First published: Fri Nov 05 2021(Updated: )
### Impact The [implementation](https://github.com/tensorflow/tensorflow/blob/e71b86d47f8bc1816bf54d7bddc4170e47670b97/tensorflow/core/kernels/split_v_op.cc#L49-L205) of `SplitV` can trigger a segfault is an attacker supplies negative arguments: ```python import tensorflow as tf tf.raw_ops.SplitV( value=tf.constant([]), size_splits=[-1, -2] ,axis=0, num_split=2) ``` This occurs whenever `size_splits` contains more than one value and at least one value is negative. ### Patches We have patched the issue in GitHub commit [25d622ffc432acc736b14ca3904177579e733cc6](https://github.com/tensorflow/tensorflow/commit/25d622ffc432acc736b14ca3904177579e733cc6). The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
Credit: security-advisories@github.com security-advisories@github.com
Affected Software | Affected Version | How to fix |
---|---|---|
>=2.4.0<2.4.4 | ||
>=2.6.0<2.6.1 | ||
=2.7.0-rc0 | ||
=2.7.0-rc1 | ||
pip/tensorflow-gpu | <2.4.4 | 2.4.4 |
pip/tensorflow-gpu | >=2.5.0<2.5.2 | 2.5.2 |
pip/tensorflow-gpu | >=2.6.0<2.6.1 | 2.6.1 |
pip/tensorflow-cpu | <2.4.4 | 2.4.4 |
pip/tensorflow-cpu | >=2.5.0<2.5.2 | 2.5.2 |
pip/tensorflow-cpu | >=2.6.0<2.6.1 | 2.6.1 |
pip/tensorflow | <2.4.4 | 2.4.4 |
pip/tensorflow | >=2.5.0<2.5.2 | 2.5.2 |
pip/tensorflow | >=2.6.0<2.6.1 | 2.6.1 |
TensorFlow Keras | >=2.4.0<2.4.4 | |
TensorFlow Keras | >=2.6.0<2.6.1 | |
TensorFlow Keras | =2.7.0-rc0 | |
TensorFlow Keras | =2.7.0-rc1 |
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CVE-2021-41222 is considered to be a high severity vulnerability due to the potential for segmentation faults when negative arguments are supplied.
To fix CVE-2021-41222, upgrade to TensorFlow versions 2.4.4, 2.5.2, or 2.6.1 which address this issue.
CVE-2021-41222 affects TensorFlow versions 2.4.0 to 2.4.4, 2.6.0 to 2.6.1, and 2.7.0-rc0 and 2.7.0-rc1.
CVE-2021-41222 can enable denial of service attacks through segmentation faults caused by improperly handled negative arguments.
Yes, CVE-2021-41222 is a vulnerability present in both TensorFlow CPU and GPU packages.