CVE-2021-29600: TensorFlow OneHot TFLite Operator Division by Zero Vulnerability
Summary
CVE-2021-29600: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-cpu across 5 version ranges.
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
< 3ebedd7e345453d68e279cfc3e4072648e5e12e5
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-gpu · PyPI
The same CVE-2021-29600 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 building and deploying machine learning models. The OneHot TFLite operator is a component of TensorFlow that is used for converting integer indices into one-hot encoded vectors. This operator is vulnerable to a division by zero error, which can be exploited by an attacker to craft a malicious model.
Vulnerability Detail
The vulnerability in the OneHot TFLite operator arises from a division by zero error in the implementation code. When the indices input tensor has at least one dimension with a value of 0, the prefix_dim_size variable becomes 0 as well. This leads to a division by zero error during the execution of the operator. An attacker can exploit this vulnerability by crafting a model that triggers this condition. The impact of this vulnerability can vary depending on the context in which TensorFlow is used, but it can potentially lead to crashes, denial of service, or even remote code execution.
How To Fix
Latest published version: 2.21.0 as of 22 Oct 2026
pip install --upgrade "tensorflow-cpu==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-cpu==2.1.4" -
>= 2.2.0, < 2.2.32.2.3pip install --upgrade "tensorflow-cpu==2.2.3" -
>= 2.3.0, < 2.3.32.3.3pip install --upgrade "tensorflow-cpu==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow-cpu==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 a patched version of TensorFlow.
Conclusion
The OneHot TFLite operator in TensorFlow is vulnerable to a division by zero error, which can be exploited by an attacker to craft a malicious model. The fix for this vulnerability is included in TensorFlow 2.5.0 and has been backported to earlier versions. It is recommended to upgrade to a patched version of TensorFlow to mitigate the risk. For further support on vulnerability remediation, contact DevNack.com.
See every vulnerability recorded for tensorflow-cpu →
FAQ
TensorFlow is an open source platform for machine learning that provides tools and libraries for building and deploying machine learning models.
The OneHot TFLite operator is a component of TensorFlow that converts integer indices into one-hot encoded vectors.
The vulnerability occurs due to a division by zero error in the implementation code of the operator.
The impact of this vulnerability can vary depending on the context, but it can potentially lead to crashes, denial of service, or remote code execution.
To fix this vulnerability, upgrade your TensorFlow installation to a patched version (2.5.0 or later).
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-cpu.
