CVE-2021-37650: Segfault and heap buffer overflow in TensorFlow
Summary
CVE-2021-37650: Segfault and heap buffer overflow in {Experimental,}DatasetToTFRecord. Affects tensorflow across 3 version ranges.
< 2.3.4
>= 2.4.0, < 2.4.3
>= 2.5.0, < 2.5.1
Fixed in 2.3.4, 2.4.3 or 2.5.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-37650 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 open-source machine learning framework developed by Google. It provides a comprehensive ecosystem of tools, libraries, and resources for building and deploying machine learning models. TensorFlow is widely used in various domains, including research, industry, and academia. However, a vulnerability has been discovered in TensorFlow that can lead to a segfault and heap buffer overflow.
Vulnerability Detail
The vulnerability exists in the implementation of tf.raw_ops.ExperimentalDatasetToTFRecord and tf.raw_ops.DatasetToTFRecord functions in TensorFlow. These functions are used to convert datasets to TFRecord format. The implementation assumes that all records in the dataset are of string type, but there is no check for this assumption. As a result, if non-string records are used, it can trigger a heap buffer overflow and segmentation fault. An attacker could potentially exploit this vulnerability to execute arbitrary code or cause a denial of service.
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.
-
< 2.3.42.3.4pip install --upgrade "tensorflow==2.3.4" -
>= 2.4.0, < 2.4.32.4.3pip install --upgrade "tensorflow==2.4.3" -
>= 2.5.0, < 2.5.12.5.1pip install --upgrade "tensorflow==2.5.1"
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Workaround
If updating TensorFlow is not immediately possible, a workaround is to ensure that all records in the dataset are of string type before using the ExperimentalDatasetToTFRecord or DatasetToTFRecord functions. This can be achieved by converting the records to strings using appropriate encoding methods.
Conclusion
The vulnerability in TensorFlow can lead to a heap buffer overflow and segmentation fault. It is crucial to update to the latest patched version of TensorFlow (2.3.4, 2.4.3, 2.5.1, or 2.6.0) to mitigate the vulnerability. If immediate updating is not possible, ensure that all records in the dataset are of string type before using the affected functions. For further support on vulnerability remediation, contact DevNack.com.
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FAQ
TensorFlow is an open-source machine learning framework developed by Google. It provides tools and resources for building and deploying machine learning models.
The vulnerability can lead to a heap buffer overflow and segmentation fault, potentially allowing an attacker to execute arbitrary code or cause a denial of service.
Update TensorFlow to the latest patched version (2.3.4, 2.4.3, 2.5.1, or 2.6.0) to fix the vulnerability.
If updating TensorFlow is not immediately possible, ensure that all records in the dataset are of string type before using the affected functions.
This vulnerability was reported by members of the Aivul Team from Qihoo 360.
References
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