CVE-2021-37683: FPE in TFLite division operations in TensorFlow
Summary
CVE-2021-37683: FPE in TFLite division operations. Affects tensorflow across 3 version ranges.
< 2.3.4
>= 2.4.0, < 2.4.3
>= 2.5.0, < 2.5.1
Fixed in 2.3.4, 2.4.3 or 2.5.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-37683 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 that provides a wide range of tools and libraries for building and deploying machine learning models. It is widely used in various domains, including research, industry, and academia. TensorFlow Lite (TFLite) is a lightweight version of TensorFlow designed for mobile and embedded devices. It allows developers to run machine learning models on resource-constrained platforms. However, TFLite is vulnerable to a division by 0 error in its division operations, which can have significant implications for the accuracy and reliability of machine learning models deployed using TFLite.
Vulnerability Detail
The vulnerability in TFLite arises from a lack of checks on the divisor tensor, which can contain zero elements. This can lead to a division by zero error during the execution of division operations. An attacker could exploit this vulnerability to cause denial of service (DoS) or manipulate the results of machine learning models by injecting zero elements into the divisor tensor. The vulnerability has a CVSS score of 5.5, indicating a moderate severity level.
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.
-
< 2.3.42.3.4pip install --upgrade "tensorflow==2.3.4" -
>= 2.4.0, < 2.4.32.4.3pip install --upgrade "tensorflow==2.4.3" -
>= 2.5.0, < 2.5.12.5.1pip install --upgrade "tensorflow==2.5.1"
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 mentioned for this vulnerability.
Conclusion
The vulnerability in TensorFlow Lite division operations can have significant implications for the accuracy and reliability of machine learning models. It is crucial to update to the patched versions of TensorFlow to mitigate the risk. For further support on vulnerability remediation, you can reach out to DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open-source machine learning framework used for building and deploying machine learning models.
TensorFlow Lite (TFLite) is a lightweight version of TensorFlow designed for mobile and embedded devices.
The vulnerability can lead to a division by zero error in TFLite division operations, potentially causing denial of service (DoS) or manipulation of machine learning model results.
To fix the vulnerability, update your TensorFlow installation to one of the patched versions: TensorFlow 2.6.0, TensorFlow 2.5.1, TensorFlow 2.4.3, or TensorFlow 2.3.4.
No specific workaround has been mentioned for this vulnerability.
References
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