QID 981539

Security update has been released for tensorflow-gpu,tensorflow,tensorflow-cpu 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.

An attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.UpperBound`:

```python
import tensorflow as tf

tf.raw_ops.UpperBound(
sorted_input=[1,2,3],
values=tf.constant(value=[[0,0,0],[1,1,1],[2,2,2]],dtype=tf.int64),
out_type=tf.int64)
```

The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input` argument:

```cc
void Compute(OpKernelContext* ctx) override {
const Tensor& sorted_inputs_t = ctx->input(0);
// ...
OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0),
Status(error::INVALID_ARGUMENT,
"Leading dim_size of both tensors must match."));
// ...
if (output_t->dtype() == DT_INT32) {
OP_REQUIRES(ctx,
FastBoundsCheck(sorted_inputs_t.dim_size(1), ...));
// ...
}
```

As we access the first two dimensions of `sorted_inputs_t` tensor, it must have rank at least 2.

A similar issue occurs in `tf.raw_ops.LowerBound`.