chore: import upstream snapshot with attribution

tensorflow/security/advisory/tfsa-2020-007.md

@@ -0,0 +1,52 @@
+## TFSA-2020-007: Null pointer dereference in TFLite
+
+### CVE Number
+CVE-2020-15209
+
+### Impact
+A crafted TFLite model can force a node to have as input a tensor backed by a
+`nullptr` buffer. This can be achieved by changing a buffer index in the
+flatbuffer serialization to convert a read-only tensor to a read-write one. The
+runtime assumes that these buffers are written to before a possible read, hence
+they are [initialized with
+`nullptr`](https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/core/subgraph.cc#L1224-L1227):
+```cc
+  TfLiteTensorReset(type, name, ConvertArrayToTfLiteIntArray(rank, dims),
+                    GetLegacyQuantization(quantization),
+                    /*buffer=*/nullptr, required_bytes, allocation_type,
+                    nullptr, is_variable, &tensor);
+```
+
+However, by changing the buffer index for a tensor and implicitly converting
+that tensor to be a read-write one, as there is nothing in the model that writes
+to it, we get a null pointer dereference.
+
+### Vulnerable Versions
+TensorFlow 1.15.0, 1.15.1, 1.15.2, 1.15.3, 2.0.0, 2.0.1, 2.0.2, 2.1.0, 2.1.1,
+2.2.0, 2.3.0.
+
+### Patches
+We have patched the issue in
+[0b5662bc](https://github.com/tensorflow/tensorflow/commit/0b5662bc) and will
+release patch releases for all versions between 1.15 and 2.3.
+
+We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or
+2.3.1.
+
+### Workarounds
+A potential workaround would be to add a custom `Verifier` to the model loading
+code to ensure that no operator reuses tensors as both inputs and outputs. Care
+should be taken to check all types of inputs (i.e., constant or variable tensors
+as well as optional tensors).
+
+### 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 discovered by members of the Aivul Team and is also
+discoverable through a variant analysis of [another
+vulnerability reported by members of the Aivul Team from Qihoo
+360](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2020-005.md).