CVE-2022-29192: TensorFlow GPU - Missing Input Validation in QuantizeAndDequantizeV4Grad Leading to Denial of Service
Summary
CVE-2022-29192: Missing validation crashes QuantizeAndDequantizeV4Grad. 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-2022-29192 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 widely used for various applications, including deep learning and neural networks. The 'tensorflow-gpu' package enables the use of GPU acceleration for TensorFlow operations, significantly improving performance for large-scale computations. However, like any complex software, it can have vulnerabilities that may affect its stability and security.
Vulnerability Detail
The vulnerability arises from the implementation of the 'tf.raw_ops.QuantizeAndDequantizeV4Grad' operation, which lacks proper validation for its input arguments. Specifically, the function assumes that 'input_min' and 'input_max' are scalars but does not validate this assumption. As a result, passing incorrect shapes for these parameters can lead to a CHECK-failure, which can be exploited to trigger a denial of service attack. This vulnerability can disrupt the normal functioning of applications relying on TensorFlow, potentially leading to service outages.
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
Currently, there are no specific workarounds mentioned for this vulnerability. However, avoiding the use of the 'QuantizeAndDequantizeV4Grad' operation with invalid input shapes can prevent triggering the denial of service.
Conclusion
In summary, CVE-2022-29192 is a significant vulnerability in the TensorFlow GPU package that can lead to denial of service due to missing input validation in a specific operation. It is crucial to update to the patched versions to mitigate this risk and ensure the stability of applications using TensorFlow.
See every vulnerability recorded for tensorflow-gpu →
FAQ
CVE-2022-29192 is a vulnerability in the TensorFlow GPU package that results from missing input validation in the QuantizeAndDequantizeV4Grad operation, potentially leading to denial of service.
You can use the Vulert playground at Vulert Scanner to check if your application is affected by this vulnerability without requiring any signup.
Exploiting this vulnerability can lead to a denial of service, causing disruptions in applications that rely on TensorFlow for processing.
The affected versions include TensorFlow 2.6.0 to 2.8.0. The vulnerability has been patched in versions 2.6.4, 2.7.2, 2.8.1, and 2.9.0.
Vulert monitors and alerts in real-time for open-source vulnerabilities in software using just the Pipfile.lock, helping developers stay informed about potential risks.
References
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