chore: import upstream snapshot with attribution

tensorflow/security/advisory/tfsa-2021-006.md

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+## TFSA-2021-006: Division by zero in `Conv3D`
+
+### CVE Number
+CVE-2021-29517
+
+### Impact
+A malicious user could trigger a division by 0 in `Conv3D` implementation:
+
+```python
+import tensorflow as tf
+
+input_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
+filter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
+
+tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 56, 56, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 23, 1])
+```
+
+The [implementation](https://github.com/tensorflow/tensorflow/blob/42033603003965bffac51ae171b51801565e002d/tensorflow/core/kernels/conv_ops_3d.cc#L143-L145) does a modulo operation based on user controlled input:
+
+```cc
+  const int64 out_depth = filter.dim_size(4);
+  OP_REQUIRES(context, in_depth % filter_depth == 0, ...);
+```
+
+Thus, when `filter` has a 0 as the fifth element, this results in a division by 0.
+
+Additionally, if the shape of the two tensors is not valid, an Eigen assertion
+can be triggered, resulting in a program crash:
+
+```python
+import tensorflow as tf
+
+input_tensor = tf.constant([], shape=[2, 2, 2, 2, 0], dtype=tf.float32)
+filter_tensor = tf.constant([], shape=[0, 0, 2, 6, 2], dtype=tf.float32)
+
+tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 39, 34, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])
+```
+
+The shape of the two tensors must follow the constraints specified in the [op
+description](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Conv3D).
+
+### Patches
+We have patched the issue in GitHub commit
+[799f835a3dfa00a4d852defa29b15841eea9d64f](https://github.com/tensorflow/tensorflow/commit/799f835a3dfa00a4d852defa29b15841eea9d64f).
+
+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.