QID 982534

Security update has been released for tensorflow,tensorflow-cpu,tensorflow-gpu to fix the vulnerability.

Note: The preceding description block is extracted directly from the security advisory. Using automation, we have attempted to clean and format it as much as possible without introducing additional issues.

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=[0], values=[1,1,1,1,1], size=5, weights=[1,2,3,4], 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-L433):

```cc
for (int idx = 0; idx < num_values; ++idx) {
while (idx >= splits(batch_idx)) {
batch_idx++;
}
...
}
```

Before the `for` loop, `batch_idx` is set to 0. The user controls the `splits` array, making it contain only one element, 0. Thus, the code in the `while` loop would increment `batch_idx` and then try to read `splits(1)`, which is outside of bounds.