CVE-2021-29564: TensorFlow-GPU Null Pointer Dereference in tf.raw_ops.EditDistance
Summary
CVE-2021-29564: 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
< f4c364a5d6880557f6f5b6eb5cee2c407f0186b3
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-2021-29564 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 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 domains for training and inference of deep learning models.
Vulnerability Detail
The vulnerability (CVE-2021-29564) resides in the implementation of tf.raw_ops.EditDistance in TensorFlow-GPU. An attacker can trigger a null pointer dereference due to incomplete validation of input parameters. This vulnerability allows an attacker to crash the application or potentially execute arbitrary code, leading to a denial of service or remote 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.
-
< 2.1.42.1.4pip 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"
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 available for this vulnerability. It is crucial to update to the patched versions mentioned above to mitigate the risk.
Conclusion
In conclusion, the vulnerability (CVE-2021-29564) in TensorFlow-GPU's tf.raw_ops.EditDistance can result in a null pointer dereference, potentially leading to a denial of service or remote code execution. It is crucial to update to the patched versions mentioned above to mitigate the risk. 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 in machine learning tasks.
This vulnerability can lead to a denial of service or remote code execution if exploited by an attacker.
You can use Vulert's playground (https://vulert.com/scanner) to check if your application is affected by this vulnerability. Vulert monitors and alerts in real-time for open-source vulnerabilities without requiring access to the code or installation.
No, there are no known workarounds for this vulnerability. It is recommended to update to the patched versions.
You can find more information about this vulnerability in the official TensorFlow-GPU advisory database: https://github.com/pypa/advisory-database/blob/main/vulns/tensorflow-gpu/PYSEC-2021-690.yaml
References
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