CVE-2020-15190: Segfault in Tensorflow
Summary
CVE-2020-15190: Segfault in Tensorflow. Affects tensorflow across 5 version ranges.
< 1.15.4
>= 2.0.0, < 2.0.3
>= 2.1.0, < 2.1.2
>= 2.2.0, < 2.2.1
>= 2.3.0, < 2.3.1
Fixed in 5 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-2020-15190 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 segmentation fault.
Vulnerability Detail
The vulnerability, identified as CVE-2020-15190, affects the tf.raw_ops.Switch operation in Tensorflow. This operation takes a tensor and a boolean as input and outputs two tensors. Depending on the boolean value, one of the tensors is the input tensor, while the other should be an empty tensor. However, due to a flaw in the eager runtime, both tensors are traversed, even though only one is defined. This results in a reference being bound to a null pointer, leading to undefined behavior and a potential segmentation fault. The vulnerability has a CVSS score of 5.3, indicating a moderate severity level.
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.
-
< 1.15.41.15.4pip install --upgrade "tensorflow==1.15.4" -
>= 2.0.0, < 2.0.32.0.3pip install --upgrade "tensorflow==2.0.3" -
>= 2.1.0, < 2.1.22.1.2pip install --upgrade "tensorflow==2.1.2" -
>= 2.2.0, < 2.2.12.2.1pip install --upgrade "tensorflow==2.2.1" -
>= 2.3.0, < 2.3.12.3.1pip install --upgrade "tensorflow==2.3.1"
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Workaround
There is no specific workaround mentioned for this vulnerability. The recommended approach is to upgrade to the patched versions of Tensorflow.
Conclusion
The vulnerability in Tensorflow (CVE-2020-15190) can lead to a segmentation fault, potentially causing crashes or instability in applications. It is crucial to upgrade to the patched versions of Tensorflow (1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1) to mitigate this 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 machine learning framework developed by Google. It provides tools and resources for building and deploying machine learning models.
The vulnerability can lead to a segmentation fault in Tensorflow, potentially causing crashes or instability in applications using the affected versions.
To fix this vulnerability, it is recommended to upgrade to the patched versions of Tensorflow (1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1).
No specific workaround is mentioned for this vulnerability. Upgrading to the patched versions is the recommended solution.
You can find more information about this vulnerability in the security guide provided by the Tensorflow team. The guide contains details about the security model and how to contact the team for any issues or questions.
References
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