CVE-2026-112393 in Pillow
Summary
by MITRE • 10/20/2026
Pillow is a Python imaging library. From 2.0.0 until 13.0.0, Pillow has a heap buffer overflow and stale-heap disclosure in _tiffWriteProc when saving compressed TIFF data through libtiff to a target without a usable fileno(), such as BytesIO. The callback sizes its allocation from the prior buffer size instead of the current write position, allowing an attacker-controlled out-of-line TIFF tag or retained ICC profile to be copied beyond the allocation after libtiff seeks forward. This overflow can crash the process and may allow code execution. Independently, unwritten alignment gaps in compressed TIFF output larger than 64 KiB can disclose stale heap bytes without a crafted tag. File paths and targets with real file descriptors are unaffected. This issue is fixed in version 13.0.0.
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Analysis
by VulDB Data Team • 10/20/2026
The vulnerability identified within the Pillow Python imaging library, spanning versions from 2.0.0 through 13.0.0, represents a critical memory safety failure rooted in improper buffer management during the serialization of Tagged Image File Format data. This flaw specifically manifests when saving compressed TIFF images to output targets that lack a usable file descriptor, such as Python BytesIO objects or network streams where direct OS-level file operations are not available. In these scenarios, Pillow relies on libtiff callbacks to handle the writing process, and it is within this specific code path, namely _tiffWriteProc, that the underlying logic error resides. The core technical deficiency involves a miscalculation of memory allocation sizes during write operations. Instead of sizing the internal buffer based on the current file position or the actual amount of data to be written at that moment, the implementation incorrectly derives the allocation size from the prior buffer state. This architectural oversight creates a discrepancy between the allocated heap space and the volume of data libtiff attempts to copy into it during seek-forward operations triggered by compressed TIFF tag processing.
This misalignment leads directly to two distinct but related security consequences: a heap-based buffer overflow and a stale-heap information disclosure. When an attacker controls specific elements of the input image, such as crafted out-of-line TIFF tags or retained International Color Consortium profiles that require significant data manipulation during compression, libtiff may seek forward in the output stream. Because Pillow has allocated insufficient memory based on outdated size metrics, the subsequent write operation copies data beyond the bounds of the heap allocation. This buffer overflow can result in immediate process termination due to segmentation faults or corruption of adjacent heap metadata, potentially leading to arbitrary code execution if an attacker can precisely control the overwritten memory regions and exploit standard heap exploitation techniques such as fastbin attacks or unlinking vulnerabilities. The severity is compounded by the fact that this occurs during a common image processing task, making it accessible to attackers who can submit maliciously crafted images for conversion or analysis.
Independently of the overflow condition, the vulnerability also facilitates information disclosure through stale-heap data leakage. Even in cases where an attacker does not craft specific tags to trigger the buffer overflow, uncompressed alignment gaps within compressed TIFF output files larger than sixty-four kilobytes can expose uninitialized memory contents from previous operations. This occurs because Pillow fails to properly zero out or manage these padding regions before writing them to the target stream. Consequently, sensitive data residing in those heap locations prior to the current image processing task may be written into the resulting file and subsequently exposed to any party with access to the output. This side-channel leakage can reveal cryptographic keys, session tokens, or other proprietary information previously held in memory by the application running Pillow. It is important to note that this specific vector of exploitation does not affect scenarios where images are saved directly to real file descriptors on disk, as those paths utilize different I/O mechanisms that do exhibit correct buffer sizing and zeroing behaviors.
From a classification perspective, this vulnerability aligns with CWE-120 Buffer Copy without Checking Size of Input in C/C++, which describes the fundamental error of copying data into a buffer without verifying that it fits within the allocated space. Additionally, the stale heap disclosure component maps to CWE-200 Exposure of Sensitive Information Through Leakage of Memory Contents, highlighting the risk of residual data exposure due to improper memory initialization or management. In terms of adversary tactics, this flaw supports techniques associated with ATT&CK T1564 Hidden Files and Directories if used for persistence via crafted files, but more critically it enables ATT&CK T1078 Valid Accounts through credential harvesting from leaked heap contents in multi-tenant environments. The exploitation chain typically involves the attacker providing a maliciously constructed TIFF image to an application that processes user-uploaded media, such as social platforms, e-commerce sites with product image uploads, or document management systems.
The operational impact of this vulnerability is severe for any service relying on Pillow for image processing in memory-constrained or high-throughput environments. A successful exploitation can lead to complete denial of service through process crashes, which disrupts availability and requires manual intervention or automated restart mechanisms that may themselves be vulnerable to race conditions. More critically, the potential for remote code execution poses a direct threat to system integrity, allowing attackers to gain control over the underlying server infrastructure hosting the image processing services. The information disclosure aspect further erodes confidentiality by potentially leaking sensitive application state data across user sessions if the memory allocator does not securely wipe freed chunks before reassignment. Mitigation strategies must prioritize immediate upgrading of the Pillow library to version 13.0.0 or later, where these allocation logic errors have been corrected to ensure buffer sizes are dynamically calculated based on current write positions and alignment gaps are properly zeroed out.
For organizations unable to immediately upgrade due to dependency constraints, defensive coding practices can offer limited protection. Implementing strict input validation that rejects TIFF files with unusually large tags or complex ICC profiles before they reach the compression stage may reduce the attack surface. Additionally, running image processing tasks in isolated containers or sandboxed environments with restricted memory access and low privileges can mitigate the impact of potential code execution attempts by limiting the attacker's ability to interact with critical system components. Monitoring for abnormal heap usage patterns or frequent process crashes related to TIFF handling can also serve as an early warning indicator for exploitation attempts. Ultimately, maintaining up-to-date dependencies remains the most effective defense against this class of memory corruption vulnerabilities inherent in legacy C-based image processing libraries like libtiff when wrapped by higher-level languages such as Python.