CVE-2020-15198: TensorFlow - SparseCountSparseOutput Shape Mismatch Vulnerability
Summary
CVE-2020-15198: In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. Affects tensorflow across 2 version ranges.
< 2.3.1
< 3cbb917b4714766030b28eba9fb41bb97ce9ee02
Fixed in 3cbb917b4714766030b28eba9fb41bb97ce9ee02. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2020-15198 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 that provides a comprehensive ecosystem of tools, libraries, and community resources. It is widely used for building and deploying machine learning models. The SparseCountSparseOutput function in TensorFlow is responsible for counting the number of sparse elements in a tensor. However, prior to version 2.3.1, this implementation does not validate the shape of the input arguments, specifically the indices and values tensors. This lack of validation can lead to shape mismatches, resulting in out-of-bounds memory accesses.
Vulnerability Detail
The vulnerability (CVE-2020-15198) arises from the absence of shape validation in the SparseCountSparseOutput function of TensorFlow. When the indices tensor does not have the same shape as the values tensor, accessing the values in parallel can lead to accessing memory outside the bounds of allocated buffers. This can potentially result in memory corruption, crashes, or even remote code execution if exploited by an attacker. The issue has been addressed in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and released in TensorFlow version 2.3.1.
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
3cbb917b4714766030b28eba9fb41bb97ce9ee02
This is the first release that contains the fix.
pip install --upgrade "tensorflow==3cbb917b4714766030b28eba9fb41bb97ce9ee02"Tip — Not sure which version your app runs? Vulert can match this fix to it. Scan free →
Workaround
There is no known workaround for this vulnerability. It is recommended to upgrade to the patched version of TensorFlow as soon as possible.
Conclusion
The SparseCountSparseOutput shape mismatch vulnerability in TensorFlow can have serious security implications, including memory corruption and potential remote code execution. It is crucial to upgrade to TensorFlow version 2.3.1 or later to mitigate this vulnerability. For further assistance or support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open-source machine learning framework widely used for building and deploying machine learning models.
The SparseCountSparseOutput function in TensorFlow is used to count the number of sparse elements in a tensor.
The vulnerability can lead to out-of-bounds memory accesses, potentially resulting in memory corruption, crashes, or remote code execution.
Yes, the vulnerability has been patched in TensorFlow version 2.3.1.
To fix this vulnerability, upgrade your TensorFlow installation to version 2.3.1 or later.
References
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