CVE-2022-29212: TensorFlow GPU Core Dump Vulnerability in TFLite Model Loading
Summary
CVE-2022-29212: Core dump when loading TFLite models with quantization in TensorFlow. Affects tensorflow-gpu across 3 version ranges.
< 2.6.4
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
Fixed in 2.6.4, 2.7.2 or 2.8.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow · Bitnami
- tensorflow · PyPI
The same CVE-2022-29212 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 developing and training machine learning models. The 'tensorflow-gpu' package enables the use of GPU acceleration for TensorFlow applications, enhancing performance for large-scale computations. However, certain TFLite models created with the TFLite model converter can lead to crashes when loaded in the TFLite interpreter due to a specific vulnerability related to quantization.
Vulnerability Detail
The vulnerability arises from the assumption in the TensorFlow code that the scale of values during quantization will always be less than 1. In cases where the scale exceeds 1, the code calls the QuantizeMultiplierSmallerThanOneExp function, which triggers a TFLITE_CHECK_LT assertion, leading to a core dump and process termination. This can result in application crashes and loss of functionality when attempting to load affected TFLite models.
How To Fix
Latest published version: 2.12.0 as of 22 Oct 2026
pip install --upgrade "tensorflow-gpu==2.12.0"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.
-
< 2.6.42.6.4pip install --upgrade "tensorflow-gpu==2.6.4" -
>= 2.7.0, < 2.7.22.7.2pip install --upgrade "tensorflow-gpu==2.7.2" -
>= 2.8.0, < 2.8.12.8.1pip install --upgrade "tensorflow-gpu==2.8.1"
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Workaround
As a temporary workaround, avoid using TFLite models that have been created with quantization settings that could lead to a scale greater than 1 until the package is updated to a fixed version.
Conclusion
The CVE-2022-29212 vulnerability in the TensorFlow GPU package poses a risk of application crashes when loading certain TFLite models with quantization. It is essential to update to the patched versions to mitigate this issue and ensure the stability of applications using TensorFlow.
See every vulnerability recorded for tensorflow-gpu →
FAQ
CVE-2022-29212 is a vulnerability in the TensorFlow GPU package that causes a core dump when loading certain TFLite models with quantization.
If your application uses affected TFLite models, it may crash when attempting to load them, leading to potential downtime and loss of functionality.
The vulnerability affects TensorFlow versions prior to 2.6.4, 2.7.2, 2.8.1, and 2.9.0.
You can use Vulert's playground at Vulert Scanner to check if your application is affected by this vulnerability without needing to sign up.
The CVSS score for this vulnerability is 5.5, indicating a moderate severity level.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
