CVE-2021-29537: TensorFlow GPU - Heap Buffer Overflow in QuantizedResizeBilinear
Summary
CVE-2021-29537: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu 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
< f6c40f0c6cbf00d46c7717a26419f2062f2f8694
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-cpu · PyPI
The same CVE-2021-29537 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 community resources that enable researchers and developers to build and deploy machine learning models. TensorFlow GPU is a variant of TensorFlow that leverages GPU acceleration for faster computation. It is widely used in various industries for deep learning tasks.
Vulnerability Detail
A heap buffer overflow vulnerability exists in the QuantizedResizeBilinear function of TensorFlow GPU. This vulnerability can be exploited by an attacker by passing in invalid thresholds for the quantization. The implementation assumes that the two arguments are always valid scalars and tries to access the numeric value directly. By providing malicious input, an attacker can trigger a heap buffer overflow, potentially leading to remote code execution or denial of service.
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.
-
< 2.2.0rc02.2.0rc0pip install --upgrade "tensorflow-gpu==2.2.0rc0" -
>= 2.2.0, < 2.3.0rc02.3.0rc0pip install --upgrade "tensorflow-gpu==2.3.0rc0" -
>= 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 known workaround for this vulnerability. It is recommended to apply the provided fix by upgrading TensorFlow GPU to the fixed versions.
Conclusion
The heap buffer overflow vulnerability in TensorFlow GPU's QuantizedResizeBilinear function can be exploited by passing in invalid thresholds for quantization. Upgrading to the fixed versions of TensorFlow GPU or applying the backported fixes is crucial to mitigate this vulnerability. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow GPU is a variant of TensorFlow that utilizes GPU acceleration for faster computation. It is commonly used in deep learning tasks.
This vulnerability can potentially allow an attacker to execute arbitrary code or cause a denial of service by triggering a heap buffer overflow.
To fix this vulnerability, upgrade your TensorFlow GPU installation to version 2.5.0 or later. Alternatively, you can update to one of the backported fixes in TensorFlow 2.4.2, 2.3.3, 2.2.3, or 2.1.4.
No, there is no known workaround for this vulnerability. It is recommended to apply the provided fix by upgrading TensorFlow GPU.
You can find more information about this vulnerability in the official TensorFlow documentation or by contacting the TensorFlow support team.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
