Vulnerability: CHECK-fail due to integer overflow ### Impact
An attacker can trigger a denial of service via a `CHECK`-fail in  caused by an integer overflow in constructing a new tensor shape:

```python
import tensorflow as tf

input_layer = 2**60-1
sparse_data = tf.raw_ops.SparseSplit(
    split_dim=1, 
    indices=[(0, 0), (0, 1), (0, 2), 
    (4, 3), (5, 0), (5, 1)],
    values=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
    shape=(input_layer, input_layer),
    num_split=2,
    name=None
    )
```
  
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/0908c2f2397c099338b901b067f6495a5b96760b/tensorflow/core/kernels/sparse_split_op.cc#L66-L70) builds a dense shape without checking that the dimensions would not result in overflow:

```cc
sparse::SparseTensor sparse_tensor;
OP_REQUIRES_OK(context,
               sparse::SparseTensor::Create(
                 input_indices, input_values,
                 TensorShape(input_shape.vec<int64>()), &sparse_tensor));
```

The [`TensorShape` constructor](https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when [`InitDims`](https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status.
                    
```cc               
template <class Shape>
TensorShapeBase<Shape>::TensorShapeBase(gtl::ArraySlice<int64> dim_sizes) {
  set_tag(REP16);
  set_data_type(DT_INVALID);
  TF_CHECK_OK(InitDims(dim_sizes));
}
```

In our scenario, this occurs when adding a dimension from the argument results in overflow:

```cc
template <class Shape>
Status TensorShapeBase<Shape>::InitDims(gtl::ArraySlice<int64> dim_sizes) {
  ...
  Status status = Status::OK();
  for (int64 s : dim_sizes) {
    status.Update(AddDimWithStatus(internal::SubtleMustCopy(s)));
    if (!status.ok()) {
      return status;
    }
  }
}

template <class Shape>
Status TensorShapeBase<Shape>::AddDimWithStatus(int64 size) {
  ...
  int64 new_num_elements;
  if (kIsPartial && (num_elements() < 0 || size < 0)) {
    new_num_elements = -1;
  } else {
    new_num_elements = MultiplyWithoutOverflow(num_elements(), size);
    if (TF_PREDICT_FALSE(new_num_elements < 0)) {
        return errors::Internal("Encountered overflow when multiplying ",
                                num_elements(), " with ", size,
                                ", result: ", new_num_elements);
      }
  }
  ...
}
```

This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows.

### Patches
We have patched the issue in GitHub commit [4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60](https://github.com/tensorflow/tensorflow/commit/4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60).

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 researchers from University of Virginia and University of California, Santa Barbara.
Vulnerability ID: GHSA-xvjm-fvxx-q3hv
CWE: CWE-190
Severity score: 2.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-05-21
File: tensorflow/core/kernels/sparse_split_op.cc
Commit message: Prevent overflow in sparse op

PiperOrigin-RevId: 372442006
Change-Id: I60fe31cd7e56fb3501e97c63500caf902ddeee96
Commit author: Mihai Maruseac

Vulnerable version (before fix):
 class SparseSplitOp : public OpKernel {                                         input_shape.vec<int64>()(axis),                                         "), got ", num_split_));      sparse::SparseTensor sparse_tensor;     OP_REQUIRES_OK(context,                    sparse::SparseTensor::Create(                        input_indices, input_values,                        TensorShape(input_shape.vec<int64>()), &sparse_tensor));      std::vector<sparse::SparseTensor> outputs;     OP_REQUIRES_OK(context, sparse::SparseTensor::Split<T>(

Fixed version (after fix):
 class SparseSplitOp : public OpKernel {                                         input_shape.vec<int64>()(axis),                                         "), got ", num_split_));      // Prevent overflow by constructing the dense shape separately     TensorShape dense_shape;     const auto input_shape_flat = input_shape.flat<int64>();     for (int i = 0; i < input_shape.NumElements(); i++) {       OP_REQUIRES_OK(context,                      dense_shape.AddDimWithStatus(input_shape_flat(i)));     }      sparse::SparseTensor sparse_tensor;     OP_REQUIRES_OK(context,                    sparse::SparseTensor::Create(input_indices, input_values,                                                 dense_shape, &sparse_tensor));      std::vector<sparse::SparseTensor> outputs;     OP_REQUIRES_OK(context, sparse::SparseTensor::Split<T>(

Patch:
patch: @@ -63,11 +63,18 @@ class SparseSplitOp : public OpKernel {
                                         input_shape.vec<int64>()(axis),
                                         "), got ", num_split_));
 
+    // Prevent overflow by constructing the dense shape separately
+    TensorShape dense_shape;
+    const auto input_shape_flat = input_shape.flat<int64>();
+    for (int i = 0; i < input_shape.NumElements(); i++) {
+      OP_REQUIRES_OK(context,
+                     dense_shape.AddDimWithStatus(input_shape_flat(i)));
+    }
+
     sparse::SparseTensor sparse_tensor;
     OP_REQUIRES_OK(context,
-                   sparse::SparseTensor::Create(
-                       input_indices, input_values,
-                       TensorShape(input_shape.vec<int64>()), &sparse_tensor));
+                   sparse::SparseTensor::Create(input_indices, input_values,
+                                                dense_shape, &sparse_tensor));
 
     std::vector<sparse::SparseTensor> outputs;
     OP_REQUIRES_OK(context, sparse::SparseTensor::Split<T>(
path: tensorflow/core/kernels/sparse_split_op.cc