CVE-2021-29555: TensorFlow FusedBatchNorm Denial of Service
Summary
CVE-2021-29555: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow across 5 version ranges.
< 1a2a87229d1d61e23a39373777c056161eb4084d
< 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-2021-29555 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 is widely used in various industries and research domains for tasks such as image recognition, natural language processing, and recommendation systems. However, a vulnerability has been discovered in TensorFlow that can lead to a denial of service (DoS) attack.
Vulnerability Detail
The vulnerability exists in the tf.raw_ops.FusedBatchNorm function of TensorFlow. This function is responsible for performing batch normalization, a common technique used in machine learning models to improve training stability and convergence. The implementation of FusedBatchNorm in TensorFlow performs a division operation based on the last dimension of the input tensor x. Since the last dimension is controlled by the user, an attacker can manipulate it to trigger a runtime error and cause a DoS condition. The impact of this vulnerability can be severe, as it can disrupt the availability of TensorFlow-based applications and services.
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
There is no known workaround for this vulnerability. It is recommended to apply the fix by upgrading to the patched versions of TensorFlow.
Conclusion
The vulnerability in TensorFlow's FusedBatchNorm function can be exploited by an attacker to cause a denial of service. It is crucial to update your TensorFlow installation to the latest patched version or one of the backported fixes to mitigate the risk. For further assistance and support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides a comprehensive set of tools and libraries for developing and deploying machine learning models.
Batch normalization is a technique used in machine learning models to normalize the inputs of each layer, improving training stability and convergence.
The vulnerability allows an attacker to manipulate the last dimension of the input tensor, triggering a runtime error and causing a denial of service condition.
The vulnerability can lead to a denial of service, disrupting the availability of TensorFlow-based applications and services.
To fix the vulnerability, upgrade your TensorFlow installation to one of the patched versions: 2.5.0, 2.4.2, 2.3.3, 2.2.3, or 2.1.4.
References
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