chore: import upstream snapshot with attribution

tensorflow/security/advisory/tfsa-2021-119.md

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+## TFSA-2021-119: Integer overflow due to conversion to unsigned
+
+### CVE Number
+CVE-2021-37645
+
+### Impact
+The implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to
+an integer overflow issue caused by converting a signed integer value to an
+unsigned one and then allocating memory based on this value.
+
+```python
+import tensorflow as tf
+
+tf.raw_ops.QuantizeAndDequantizeV4Grad(
+  gradients=[1.0,2.0],
+  input=[1.0,1.0],
+  input_min=[0.0],
+  input_max=[10.0],
+  axis=-100)
+```
+
+The
+[implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126)
+uses the `axis` value as the size argument to `absl::InlinedVector` constructor.
+But, the constructor uses an unsigned type for the argument, so the implicit
+conversion transforms the negative value to a large integer.
+
+### Patches
+We have patched the issue in GitHub commit
+[96f364a1ca3009f98980021c4b32be5fdcca33a1](https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1).
+
+The fix will be included in TensorFlow 2.6.0. We will also cherrypick this
+commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, 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.