CVE-2021-29512: TensorFlow GPU - Heap Buffer Overflow in RaggedBincount
Summary
CVE-2021-29512: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu across 3 version ranges.
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
< eebb96c2830d48597d055d247c0e9aebaea94cd5
Fixed in 2.3.3 or 2.4.2, 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-2021-29512 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 variant of TensorFlow that leverages GPU acceleration for faster computation. It is widely used in various industries and research domains for training and inference of machine learning models.
Vulnerability Detail
The vulnerability (CVE-2021-29512) exists in the RaggedBincount function of TensorFlow GPU. When the splits argument of RaggedBincount does not specify a valid SparseTensor, it can trigger a heap buffer overflow. This leads to a read operation outside the bounds of the splits tensor buffer, potentially causing memory corruption and arbitrary code execution. The issue arises due to improper bounds checking in the implementation of the RaggedBincount op.
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, < 2.3.32.3.3pip install --upgrade "tensorflow-gpu==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow-gpu==2.4.2"
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 strongly advised to apply the recommended fix by updating TensorFlow GPU to a patched version.
Conclusion
The vulnerability (CVE-2021-29512) in TensorFlow GPU's RaggedBincount function can lead to a heap buffer overflow, potentially resulting in memory corruption and arbitrary code execution. Users are strongly advised to update their TensorFlow GPU installation to a patched version (2.5.0 or later) 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 GPU is a variant of TensorFlow that utilizes GPU acceleration for faster machine learning computations.
The RaggedBincount function in TensorFlow GPU is used to compute the number of occurrences of each value in a ragged tensor.
An attacker can exploit this vulnerability by providing a malicious splits argument that does not specify a valid SparseTensor. This can trigger a heap buffer overflow and potentially lead to arbitrary code execution.
The vulnerability affects TensorFlow GPU versions 2.3.0 to 2.3.2, 2.4.0 to 2.4.1, and 2.5.0 (prior to the fix).
There is no known exploit in the wild at the time of this advisory. However, it is crucial to apply the recommended fix to mitigate the risk of potential attacks.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
