CVE-2021-29564: TensorFlow 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 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-cpu · PyPI
- tensorflow-gpu · 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 developing and deploying machine learning models. TensorFlow is widely used in various domains, including research, industry, and academia. The vulnerability described here affects the implementation of tf.raw_ops.EditDistance in TensorFlow.
Vulnerability Detail
The vulnerability arises from incomplete validation of input parameters in the implementation of tf.raw_ops.EditDistance. An attacker can exploit this flaw to trigger a null pointer dereference. This vulnerability has the potential to lead to a crash or denial of service (DoS) condition. The issue has been assigned CVE-2021-29564 and has been reported to the TensorFlow project.
How To Fix
Latest published version: 2.21.0 as of 22 Oct 2026
pip install --upgrade "tensorflow==2.21.0"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==2.1.4" -
>= 2.2.0, < 2.2.32.2.3pip install --upgrade "tensorflow==2.2.3" -
>= 2.3.0, < 2.3.32.3.3pip install --upgrade "tensorflow==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow==2.4.2"
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Workaround
No specific workaround has been provided for this vulnerability. It is recommended to apply the available patches or update to the fixed versions of TensorFlow.
Conclusion
The vulnerability in TensorFlow's tf.raw_ops.EditDistance can be exploited by an attacker to trigger a null pointer dereference, potentially leading to a crash or denial of service (DoS) condition. Users are advised to update their TensorFlow installations to the latest patched versions or apply the backported patches to mitigate the vulnerability. For further support on vulnerability remediation, you can reach out to DevNack.com.
See every vulnerability recorded for tensorflow →
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.
The vulnerability can be exploited by an attacker to trigger a null pointer dereference, potentially leading to a crash or denial of service (DoS) condition.
The vulnerability affects TensorFlow versions 2.1.4 and above, including TensorFlow 2.2.x, 2.3.x, and 2.4.x.
To fix this vulnerability, it is recommended to update your TensorFlow installation to the latest patched version, which is TensorFlow 2.5.0. Alternatively, you can also apply the backported patches for TensorFlow 2.4.2, 2.3.3, 2.2.3, and 2.1.4.
No specific workaround has been provided for this vulnerability. It is recommended to update to the patched versions of TensorFlow.
References
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