CVE-2021-29524: Division by 0 in TensorFlow
Summary
CVE-2021-29524: Division by 0 in Conv2DBackpropFilter. Affects tensorflow across 4 version ranges.
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
Fixed in 4 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-29524 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 training deep learning models. It provides a comprehensive set of tools and libraries for building and deploying machine learning applications. TensorFlow supports various operations, including convolutional neural networks (CNNs) for image processing tasks. However, a vulnerability has been discovered in the Conv2DBackpropFilter operation of TensorFlow, which can lead to a division by zero error.
Vulnerability Detail
The vulnerability (CVE-2021-29524) exists in the tf.raw_ops.Conv2DBackpropFilter function of TensorFlow. An attacker can exploit this vulnerability by providing specific input parameters that trigger a division by zero error. This can be achieved by passing an empty input tensor with dimensions [0, 0, 1, 0] and a filter size of [1, 1, 1, 1]. The vulnerability arises from a modulus operation in the implementation, where the divisor is controlled by the caller. The impact of this vulnerability can result in a denial of service (DoS) condition or potential information disclosure.
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.
-
< 2.1.42.1.4pip install --upgrade "tensorflow==2.1.4" -
>= 2.2.0, < 2.2.32.2.3pip install --upgrade "tensorflow==2.2.3" -
>= 2.3.0, < 2.3.32.3.3pip install --upgrade "tensorflow==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow==2.4.2"
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Workaround
As a workaround, users can avoid calling the tf.raw_ops.Conv2DBackpropFilter function with the specific input parameters that trigger the vulnerability. If possible, it is recommended to update to the patched versions of TensorFlow to ensure complete mitigation of the vulnerability.
Conclusion
In conclusion, the vulnerability (CVE-2021-29524) in TensorFlow's tf.raw_ops.Conv2DBackpropFilter function can lead to a division by zero error, potentially resulting in a denial of service (DoS) condition or information disclosure. It is crucial to update to the patched versions of TensorFlow (2.5.0, 2.4.2, 2.3.3, 2.2.3, or 2.1.4) to mitigate this vulnerability. For further support and assistance in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open-source machine learning framework used for developing and training deep learning models.
The vulnerability can lead to a division by zero error, resulting in a denial of service (DoS) condition or potential information disclosure.
To fix this vulnerability, it is recommended to update to one of the patched versions of TensorFlow: TensorFlow 2.5.0, TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, or TensorFlow 2.1.4.
Yes, users can avoid calling the vulnerable function with the specific input parameters that trigger the vulnerability.
For more information regarding TensorFlow security, please refer to the official TensorFlow security guide.
References
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