First published: Fri May 20 2022(Updated: )
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.LoadAndRemapMatrix does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `initializing_values` is a vector but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Credit: security-advisories@github.com
Affected Software | Affected Version | How to fix |
---|---|---|
Google TensorFlow | <2.6.4 | |
Google TensorFlow | >=2.7.0<2.7.2 | |
Google TensorFlow | =2.7.0-rc0 | |
Google TensorFlow | =2.7.0-rc1 | |
Google TensorFlow | =2.8.0 | |
Google TensorFlow | =2.8.0-rc0 | |
Google TensorFlow | =2.8.0-rc1 | |
Google TensorFlow | =2.9.0-rc0 | |
Google TensorFlow | =2.9.0-rc1 |
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CVE-2022-29199 has a severity rating that indicates a potential denial of service vulnerability in TensorFlow.
To fix CVE-2022-29199, upgrade TensorFlow to version 2.9.0 or later, or to 2.8.1, 2.7.2, or 2.6.4.
CVE-2022-29199 affects TensorFlow versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4.
The vulnerability in CVE-2022-29199 is found in the `tf.raw_ops.LoadAndRemapMatrix` implementation.
CVE-2022-29199 primarily poses a risk of denial of service, but it does not specifically indicate potential data loss.