Vulnerability: Heap OOB in `UpperBound` and `LowerBound` ### Impact
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`.

### Patches
We have patched the issue in GitHub commit [42459e4273c2e47a3232cc16c4f4fff3b3a35c38](https://github.com/tensorflow/tensorflow/commit/42459e4273c2e47a3232cc16c4f4fff3b3a35c38).
  
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 members of the Aivul Team from Qihoo 360.
Vulnerability ID: GHSA-9697-98pf-4rw7
CWE: CWE-125
Severity score: 5.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-08-25
File: tensorflow/core/kernels/searchsorted_op.cc
Commit message: Prevent CHECK-fail/heap OOB in UpperBound and LowerBound

PiperOrigin-RevId: 387738073
Change-Id: Iee74de95ddad18440d052a75a5a1cb67544f490a
Commit author: Mihai Maruseac

Vulnerable version (before fix):
 class UpperBoundOp : public OpKernel {     const Tensor& sorted_inputs_t = ctx->input(0);     const Tensor& values_t = ctx->input(1);      // must have same batch dim_size for both     OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0),                 Status(error::INVALID_ARGUMENT, class LowerBoundOp : public OpKernel {     const Tensor& sorted_inputs_t = ctx->input(0);     const Tensor& values_t = ctx->input(1);      // must have same batch dim_size for both     OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0),                 Status(error::INVALID_ARGUMENT,

Fixed version (after fix):
 class UpperBoundOp : public OpKernel {     const Tensor& sorted_inputs_t = ctx->input(0);     const Tensor& values_t = ctx->input(1);      // inputs must be at least a matrix     OP_REQUIRES(         ctx, sorted_inputs_t.shape().dims() >= 2,         errors::InvalidArgument("sorted input argument must be a matrix"));     // must have same batch dim_size for both     OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0),                 Status(error::INVALID_ARGUMENT, class LowerBoundOp : public OpKernel {     const Tensor& sorted_inputs_t = ctx->input(0);     const Tensor& values_t = ctx->input(1);      // inputs must be at least a matrix     OP_REQUIRES(         ctx, sorted_inputs_t.shape().dims() >= 2,         errors::InvalidArgument("sorted input argument must be a matrix"));     // must have same batch dim_size for both     OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0),                 Status(error::INVALID_ARGUMENT,

Patch:
patch: @@ -86,6 +86,10 @@ class UpperBoundOp : public OpKernel {
     const Tensor& sorted_inputs_t = ctx->input(0);
     const Tensor& values_t = ctx->input(1);
 
+    // inputs must be at least a matrix
+    OP_REQUIRES(
+        ctx, sorted_inputs_t.shape().dims() >= 2,
+        errors::InvalidArgument("sorted input argument must be a matrix"));
     // must have same batch dim_size for both
     OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0),
                 Status(error::INVALID_ARGUMENT,
@@ -127,6 +131,10 @@ class LowerBoundOp : public OpKernel {
     const Tensor& sorted_inputs_t = ctx->input(0);
     const Tensor& values_t = ctx->input(1);
 
+    // inputs must be at least a matrix
+    OP_REQUIRES(
+        ctx, sorted_inputs_t.shape().dims() >= 2,
+        errors::InvalidArgument("sorted input argument must be a matrix"));
     // must have same batch dim_size for both
     OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0),
                 Status(error::INVALID_ARGUMENT,
path: tensorflow/core/kernels/searchsorted_op.cc