Heap out of bounds write in `RaggedBinCount`
### Impact
If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`
https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor, then an attacker can trigger a heap buffer overflow:
```python
import tensorflow as tf
tf.raw_ops.RaggedBincount(splits=[7,8], values= [5, 16, 51, 76, 29, 27, 54, 95],\
size= 59, weights= [0, 0, 0, 0, 0, 0, 0, 0],\
binary_output=False)
```
This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op
https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L446:
```cc
for (int idx = 0; idx < num_values; ++idx) {
while (idx >= splits(batch_idx)) {
batch_idx++;
}
...
if (bin < size) {
if (binary_output_) {
out(batch_idx - 1, bin) = T(1);
} else {
T value = (weights_size > 0) ? weights(idx) : T(1);
out(batch_idx - 1, bin) += value;
}
}
}
```
Before the `for` loop, `batch_idx` is set to 0. The attacker sets `splits(0)` to be 7, hence the `while` loop does not execute and `batch_idx` remains 0. This then results in writing to `out(-1, bin)`, which is before the heap allocated buffer for the output tensor.
### Patches
We have patched the issue in GitHub commit eebb96c2830d48597d055d247c0e9aebaea94cd5
https://github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are also affected.
### 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.