CVE-2021-37681: TensorFlow GPU - Null Pointer Error in SVDF Implementation
Summary
CVE-2021-37681: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu across 3 version ranges.
>= 2.3.0, < 2.3.4
>= 2.4.0, < 2.4.3
< 5b048e87e4e55990dae6b547add4dae59f4e1c76
Fixed in 2.3.4 or 2.4.3, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-cpu · PyPI
The same CVE-2021-37681 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 for building and deploying machine learning models. TensorFlow GPU is a variant of TensorFlow that leverages GPU acceleration for faster computation. It is widely used in various industries and research fields for deep learning tasks.
Vulnerability Detail
The vulnerability (CVE-2021-37681) exists in the implementation of the Singular Value Decomposition Filter (SVDF) in TensorFlow Lite (TFLite). The SVDF implementation in TFLite is vulnerable to a null pointer error. Specifically, the GetVariableInput function can return a null pointer, but the GetTensorData function assumes that the argument is always a valid tensor. Additionally, the expression tensor->is_variable can trigger a null pointer exception when GetVariableInput calls GetMutableInput and it returns nullptr. This vulnerability can lead to a crash or potentially be exploited for arbitrary code execution.
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.
-
>= 2.3.0, < 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"
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. Users are strongly encouraged to apply the patch or update to the fixed versions of TensorFlow as soon as possible.
Conclusion
The vulnerability (CVE-2021-37681) in TensorFlow GPU's SVDF implementation poses a risk of null pointer errors, potentially leading to crashes or arbitrary code execution. It is crucial for users to update their TensorFlow installations to the patched versions or apply the provided fix to mitigate this vulnerability. For further assistance or support in 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 ecosystem for building and deploying machine learning models.
TensorFlow GPU is a variant of TensorFlow that leverages GPU acceleration for faster computation.
SVDF stands for Singular Value Decomposition Filter, which is a mathematical technique used in machine learning for dimensionality reduction and feature extraction.
A null pointer error occurs when a program tries to access or dereference a memory address that is null (i.e., does not point to any valid memory location). This can lead to crashes or undefined behavior.
The vulnerability can result in crashes or potentially be exploited for arbitrary code execution, which could lead to unauthorized access, data breaches, or other security compromises.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
