CVE-2022-29202: Denial of service in TensorFlow due to lack of validation in `tf.ragged.constant`
Impact The implementation of tf.ragged.constant does not fully validate the input arguments. This results in a denial of service by consuming all available memory:
python import tensorflow as tf tf.ragged.constant(pylist=[],raggedrank=8968073515812833920) Patches We have patched the issue in GitHub commit bd4d5583ff9c8df26d47a23e508208844297310e.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.
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Attribution This vulnerability has been reported externally via a GitHub issue.
Other sources
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.ragged.constant does not fully validate the input arguments. This results in a denial of service by consuming all available memory. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Affected Software
Remediation
Patch Available
Event History
Frequently Asked Questions
What is the severity of CVE-2022-29202?
The CVE-2022-29202 vulnerability is classified as a denial of service issue.
How do I fix CVE-2022-29202?
To address CVE-2022-29202, update TensorFlow to a version later than 2.9.0.
Which TensorFlow versions are affected by CVE-2022-29202?
CVE-2022-29202 affects TensorFlow versions up to 2.9.0 inclusive.
What type of issue is CVE-2022-29202?
CVE-2022-29202 is a denial of service vulnerability resulting from inadequate input validation.
Is CVE-2022-29202 related to input validation?
Yes, CVE-2022-29202 is related to insufficient input validation in the implementation of tf.ragged.constant.