A use of uninitialized value vulnerability in Tensorflow
### Impact
TensorFlow's Grappler optimizer has a use of unitialized variable
https://github.com/tensorflow/tensorflow/blob/3457a2b122e50b4d44ceaaed5a663d635e5c22df/tensorflow/core/grappler/optimizers/auto_parallel.cc#L155-L164:
```cc
const NodeDef* dequeue_node;
for (const auto& train_node : train_nodes) {
if (IsDequeueOp(*train_node)) {
dequeue_node = train_node;
break;
}
}
if (dequeue_node) {
...
}
```
If the `train_nodes` vector (obtained from the saved model that gets optimized) does not contain a `Dequeue` node, then `dequeue_node` is left unitialized.
### Patches
We have patched the issue in GitHub commit 68867bf01239d9e1048f98cbad185bf4761bedd3
https://github.com/tensorflow/tensorflow/commit/68867bf01239d9e1048f98cbad185bf4761bedd3.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 Qian Feng from Baidu Security Team.