CVE-2020-15201: Heap buffer overflow in Tensorflow
Summary
CVE-2020-15201: Heap buffer overflow in Tensorflow. Affects tensorflow versions >= 2.3.0, < 2.3.1. Fixed in 2.3.1. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2020-15201 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 heap buffer overflow.
Vulnerability Detail
The vulnerability, identified as CVE-2020-15201, specifically affects the RaggedCountSparseOutput implementation in Tensorflow. This implementation fails to validate the input arguments, particularly the splits tensor, which is responsible for partitioning the values tensor. As a result, a heap buffer overflow can occur. The issue arises when split_values does not end with a value at least num_values, causing a read outside the bounds of split_values when batch_idx grows too large. This vulnerability has a CVSS score of 4.8, 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 version below is the minimum fixed release for this vulnerability.
If you need the minimum change
2.3.1
This is the first release that contains the fix.
pip install --upgrade "tensorflow==2.3.1"Tip — Not sure which version your app runs? Vulert can match this fix to it. Scan free →
Workaround
There is no specific workaround mentioned for this vulnerability. However, upgrading to the patched version of TensorFlow is the recommended solution.
Conclusion
In conclusion, the vulnerability CVE-2020-15201 in Tensorflow can lead to a heap buffer overflow. Upgrading to TensorFlow 2.3.1 or later is recommended to fix this issue. For further support on vulnerability remediation, you can contact 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 heap buffer overflow, which may result in a crash or potentially allow an attacker to execute arbitrary code.
To fix this vulnerability, upgrade to TensorFlow 2.3.1 or later, which includes the necessary patches.
There is no specific workaround mentioned for this vulnerability. Upgrading to the patched version is the recommended solution.
This vulnerability was reported by members of the Aivul Team from Qihoo 360.
References
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