CVE-2022-21740: TensorFlow Heap Overflow Vulnerability
Summary
CVE-2022-21740: Heap overflow in Tensorflow. Affects tensorflow across 3 version ranges.
< 2.5.3
>= 2.6.0, < 2.6.3
>= 2.7.0, < 2.7.1
Fixed in 2.5.3, 2.6.3 or 2.7.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-gpu · PyPI
- tensorflow-cpu · PyPI
The same CVE-2022-21740 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 library developed by Google, widely used for building and training machine learning models. It provides a flexible ecosystem of tools, libraries, and community resources that enables researchers and developers to create and deploy machine learning applications. However, it is susceptible to vulnerabilities that can compromise its functionality and security.
Vulnerability Detail
The vulnerability arises from a heap overflow in the implementation of the SparseCountSparseOutput function in TensorFlow. This flaw can be exploited when specific parameters are passed to the function, leading to potential memory corruption. The affected code can be triggered using the following Python snippet: import tensorflow as tf; tf.raw_ops.SparseCountSparseOutput(indices=[[-1,-1]], values=[2], dense_shape=[1, 1], weights=[1], binary_output=True, minlength=-1, maxlength=-1). If exploited, this vulnerability can lead to unauthorized access, data corruption, or application crashes.
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.
-
< 2.5.32.5.3pip install --upgrade "tensorflow==2.5.3" -
>= 2.6.0, < 2.6.32.6.3pip install --upgrade "tensorflow==2.6.3" -
>= 2.7.0, < 2.7.12.7.1pip install --upgrade "tensorflow==2.7.1"
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Workaround
Currently, there are no specific workarounds mentioned for this vulnerability. The best course of action is to update to the patched versions as soon as possible.
Conclusion
The heap overflow vulnerability in TensorFlow (CVE-2022-21740) poses significant risks to applications using the library. It is essential to update to the patched versions to ensure the security and stability of your machine learning applications. Regular monitoring for vulnerabilities using tools like Vulert can help maintain a secure environment.
See every vulnerability recorded for tensorflow →
FAQ
CVE-2022-21740 is a vulnerability in TensorFlow that allows for a heap overflow, potentially leading to memory corruption and application instability.
You can use Vulert to monitor and alert for open-source vulnerabilities in your software. Visit the Vulert playground at Vulert Scanner to check if your application is affected without needing to sign up.
The affected versions of TensorFlow are all versions prior to 2.5.3, 2.6.3, and 2.7.1.
The CVSS score of this vulnerability is 7.6, indicating a high severity level.
While there are no specific workarounds, it is crucial to prioritize updating TensorFlow to the patched versions to mitigate the risk of exploitation.
References
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