CVE-2020-15197: Denial of Service in Tensorflow
Summary
CVE-2020-15197: Denial of Service 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-2020-15197 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. The vulnerability identified as CVE-2020-15197 affects versions 2.3.0 of the tensorflow, tensorflow-cpu, and tensorflow-gpu packages. This vulnerability allows malicious users to pass tensors of different rank, causing a CHECK assertion failure and resulting in a crash. This can lead to denial of service in serving installations if users have control over the input sparse tensor.
Vulnerability Detail
The vulnerability arises from the SparseCountSparseOutput implementation in Tensorflow. This implementation does not validate that the input arguments form a valid sparse tensor. Specifically, it does not verify that the indices tensor has rank 2, which is necessary for proper matrix access. Malicious users can exploit this by passing tensors of different rank, triggering a CHECK assertion failure and causing a crash. This vulnerability can be used to launch denial of service attacks on serving installations where users can control the components of the input sparse tensor.
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.
Conclusion
The vulnerability CVE-2020-15197 in Tensorflow allows malicious users to launch denial of service attacks by passing tensors of different rank. It has been patched in version 2.3.1 of the tensorflow, tensorflow-cpu, and tensorflow-gpu packages. Users are advised to upgrade to this version to mitigate the issue. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
The vulnerability allows malicious users to cause denial of service in serving installations by passing tensors of different rank, resulting in a crash.
Versions 2.3.0 of the tensorflow, tensorflow-cpu, and tensorflow-gpu packages are affected.
Yes, the vulnerability has been patched in version 2.3.1 of the tensorflow, tensorflow-cpu, and tensorflow-gpu packages.
You can upgrade to the patched version by running the command 'pip install --upgrade tensorflow'.
No specific workaround has been mentioned for this vulnerability.
References
Related vulnerabilities
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