Vulnerability: Heap buffer overflow in `FractionalAvgPoolGrad` ### Impact
The implementation of `tf.raw_ops.FractionalAvgPoolGrad` is vulnerable to a heap buffer overflow:
  
```python
import tensorflow as tf

orig_input_tensor_shape = tf.constant([1, 3, 2, 3], shape=[4], dtype=tf.int64)
out_backprop = tf.constant([2], shape=[1, 1, 1, 1], dtype=tf.int64)
row_pooling_sequence = tf.constant([1], shape=[1], dtype=tf.int64)
col_pooling_sequence = tf.constant([1], shape=[1], dtype=tf.int64)


tf.raw_ops.FractionalAvgPoolGrad(
  orig_input_tensor_shape=orig_input_tensor_shape, out_backprop=out_backprop,
  row_pooling_sequence=row_pooling_sequence,
  col_pooling_sequence=col_pooling_sequence, overlapping=False)
```

The [implementation](https://github.com/tensorflow/tensorflow/blob/dcba796a28364d6d7f003f6fe733d82726dda713/tensorflow/core/kernels/fractional_avg_pool_op.cc#L216) fails to validate that the pooling sequence arguments have enough elements as required by the `out_backprop` tensor shape.

### Patches
We have patched the issue in GitHub commit [12c727cee857fa19be717f336943d95fca4ffe4f](https://github.com/tensorflow/tensorflow/commit/12c727cee857fa19be717f336943d95fca4ffe4f).

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.
Vulnerability ID: GHSA-6f89-8j54-29xf
CWE: CWE-119
Severity score: 2.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-05-21
File: tensorflow/core/kernels/fractional_avg_pool_op.cc
Commit message: Validate inputs of `FractionalAvgPoolGrad`.

PiperOrigin-RevId: 372420640
Change-Id: Icc583928e6cdc3062e12498e4d2337a8fe3da016
Commit author: Mihai Maruseac

Vulnerable version (before fix):
 class FractionalAvgPoolGradOp : public OpKernel {     const int64 out_cols = out_backprop.dim_size(2);     const int64 out_depth = out_backprop.dim_size(3);      auto row_seq_tensor_flat = row_seq_tensor.flat<int64>();     auto col_seq_tensor_flat = col_seq_tensor.flat<int64>();     auto orig_input_tensor_shape_flat = orig_input_tensor_shape.flat<int64>();

Fixed version (after fix):
 class FractionalAvgPoolGradOp : public OpKernel {     const int64 out_cols = out_backprop.dim_size(2);     const int64 out_depth = out_backprop.dim_size(3);      OP_REQUIRES(context, row_seq_tensor.NumElements() > out_rows,                 errors::InvalidArgument("Given out_backprop shape ",                                         out_backprop.shape().DebugString(),                                         ", row_seq_tensor must have at least ",                                         out_rows + 1, " elements, but got ",                                         row_seq_tensor.NumElements()));     OP_REQUIRES(context, col_seq_tensor.NumElements() > out_cols,                 errors::InvalidArgument("Given out_backprop shape ",                                         out_backprop.shape().DebugString(),                                         ", col_seq_tensor must have at least ",                                         out_cols + 1, " elements, but got ",                                         col_seq_tensor.NumElements()));      auto row_seq_tensor_flat = row_seq_tensor.flat<int64>();     auto col_seq_tensor_flat = col_seq_tensor.flat<int64>();     auto orig_input_tensor_shape_flat = orig_input_tensor_shape.flat<int64>();

Patch:
patch: @@ -250,6 +250,19 @@ class FractionalAvgPoolGradOp : public OpKernel {
     const int64 out_cols = out_backprop.dim_size(2);
     const int64 out_depth = out_backprop.dim_size(3);
 
+    OP_REQUIRES(context, row_seq_tensor.NumElements() > out_rows,
+                errors::InvalidArgument("Given out_backprop shape ",
+                                        out_backprop.shape().DebugString(),
+                                        ", row_seq_tensor must have at least ",
+                                        out_rows + 1, " elements, but got ",
+                                        row_seq_tensor.NumElements()));
+    OP_REQUIRES(context, col_seq_tensor.NumElements() > out_cols,
+                errors::InvalidArgument("Given out_backprop shape ",
+                                        out_backprop.shape().DebugString(),
+                                        ", col_seq_tensor must have at least ",
+                                        out_cols + 1, " elements, but got ",
+                                        col_seq_tensor.NumElements()));
+
     auto row_seq_tensor_flat = row_seq_tensor.flat<int64>();
     auto col_seq_tensor_flat = col_seq_tensor.flat<int64>();
     auto orig_input_tensor_shape_flat = orig_input_tensor_shape.flat<int64>();
path: tensorflow/core/kernels/fractional_avg_pool_op.cc