CVE-2021-37690: TensorFlow GPU - ShapeAndType Struct Information Disclosure
Summary
CVE-2021-37690: 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
< ee119d4a498979525046fba1c3dd3f13a039fbb1
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-2021-37690 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
Check if this vulnerability affects your application
Upload a manifest or SBOM and we'll show whether you're affected, plus every other risky package in the same scan.
No signup required · Results in about 60 seconds
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 GPU is a specific package that enables GPU acceleration for TensorFlow. It allows users to leverage the power of GPUs to accelerate their machine learning workloads.
Vulnerability Detail
In affected versions of TensorFlow GPU, there is a vulnerability that can lead to information disclosure. When running shape functions, certain functions, such as MutableHashTableShape, produce extra output information in the form of a ShapeAndType struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately. If the upstream code attempts to access this shape information, it can trigger a segmentation fault (segfault). This vulnerability can potentially be exploited by an attacker to crash the application or leak sensitive information from the memory.
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 mentioned for this vulnerability.
Conclusion
The vulnerability in TensorFlow GPU (CVE-2021-37690) allows for information disclosure through the use of shape functions. It is crucial to update TensorFlow GPU to the latest patched version or apply the provided patches to mitigate the risk. Failure to do so may result in application crashes or the exposure of sensitive information. For further support on 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 set of tools and resources for developing and deploying machine learning models.
TensorFlow GPU is a specific package that enables GPU acceleration for TensorFlow. It allows users to leverage the power of GPUs to accelerate their machine learning workloads.
This vulnerability can potentially be exploited by an attacker to crash the application or leak sensitive information from the memory.
To fix this vulnerability, it is recommended to update TensorFlow GPU to version 2.6.0 or apply the provided patches. The fix has been implemented in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. The patch will also be included in TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, which are still within the supported range. Users should update their TensorFlow GPU installation to the latest patched version to mitigate the vulnerability.
There is no specific workaround mentioned for this vulnerability.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
