CVE-2021-29566: TensorFlow - Out-of-Bounds Write Vulnerability
Summary
CVE-2021-29566: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow 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
< 3f6fe4dfef6f57e768260b48166c27d148f3015f
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-2021-29566 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 domains, including research, industry, and academia. It offers extensive support for deep learning algorithms and enables efficient computation on both CPUs and GPUs.
Vulnerability Detail
The vulnerability (CVE-2021-29566) in TensorFlow allows an attacker to write outside the bounds of heap allocated arrays by passing invalid arguments to the tf.raw_ops.Dilation2DBackpropInput function. The issue arises due to the lack of validation before writing to the output array. While the loop indices (h_out and w_out) are guaranteed to be within range for out_backprop, there are no similar guarantees for h_in_max/w_in_max and in_backprop. This vulnerability can be exploited to overwrite adjacent memory, potentially leading to memory corruption, crashes, or arbitrary code execution. The impact of this vulnerability depends on the context in which TensorFlow is used and the specific data being processed.
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.
-
< 2.2.0rc02.2.0rc0pip install --upgrade "tensorflow==2.2.0rc0" -
>= 2.2.0, < 2.3.0rc02.3.0rc0pip install --upgrade "tensorflow==2.3.0rc0" -
>= 2.3.0, < 2.3.42.3.4pip install --upgrade "tensorflow==2.3.4" -
>= 2.4.0, < 2.4.32.4.3pip install --upgrade "tensorflow==2.4.3"
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
There is no specific workaround provided for this vulnerability. It is recommended to apply the available fix by upgrading to a patched version of TensorFlow.
Conclusion
The out-of-bounds write vulnerability in TensorFlow (CVE-2021-29566) can be exploited by passing invalid arguments to the tf.raw_ops.Dilation2DBackpropInput function. It is crucial to upgrade to the patched versions of TensorFlow or apply the available fixes to mitigate the risk. Regularly updating your software and following secure coding practices are essential for maintaining the security of your machine learning applications.
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.
This vulnerability allows an attacker to write outside the bounds of heap allocated arrays, potentially leading to memory corruption, crashes, or arbitrary code execution.
The vulnerability affects TensorFlow versions 2.1.4 and above. The fix has been backported to TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.
To fix this vulnerability, upgrade to TensorFlow 2.5.0 or apply the available patches for TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.
There are no specific workarounds provided for this vulnerability. It is recommended to upgrade to a patched version of TensorFlow.
References
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