CVE-2022-23560: TensorFlow GPU - Limited Reads and Writes Outside of Arrays in TFLite
Summary
CVE-2022-23560: Tensorflow is an Open Source Machine Learning Framework. Affects tensorflow-gpu across 3 version ranges.
< 2.5.3
>= 2.6.0, < 2.6.3
< 6364463d6f5b6254cac3d6aedf999b6a96225038
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-2022-23560 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 set of tools and libraries for building and training neural networks. TensorFlow GPU is a variant of TensorFlow that leverages GPU acceleration for faster computation. It is commonly used in scenarios where large-scale parallel processing is required for training deep learning models. However, TensorFlow GPU is vulnerable to a security issue that allows limited reads and writes outside of arrays in TFLite models.
Vulnerability Detail
The vulnerability arises due to missing validation in the conversion from sparse tensors to dense tensors in TFLite. An attacker can exploit this flaw by crafting a malicious TFLite model. When this model is executed, it can perform unauthorized reads and writes outside of the intended arrays, potentially leading to information disclosure or arbitrary code execution. This vulnerability affects versions of TensorFlow GPU up to 2.5.3, 2.6.3, and 2.7.1. However, the issue has been addressed in TensorFlow 2.8.0.
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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Conclusion
The vulnerability in TensorFlow GPU allows limited reads and writes outside of arrays in TFLite, potentially leading to security breaches. Users are strongly advised to upgrade to TensorFlow GPU 2.8.0 or apply the provided fix on affected versions. For further support on vulnerability remediation, contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow GPU is a variant of TensorFlow that utilizes GPU acceleration for faster computation in machine learning tasks.
TFLite is a TensorFlow library for deploying machine learning models on mobile and embedded devices.
The vulnerability allows limited reads and writes outside of arrays in TFLite, potentially leading to information disclosure or arbitrary code execution.
Versions up to 2.5.3, 2.6.3, and 2.7.1 of TensorFlow GPU are affected.
Upgrading to TensorFlow GPU 2.8.0 or applying the fix commit on affected versions (2.5.3, 2.6.3, and 2.7.1) will mitigate the vulnerability.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
