CVE-2021-29606: TensorFlow Out-of-Bounds Read Vulnerability
Summary
CVE-2021-29606: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow across 5 version ranges.
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
< ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412
Fixed in 4 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-29606 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 end-to-end open source platform for machine learning. It provides a comprehensive ecosystem of tools, libraries, and community resources that enable researchers and developers to build and deploy machine learning models. TensorFlow is widely used in various domains, including computer vision, natural language processing, and robotics. This vulnerability affects the TensorFlow package, specifically the TFLite implementation of the Split_V function.
Vulnerability Detail
A specially crafted TFLite model can trigger an out-of-bounds read on the heap in the TFLite implementation of Split_V. The vulnerability arises when the axis_value parameter is not within the valid range of 0 to the number of dimensions of the input tensor. This leads to the SizeOfDimension function accessing data outside the bounds of the tensor shape array. An attacker could exploit this vulnerability to read sensitive information from the heap or cause a denial-of-service condition. The vulnerability has been assigned the identifier CVE-2021-29606.
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.
-
< 2.1.42.1.4pip install --upgrade "tensorflow==2.1.4" -
>= 2.2.0, < 2.2.32.2.3pip install --upgrade "tensorflow==2.2.3" -
>= 2.3.0, < 2.3.32.3.3pip install --upgrade "tensorflow==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow==2.4.2"
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Workaround
There is no known workaround for this vulnerability. It is recommended to apply the provided fix by upgrading TensorFlow to the patched versions.
Conclusion
The TensorFlow package is vulnerable to an out-of-bounds read vulnerability in the TFLite implementation of Split_V. Users are advised to upgrade to TensorFlow 2.5.0 or later, or apply the respective fixes for versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4. For further assistance or support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides a comprehensive set of tools and libraries for building and deploying machine learning models.
TFLite is a lightweight version of TensorFlow designed for mobile and embedded devices. It allows developers to run TensorFlow models on resource-constrained platforms.
An out-of-bounds read vulnerability occurs when a program accesses memory outside the bounds of a valid memory region. This can lead to information disclosure or a crash.
This vulnerability could allow an attacker to read sensitive information from the heap or cause a denial-of-service condition in applications that use TensorFlow.
No, only TensorFlow versions 2.1.4 and later are affected. Earlier versions are not impacted by this vulnerability.
References
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