CVE-2026-18495 in libtiff
Summary
by MITRE • 09/11/2026
A flaw was found in libtiff. A heap-buffer overflow vulnerability exists in the `tiff2pdf` utility due to an integer truncation error when processing crafted BigTIFF files. An attacker can provide a specially crafted BigTIFF file, causing a 64-bit `StripByteCounts` value to be truncated to a 32-bit integer. This leads to an undersized memory allocation and a subsequent out-of-bounds memory copy, resulting in a crash and severe memory corruption.
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Analysis
by VulDB Data Team • 09/11/2026
The vulnerability identified within the libtiff library specifically impacts the tiff2pdf utility through a critical heap-buffer overflow condition triggered by malformed input data. This flaw stems from an integer truncation error that occurs during the processing of crafted BigTIFF files, which are designed to exploit weaknesses in how large file structures are interpreted by the software. When the application encounters these specially constructed files, it fails to properly validate or handle the full range of values associated with image strip data, leading directly to memory safety violations that compromise system integrity and stability.
At a technical level, the root cause lies in the handling of the StripByteCounts field within BigTIFF structures. In standard TIFF formats, this value typically fits within 32-bit boundaries, but BigTIFF files support larger values using 64-bit integers to accommodate high-resolution or large-scale images. The vulnerability arises when a crafted file provides a StripByteCounts value that exceeds the maximum limit of a 32-bit signed integer yet is processed in a context where it gets truncated down to fit into a 32-bit variable. This truncation results in a significantly smaller number than intended, causing the application to allocate an undersized buffer on the heap for storing image data.
Once the insufficient memory allocation occurs, subsequent operations attempt to copy the full amount of image data specified by the original untruncated value into this small buffer. Because the allocated space is far too small to hold the incoming data stream, a classic out-of-bounds write operation takes place on the heap. This action overwrites adjacent memory regions that may contain critical application state information or other security-sensitive structures. The immediate operational impact of such an overflow includes severe memory corruption and application crashes, which can manifest as denial of service conditions for users relying on automated processing pipelines involving this utility.
From a threat modeling perspective, while the primary observed effect is stability-related through crashing, heap buffer overflows are frequently precursors to more severe security breaches if specific exploitation techniques are applied under controlled circumstances. An attacker with the ability to inject or manipulate input files could potentially leverage memory corruption patterns to execute arbitrary code, although successful exploitation depends heavily on compiler protections and runtime mitigations present in the target environment. This vulnerability aligns closely with CWE-190, which describes integer overflow or wraparound issues that lead to subsequent buffer overflows, as well as CWE-787, which covers out-of-bounds write vulnerabilities resulting from improper boundary checks following arithmetic errors.
In terms of detection and classification within threat intelligence frameworks, this type of vulnerability is often associated with techniques involving invalid memory access during file parsing operations. It falls under the broader category of input validation failures where external data sources are not adequately sanitized or range-checked before being used to determine resource allocation sizes. Security analysts should monitor for anomalies in log files indicating segmentation faults or core dumps within systems running affected versions of libtiff, particularly those utilizing tiff2pdf for batch processing workflows involving untrusted image inputs.
To mitigate this risk, organizations must ensure that all instances of the libtiff library are updated to a patched version where developers have implemented proper 64-bit integer handling and bounds checking before memory allocation calls. Input validation mechanisms should be strengthened at the parsing layer to reject or safely handle values that exceed expected limits for specific data types without causing truncation errors. Additionally, deploying runtime application self-protection tools such as Address Sanitizer during development phases can help identify similar logical flaws in other parts of the codebase before they reach production environments. Regular security audits focusing on image processing libraries are recommended to maintain resilience against evolving file format exploitation techniques.