CVE-2021-29550: TensorFlow-gpu - Division by Zero Denial of Service
Summary
CVE-2021-29550: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu across 5 version ranges.
>= 2.2.0, < 2.3.0rc0
< 2.2.0rc0
>= 2.3.0, < 2.3.4
>= 2.4.0, < 2.4.3
< 548b5eaf23685d86f722233d8fbc21d0a4aecb96
Fixed in 4 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-cpu · PyPI
The same CVE-2021-29550 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 end-to-end open source platform for machine learning. It provides a comprehensive ecosystem of tools, libraries, and resources for developing and deploying machine learning models. TensorFlow-gpu is a specific package that enables GPU acceleration for TensorFlow. It allows users to leverage the power of GPUs to accelerate their machine learning workflows.
Vulnerability Detail
The vulnerability identified as CVE-2021-29550 affects the tf.raw_ops.FractionalAvgPool function in TensorFlow-gpu. An attacker can exploit this vulnerability to cause a runtime division by zero error, leading to a denial of service. The vulnerability arises from the implementation of the function, which computes a divisor quantity by dividing two user-controlled values: input_size[i] and pooling_ratio_[i]. If the value in input_size[i] is smaller than pooling_ratio_[i], the floor operation results in output_size[i] being 0. This computed value is later used as an argument in the GeneratePoolingSequence function, where a division in a modulo operation occurs. Since output_length can be 0, this results in a runtime crash. The vulnerability can have severe consequences, including service disruption and potential data loss.
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.
-
< 2.2.0rc02.2.0rc0pip install --upgrade "tensorflow-gpu==2.2.0rc0" -
>= 2.2.0, < 2.3.0rc02.3.0rc0pip install --upgrade "tensorflow-gpu==2.3.0rc0" -
>= 2.3.0, < 2.3.42.3.4pip install --upgrade "tensorflow-gpu==2.3.4" -
>= 2.4.0, < 2.4.32.4.3pip install --upgrade "tensorflow-gpu==2.4.3"
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Workaround
There is no specific workaround mentioned for this vulnerability. However, as a general best practice, it is recommended to follow secure coding practices and keep all software and dependencies up to date to minimize the risk of vulnerabilities.
Conclusion
The vulnerability identified as CVE-2021-29550 in TensorFlow-gpu can result in a division by zero error and denial of service. It is crucial to update to the fixed version of TensorFlow or TensorFlow-gpu to mitigate this vulnerability. Following secure coding practices and keeping software up to date are essential to minimize the risk of vulnerabilities. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow is an open source platform for machine learning that provides a comprehensive set of tools and resources for developing and deploying machine learning models.
TensorFlow-gpu is a specific package that enables GPU acceleration for TensorFlow. It allows users to leverage the power of GPUs to accelerate their machine learning workflows.
This vulnerability can lead to a runtime division by zero error and denial of service. It can cause service disruption and potential data loss.
The recommended fix is to update to TensorFlow 2.5.0 or later, or the corresponding version of TensorFlow-gpu that includes the fix.
There are no specific workarounds mentioned for this vulnerability. It is recommended to follow secure coding practices and keep software and dependencies up to date.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
