CVE-2022-41911: Invalid char to bool conversion when printing a tensor in TensorFlow
Summary
CVE-2022-41911: Invalid char to bool conversion when printing a tensor. Affects tensorflow across 3 version ranges.
< 2.8.4
>= 2.9.0, < 2.9.3
>= 2.10.0, < 2.10.1
Fixed in 2.8.4, 2.9.3 or 2.10.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow-gpu · PyPI
- tensorflow-gpu · PyPI
- tensorflow · Bitnami
The same CVE-2022-41911 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 community resources for building and deploying machine learning models. TensorFlow allows users to define and manipulate tensors, which are multi-dimensional arrays used to represent data in machine learning computations. Tensors can store various types of data, including numeric values, strings, and booleans.
Vulnerability Detail
The vulnerability (CVE-2022-41911) in TensorFlow arises when printing a tensor. The underlying storage of a tensor is a const char* array, and when this data is typecasted to the element type, conversions from char to bool can result in undefined behavior. Specifically, if the char is not 0 or 1, sanitizers and fuzzers may crash. This vulnerability can be exploited by an attacker to cause a denial of service (DoS) or potentially execute arbitrary code.
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.
-
< 2.8.42.8.4pip install --upgrade "tensorflow==2.8.4" -
>= 2.9.0, < 2.9.32.9.3pip install --upgrade "tensorflow==2.9.3" -
>= 2.10.0, < 2.10.12.10.1pip install --upgrade "tensorflow==2.10.1"
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Workaround
There is no specific workaround provided for this vulnerability. However, users can minimize the risk by ensuring that they are using the latest patched version of TensorFlow. Additionally, it is recommended to follow best practices for secure coding and regularly update software dependencies to address any known vulnerabilities.
Conclusion
The vulnerability (CVE-2022-41911) in TensorFlow, which involves an invalid char to bool conversion when printing a tensor, has been addressed through code patches. Users are advised to update their TensorFlow installations to the latest patched version to mitigate the vulnerability. 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 developed by Google. It provides tools and libraries for building and deploying machine learning models.
A tensor is a multi-dimensional array used to represent data in machine learning computations. TensorFlow allows users to define and manipulate tensors.
The vulnerability can lead to crashes in sanitizers and fuzzers when printing tensors. It may also be exploited by attackers to cause a denial of service or execute arbitrary code.
To fix the vulnerability, update your TensorFlow installation to the latest patched version (2.11.0 or later). Backported patches are available for TensorFlow 2.10.1, 2.9.3, and 2.8.4.
There are no specific workarounds provided for this vulnerability. It is recommended to update to the patched version of TensorFlow and follow secure coding practices.
References
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