Vulnerability: Division by 0 in `Reverse` ### Impact
An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.Reverse`:

```python
import tensorflow as tf

tensor_input = tf.constant([], shape=[0, 1, 1], dtype=tf.int32)
dims = tf.constant([False, True, False], shape=[3], dtype=tf.bool)

tf.raw_ops.Reverse(tensor=tensor_input, dims=dims)
``` 
    
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/36229ea9e9451dac14a8b1f4711c435a1d84a594/tensorflow/core/kernels/reverse_op.cc#L75-L76) performs a division based on the first dimension of the tensor argument:
    
```cc
const int64 N = input.dim_size(0);
const int64 cost_per_unit = input.NumElements() / N;
```

Since this is controlled by the user, an attacker can trigger a denial of service.

### Patches
We have patched the issue in GitHub commit [4071d8e2f6c45c1955a811fee757ca2adbe462c1](https://github.com/tensorflow/tensorflow/commit/4071d8e2f6c45c1955a811fee757ca2adbe462c1).

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-fxqh-cfjm-fp93
CWE: CWE-369
Severity score: 2.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-05-21
File: tensorflow/core/kernels/reverse_op.cc
Commit message: Fix FPE issue with `tf.raw_ops.Reverse`.

PiperOrigin-RevId: 371176973
Change-Id: Ic6d483bfc95313ec2299c2d1c956cfe96c96626c
Commit author: Amit Patankar

Vulnerable version (before fix):
 class ReverseOp : public OpKernel {    void Compute(OpKernelContext* context) override {     const Tensor& input = context->input(0);     const Tensor& dims = context->input(1);      if (TensorShapeUtils::IsScalar(input.shape())) {

Fixed version (after fix):
 class ReverseOp : public OpKernel {    void Compute(OpKernelContext* context) override {     const Tensor& input = context->input(0);     // If input is provided, check to make sure the first dimension is valid.     if (input.dims() > 0) {       OP_REQUIRES(           context, input.dim_size(0) != 0,           errors::InvalidArgument("Invalid input first dimension. Found 0."));     }     const Tensor& dims = context->input(1);      if (TensorShapeUtils::IsScalar(input.shape())) {

Patch:
patch: @@ -155,6 +155,12 @@ class ReverseOp : public OpKernel {
 
   void Compute(OpKernelContext* context) override {
     const Tensor& input = context->input(0);
+    // If input is provided, check to make sure the first dimension is valid.
+    if (input.dims() > 0) {
+      OP_REQUIRES(
+          context, input.dim_size(0) != 0,
+          errors::InvalidArgument("Invalid input first dimension. Found 0."));
+    }
     const Tensor& dims = context->input(1);
 
     if (TensorShapeUtils::IsScalar(input.shape())) {
path: tensorflow/core/kernels/reverse_op.cc