CVE-2022-35989: TensorFlow MaxPool CHECK Fail Vulnerability
Summary
CVE-2022-35989: TensorFlow vulnerable to CHECK fail in MaxPool. Affects tensorflow across 3 version ranges.
< 2.7.2
>= 2.8.0, < 2.8.1
>= 2.9.0, < 2.9.1
Fixed in 2.7.2, 2.8.1 or 2.9.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
- tensorflow · Bitnami
The same CVE-2022-35989 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 library developed by Google, widely used for building and training deep learning models. It provides a flexible ecosystem for deploying machine learning applications across various platforms. However, TensorFlow has a vulnerability in its MaxPool operation, which can lead to denial of service under specific conditions.
Vulnerability Detail
The vulnerability arises when the MaxPool operation receives a window size input array (ksize) with dimensions greater than its input tensor. This situation triggers a CHECK fail in the GPU kernel, which can be exploited to cause a denial of service attack. An attacker can craft inputs that lead to this failure, potentially disrupting services that rely on TensorFlow for processing.
How To Fix
Latest published version: 2.21.0 as of 22 Oct 2026
pip install --upgrade "tensorflow==2.21.0"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.
-
< 2.7.22.7.2pip install --upgrade "tensorflow==2.7.2" -
>= 2.8.0, < 2.8.12.8.1pip install --upgrade "tensorflow==2.8.1" -
>= 2.9.0, < 2.9.12.9.1pip install --upgrade "tensorflow==2.9.1"
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
As a workaround, ensure that the ksize parameter passed to the MaxPool operation does not exceed the dimensions of the input tensor. Here is an example of how to avoid the vulnerability:
import tensorflow as tf import numpy as np
input_tensor = np.ones([1, 1, 1, 1]) ksize = [1, 1, 1, 1] # Ensure ksize does not exceed input dimensions strides = [1, 1, 1, 1] padding = 'VALID' data_format = 'NCHW'
tf.raw_ops.MaxPool(input=input_tensor, ksize=ksize, strides=strides, padding=padding, data_format=data_format)
Conclusion
The CVE-2022-35989 vulnerability in TensorFlow's MaxPool operation poses a risk of denial of service due to improper input handling. Users are advised to update to the latest patched versions to mitigate this risk and ensure the security of their applications.
See every vulnerability recorded for tensorflow →
FAQ
CVE-2022-35989 is a vulnerability in TensorFlow's MaxPool operation that can lead to a denial of service when improperly configured input parameters are used.
You can use the Vulert playground at Vulert Scanner to check if your application is affected by this vulnerability without needing to sign up.
TensorFlow versions prior to 2.7.2, 2.8.1, and 2.9.1 are affected by this vulnerability.
The CVSS score of this vulnerability is 5.9, indicating a moderate severity level.
You can update TensorFlow by running the command: pip install --upgrade tensorflow in your terminal.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
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