analysis
by VulDB Data Team • 11/28/2022
The vulnerability identified as CVE-2017-7599 resides within LibTIFF version 4.0.7, a widely used library for handling tag image file format image files. This issue manifests as undefined behavior when processing specially crafted image files that contain values outside the representable range of the short data type. The flaw occurs during the parsing and interpretation of image metadata, specifically when the library encounters image parameters that exceed the maximum or minimum values storable in a signed 16-bit integer. The undefined behavior arises from the library's failure to properly validate input data ranges before performing arithmetic operations or memory allocations based on these values, creating a scenario where the application's execution becomes unpredictable and potentially unstable.
The technical exploitation of this vulnerability involves crafting malicious TIFF image files with malformed metadata fields that contain numeric values exceeding the short data type's limits of -32,768 to 32,767. When the vulnerable LibTIFF library attempts to process these images, the undefined behavior can manifest as memory corruption, stack overflow conditions, or invalid memory access patterns. The vulnerability's impact extends beyond simple denial of service since the undefined behavior could potentially be leveraged for more sophisticated attacks, though the exact attack vectors remain unspecified in the original CVE description. The flaw represents a classic case of insufficient input validation and improper error handling in low-level image processing libraries.
From an operational standpoint, this vulnerability poses significant risks to systems that process untrusted image files, including web applications, image processing services, content management systems, and digital asset management platforms. The remote attack vector means that adversaries can exploit this vulnerability without requiring local access to the target system, making it particularly dangerous in internet-facing applications. The potential for application crashes creates a reliable denial of service condition that can be exploited to disrupt services continuously. The unspecified other impacts suggest that under certain conditions, this undefined behavior might be exploitable for more serious consequences such as arbitrary code execution, although this remains theoretical without additional exploitation details.
Security mitigations for CVE-2017-7599 should prioritize immediate patching of affected LibTIFF versions to the latest stable releases that contain proper input validation and bounds checking. Organizations should implement strict image file validation processes that include automated scanning for malformed TIFF files before processing, along with sandboxing mechanisms that isolate image processing operations. Network segmentation and access controls should limit exposure to vulnerable services, while monitoring systems should be configured to detect unusual application behavior or crash patterns that might indicate exploitation attempts. The vulnerability aligns with CWE-129, which addresses insufficient validation of length of input buffers, and relates to ATT&CK technique T1059.007 for application layer execution, though the specific attack paths require further analysis to fully understand the exploitation potential. Regular security assessments of image processing pipelines and dependency updates form essential components of a comprehensive defense strategy against this class of vulnerabilities.