CVE-2022-23589: TensorFlow GPU - Null Pointer Dereference in Grappler Component
Summary
CVE-2022-23589: Tensorflow is an Open Source Machine Learning Framework. Affects tensorflow-gpu across 4 version ranges.
< 0a365c029e437be0349c31f8d4c9926b69fa3fa1
< 2.5.3
>= 2.6.0, < 2.6.3
< 045deec1cbdebb27d817008ad5df94d96a08b1bf
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-2022-23589 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 for building and training neural networks. The TensorFlow GPU package, available on PyPI, is specifically designed to leverage the power of GPUs for accelerated computation. This vulnerability affects versions 0 to 2.5.3 of the TensorFlow GPU package.
Vulnerability Detail
The vulnerability arises in the Grappler component of TensorFlow. Under certain scenarios, a null pointer dereference can be triggered, leading to a crash or potential code execution. The issue occurs in two places within the codebase, both related to a malicious alteration of a SavedModel file. The first instance is during constant folding, where the GraphDef may lack the necessary nodes for a binary operation. This results in a null value for the corresponding mul_*child, leading to an incorrect dereference in subsequent lines. The second instance is during IsIdentityConsumingSwitch, where a similar issue can occur. The fix for this vulnerability will be included in TensorFlow 2.8.0, and patches will also be backported to TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3.
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 for this vulnerability. It is crucial to update to the patched versions as soon as they become available.
Conclusion
The null pointer dereference vulnerability in the Grappler component of TensorFlow GPU can lead to crashes or potential code execution. It is crucial for users to update their TensorFlow GPU package to the patched versions once they become available. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow is an open-source machine learning framework used for building and training neural networks.
Grappler is a TensorFlow subcomponent responsible for optimizing and transforming computational graphs.
A null pointer dereference occurs when a program attempts to access or manipulate memory using a null pointer, leading to a crash or potential code execution.
This vulnerability can be exploited by an attacker who can provide a maliciously crafted SavedModel file, triggering the null pointer dereference and potentially crashing or executing arbitrary code.
No, only versions 0 to 2.5.3 of the TensorFlow GPU package are affected. Versions 2.6.3, 2.7.1, and 2.8.0 (upcoming) will include patches for this vulnerability.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
