Heap buffer overflow in `SparseTensorToCSRSparseMatrix`
### Impact
An attacker can trigger a denial of service via a `CHECK`-fail in converting sparse tensors to CSR Sparse matrices:
```python
import tensorflow as tf
import numpy as np
from tensorflow.python.ops.linalg.sparse import sparse_csr_matrix_ops
indices_array = np.array([[0, 0]])
value_array = np.array([0.0], dtype=np.float32)
dense_shape = [0, 0]
st = tf.SparseTensor(indices_array, value_array, dense_shape)
values_tensor = sparse_csr_matrix_ops.sparse_tensor_to_csr_sparse_matrix(
st.indices, st.values, st.dense_shape)
```
This is because the implementation
https://github.com/tensorflow/tensorflow/blob/800346f2c03a27e182dd4fba48295f65e7790739/tensorflow/core/kernels/sparse/kernels.cc#L66 does a double redirection to access an element of an array allocated on the heap:
```cc
csr_row_ptr(indices(i, 0) + 1) += 1;
```
If the value at `indices(i, 0)` is such that `indices(i, 0) + 1` is outside the bounds of `csr_row_ptr`, this results in writing outside of bounds of heap allocated data.
### Patches
We have patched the issue in GitHub commit 1e922ccdf6bf46a3a52641f99fd47d54c1decd13
https://github.com/tensorflow/tensorflow/commit/1e922ccdf6bf46a3a52641f99fd47d54c1decd13.
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 Yakun Zhang and Ying Wang of Baidu X-Team.