CVE-2023-25667: TensorFlow GPU Integer Overflow Vulnerability Leading to Segfault
Summary
CVE-2023-25667: TensorFlow vulnerable to segfault when opening multiframe gif. Affects tensorflow-gpu versions < 2.11.1. Fixed in 2.11.1. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow · Bitnami
- tensorflow · PyPI
The same CVE-2023-25667 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
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Background
TensorFlow is an open-source machine learning framework that provides a comprehensive ecosystem for building and deploying machine learning models. It is widely used for tasks such as image recognition, natural language processing, and more. The TensorFlow GPU package enhances performance by utilizing GPU resources for computations. However, it has been found to be vulnerable to an integer overflow issue when processing multiframe GIF images, which can lead to a segmentation fault, potentially crashing applications that rely on this functionality.
Vulnerability Detail
The vulnerability arises from an integer overflow that occurs when the product of the number of frames, height, width, and channels of a GIF image exceeds the maximum value for a 32-bit integer. Specifically, this can happen when the calculation results in a value between 2^31 and 2^32. For instance, a Full HD screencast with at least 346 frames can trigger this overflow, leading to a segmentation fault when the function tf.io.decode_gif is called. This can result in application crashes and potential denial of service.
How To Fix
Latest published version: 2.12.0 as of 22 Oct 2026
pip install --upgrade "tensorflow-gpu==2.12.0"Upgrading to it may include breaking changes; the version below is the minimum fixed release for this vulnerability.
If you need the minimum change
2.11.1
This is the first release that contains the fix.
pip install --upgrade "tensorflow-gpu==2.11.1"Tip — Not sure which version your app runs? Vulert can match this fix to it. Scan free →
Workaround
As a temporary workaround, avoid processing multiframe GIF images that may exceed the specified dimensions and frame count until the package is updated. Additionally, users can implement input validation to check the dimensions and frame count of GIF images before processing them.
Conclusion
The CVE-2023-25667 vulnerability in TensorFlow GPU poses a significant risk by allowing integer overflow during GIF processing, leading to application crashes. Users are advised to update to version 2.11.1 or later to mitigate this risk. Implementing input validation can also help prevent potential issues until the update is applied.
See every vulnerability recorded for tensorflow-gpu →
FAQ
CVE-2023-25667 is a vulnerability in TensorFlow GPU that allows for an integer overflow when processing multiframe GIF images, leading to potential application crashes.
You can use the Vulert playground at Vulert Scanner to check if your application is affected by this vulnerability without needing to sign up.
The primary consequence is a segmentation fault that can crash applications using TensorFlow GPU to decode problematic GIF images, potentially leading to denial of service.
You can update TensorFlow GPU by running the command: pip install --upgrade tensorflow-gpu==2.11.1 in your terminal or command prompt.
Yes, you can implement input validation to check the dimensions and frame count of GIF images before processing them, and avoid using multiframe GIFs that may exceed safe limits.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
