CVE-2022-23559: Integer Overflow in TFLite
Summary
CVE-2022-23559: Integer overflow in TFLite. 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-2022-23559 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 widely used for various tasks such as image recognition, natural language processing, and deep learning. It provides a comprehensive ecosystem of tools, libraries, and resources for developing and deploying machine learning models. TFLite is a component of TensorFlow that enables the deployment of machine learning models on mobile and embedded devices. It allows developers to optimize and run TensorFlow models efficiently on resource-constrained platforms.
Vulnerability Detail
The vulnerability identified as CVE-2022-23559 affects TFLite's embedding lookup operations. It arises due to an integer overflow in the calculation of embedding_size and lookup_size, which are products of user-provided values. An attacker can exploit this vulnerability by crafting a malicious TFLite model that triggers an integer overflow during the multiplication process. This can lead to heap out-of-bounds read/write, potentially enabling the attacker to execute arbitrary code or access sensitive information. The vulnerability has a CVSS score of 8.8, indicating a high 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.
-
< 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
There is no specific workaround mentioned for this vulnerability. Users are advised to update to the patched versions of TensorFlow as mentioned in the 'how_to_fix' section.
Conclusion
The identified vulnerability in TFLite's embedding lookup operations can be exploited by an attacker to trigger an integer overflow, potentially leading to heap out-of-bounds read/write. The TensorFlow team has promptly addressed this issue and provided patches in the latest versions of TensorFlow. Users are strongly advised to update their installations to the patched versions to mitigate the risk. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open-source machine learning framework used for developing and deploying machine learning models.
TFLite is a component of TensorFlow that allows the deployment of machine learning models on mobile and embedded devices.
An integer overflow occurs when the result of an arithmetic operation exceeds the maximum value that can be represented by the data type.
The vulnerability can lead to heap out-of-bounds read/write, which may enable an attacker to execute arbitrary code or access sensitive information.
To fix this vulnerability, update your TensorFlow installation to the patched versions mentioned in the 'how_to_fix' section.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
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