CVE-2022-23561: Out-of-bounds Write Vulnerability in TensorFlow-GPU
Summary
CVE-2022-23561: Tensorflow is an Open Source Machine Learning Framework. Affects tensorflow-gpu across 3 version ranges.
< 2.5.3
>= 2.6.0, < 2.6.3
< 6c0b2b70eeee588591680f5b7d5d38175fd7cdf6
Fixed in 2.5.3 or 2.6.3, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow-cpu · PyPI
The same CVE-2022-23561 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 widely used for developing and deploying machine learning models. It provides a comprehensive ecosystem of tools, libraries, and resources for building and training various types of neural networks. TensorFlow-GPU is a variant of TensorFlow that leverages the power of GPUs for accelerated computation. It enables faster training and inference of machine learning models on systems equipped with compatible GPUs.
Vulnerability Detail
A vulnerability has been identified in TensorFlow-GPU that allows an attacker to craft a TFLite model capable of triggering a write outside the bounds of an array in TFLite. This can lead to memory corruption and potentially enable the attacker to overwrite the linked list used by the memory allocator. Exploiting this vulnerability under certain conditions can result in an arbitrary write primitive. The impact of this vulnerability can be severe, potentially leading to remote code execution or denial of service attacks.
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 versions below are the minimum fixed release for this vulnerability.
If you can't move to the latest
The minimum fixed version depends on the release line you run.
-
< 2.5.32.5.3pip install --upgrade "tensorflow-gpu==2.5.3" -
>= 2.6.0, < 2.6.32.6.3pip install --upgrade "tensorflow-gpu==2.6.3"
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Workaround
There is no known workaround available for this vulnerability. It is essential to update to the fixed versions of TensorFlow-GPU to ensure the security of your machine learning applications.
Conclusion
The identified vulnerability in TensorFlow-GPU can allow an attacker to trigger an out-of-bounds write, potentially leading to memory corruption and arbitrary code execution. It is crucial to update to the fixed versions of TensorFlow-GPU (2.8.0, 2.7.1, 2.6.3, or 2.5.3) to mitigate this vulnerability. For further assistance or support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow-GPU is a variant of TensorFlow that utilizes GPUs for accelerated computation, enabling faster training and inference of machine learning models.
TFLite is a TensorFlow library for deploying machine learning models on resource-constrained devices, such as mobile and IoT devices.
An out-of-bounds write vulnerability occurs when a program writes data beyond the boundaries of a buffer or array, potentially overwriting adjacent memory and leading to memory corruption or arbitrary code execution.
Exploiting this vulnerability can result in memory corruption, potentially leading to remote code execution or denial of service attacks.
You can update TensorFlow-GPU to the fixed version by using the package manager or manually downloading and installing the fixed version from the official TensorFlow repository.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
