chore: import upstream snapshot with attribution

tensorflow/security/advisory/tfsa-2021-153.md

@@ -0,0 +1,53 @@
+## TFSA-2021-153: Heap OOB in nested `tf.map_fn` with `RaggedTensor`s
+
+### CVE Number
+CVE-2021-37679
+
+### Impact
+It is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However,
+if the input tensor is a `RaggedTensor` and there is no function signature
+provided, code assumes the output is a fully specified tensor and fills output
+buffer with uninitialized contents from the heap:
+
+```python
+import tensorflow as tf
+x = tf.ragged.constant([[1,2,3], [4,5], [6]])
+t = tf.map_fn(lambda r: tf.map_fn(lambda y: r, r), x)
+z = tf.ragged.constant([[[1,2,3],[1,2,3],[1,2,3]],[[4,5],[4,5]],[[6]]])
+```
+
+The `t` and `z` outputs should be identical, however this is not the case. The
+last row of `t` contains data from the heap which can be used to leak other
+memory information.
+
+The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The
+[implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190)
+does not check that all inner shapes match and this results in the additional
+dimensions in the above example.
+
+The same implementation can result in data loss, if input tensor is tweaked:
+
+```python
+import tensorflow as tf
+x = tf.ragged.constant([[1,2], [3,4,5], [6]])
+t = tf.map_fn(lambda r: tf.map_fn(lambda y: r, r), x)
+```
+
+Here, the output tensor will only have 2 elements for each inner dimension.
+
+### Patches
+We have patched the issue in GitHub commit
+[4e2565483d0ffcadc719bd44893fb7f609bb5f12](https://github.com/tensorflow/tensorflow/commit/4e2565483d0ffcadc719bd44893fb7f609bb5f12).
+
+The fix will be included in TensorFlow 2.6.0. We will also cherrypick this
+commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 Haris Sahovic.