CVE-2021-29520: TensorFlow GPU - Heap Buffer Overflow in Conv3DBackprop Operations
Summary
CVE-2021-29520: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu 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
< 8f37b52e1320d8d72a9529b2468277791a261197
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-2021-29520 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 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 the training and inference processes of machine learning models.
Vulnerability Detail
The vulnerability in TensorFlow GPU arises from missing validation between arguments to tf.raw_ops.Conv3DBackprop* operations. This can lead to heap buffer overflows. The issue stems from the assumption made in the implementation that the input, filter_sizes, and out_backprop tensors have the same shape, as they are accessed in parallel. However, if these tensors have different shapes, it can result in a heap buffer overflow. The impact of this vulnerability can be severe, potentially leading to arbitrary 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.
-
< 2.1.42.1.4pip install --upgrade "tensorflow-gpu==2.1.4" -
>= 2.2.0, < 2.2.32.2.3pip install --upgrade "tensorflow-gpu==2.2.3" -
>= 2.3.0, < 2.3.32.3.3pip install --upgrade "tensorflow-gpu==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow-gpu==2.4.2"
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Workaround
There is no specific workaround mentioned for this vulnerability.
Conclusion
The vulnerability in TensorFlow GPU (CVE-2021-29520) can result in heap buffer overflows, potentially leading to arbitrary code execution or denial of service. It is crucial to upgrade to TensorFlow 2.5.0 or apply the fix by cherry-picking the relevant commit to mitigate this vulnerability. For further support on vulnerability remediation, you can reach out to DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow is an open source platform for machine learning that 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 the training and inference processes of machine learning models.
A heap buffer overflow occurs when a program writes data beyond the allocated memory buffer in the heap. This can lead to memory corruption and potentially allow an attacker to execute arbitrary code or cause a denial of service.
The possible consequences of this vulnerability include arbitrary code execution or denial of service. An attacker could exploit the heap buffer overflow to execute malicious code or crash the application, leading to a denial of service.
To fix this vulnerability, it is recommended to upgrade to TensorFlow 2.5.0 or any subsequent versions that include the fix. Alternatively, if you are using an affected version, you can apply the fix by cherry-picking the relevant commit.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
