Vulnerability: Floating point exception in `SparseDenseCwiseDiv` ### Impact
The implementation of `tf.raw_ops.SparseDenseCwiseDiv` is vulnerable to a division by 0 error:

```python
import tensorflow as tf
import numpy as np

tf.raw_ops.SparseDenseCwiseDiv( 
  sp_indices=np.array([[4]]),
  sp_values=np.array([-400]),
  sp_shape=np.array([647.]),
  dense=np.array([0]))
```

The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L56) uses a common class for all binary operations but fails to treat the division by 0 case separately.

### Patches
We have patched the issue in GitHub commit [d9204be9f49520cdaaeb2541d1dc5187b23f31d9](https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9).

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-hp4c-x6r7-6555
CWE: CWE-369
Severity score: 5.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-08-25
File: tensorflow/core/kernels/sparse_dense_binary_op_shared.cc
Commit message: Disallow division by zero FPE in tf.raw_ops.SparseDenseCwiseDiv

PiperOrigin-RevId: 383959809
Change-Id: Ibe88458bdf66a686c93e354b8255dec94285c560
Commit author: Laura Pak

Vulnerable version (before fix):
 class SparseDenseBinaryOpShared : public OpKernel {     OP_REQUIRES_OK(         ctx, ctx->allocate_temp(DataTypeToEnum<T>::value, TensorShape({nnz}),                                 &dense_gathered));      // Pulls relevant entries from the dense side, with reshape and broadcasting     // *of the dense side* taken into account.  Use a TensorRef to avoid blowing     // up memory. class SparseDenseBinaryOpShared : public OpKernel {           errors::InvalidArgument("Provided indices are out-of-bounds w.r.t. " \                                   "dense side with broadcasted shape"));       \       dense_gathered_flat(i) = rhs_ref.coeff(idx);                             \     }                                                                          \     break;                                                                     \   }

Fixed version (after fix):
 class SparseDenseBinaryOpShared : public OpKernel {     OP_REQUIRES_OK(         ctx, ctx->allocate_temp(DataTypeToEnum<T>::value, TensorShape({nnz}),                                 &dense_gathered));     bool op_is_div = false;     if (absl::StrContains(ctx->op_kernel().type_string_view(), "Div")) {       op_is_div = true;     }     // Pulls relevant entries from the dense side, with reshape and broadcasting     // *of the dense side* taken into account.  Use a TensorRef to avoid blowing     // up memory. class SparseDenseBinaryOpShared : public OpKernel {           errors::InvalidArgument("Provided indices are out-of-bounds w.r.t. " \                                   "dense side with broadcasted shape"));       \       dense_gathered_flat(i) = rhs_ref.coeff(idx);                             \       if (op_is_div) {                                                         \         OP_REQUIRES(ctx, dense_gathered_flat(i) != 0,                          \                     errors::InvalidArgument(                                   \                         "SparseDenseCwiseDiv cannot divide by zero,"           \                         "but input dense tensor contains zero "));             \       }                                                                        \     }                                                                          \     break;                                                                     \   }

Patch:
patch: @@ -114,7 +114,10 @@ class SparseDenseBinaryOpShared : public OpKernel {
     OP_REQUIRES_OK(
         ctx, ctx->allocate_temp(DataTypeToEnum<T>::value, TensorShape({nnz}),
                                 &dense_gathered));
-
+    bool op_is_div = false;
+    if (absl::StrContains(ctx->op_kernel().type_string_view(), "Div")) {
+      op_is_div = true;
+    }
     // Pulls relevant entries from the dense side, with reshape and broadcasting
     // *of the dense side* taken into account.  Use a TensorRef to avoid blowing
     // up memory.
@@ -143,6 +146,12 @@ class SparseDenseBinaryOpShared : public OpKernel {
           errors::InvalidArgument("Provided indices are out-of-bounds w.r.t. " \
                                   "dense side with broadcasted shape"));       \
       dense_gathered_flat(i) = rhs_ref.coeff(idx);                             \
+      if (op_is_div) {                                                         \
+        OP_REQUIRES(ctx, dense_gathered_flat(i) != 0,                          \
+                    errors::InvalidArgument(                                   \
+                        "SparseDenseCwiseDiv cannot divide by zero,"           \
+                        "but input dense tensor contains zero "));             \
+      }                                                                        \
     }                                                                          \
     break;                                                                     \
   }
path: tensorflow/core/kernels/sparse_dense_binary_op_shared.cc