chore: import upstream snapshot with attribution

tensorflow/security/advisory/tfsa-2021-020.md

@@ -0,0 +1,59 @@
+## TFSA-2021-020: `CHECK`-fail in `tf.raw_ops.EncodePng`
+
+### CVE Number
+CVE-2021-29531
+
+### Impact
+An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty
+input tensor as the pixel data:
+
+```python
+import tensorflow as tf
+
+image = tf.zeros([0, 0, 3])
+image = tf.cast(image, dtype=tf.uint8)
+tf.raw_ops.EncodePng(image=image)
+```
+
+This is because the
+[implementation](https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60)
+only validates that the total number of pixels in the image does not overflow.
+Thus, an attacker can send an empty matrix for encoding. However, if the tensor
+is empty, then the associated buffer is `nullptr`. Hence, when [calling
+`png::WriteImageToBuffer`](https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93),
+the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then
+triggers the `CHECK_NOTNULL` in the [first line of
+`png::WriteImageToBuffer`](https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349).
+
+```cc
+template <typename T>
+bool WriteImageToBuffer(
+    const void* image, int width, int height, int row_bytes, int num_channels,
+    int channel_bits, int compression, T* png_string,
+    const std::vector<std::pair<std::string, std::string> >* metadata) {
+  CHECK_NOTNULL(image);
+  ...
+}
+```
+
+Since `image` is null, this results in `abort` being called after printing the
+stacktrace. Effectively, this allows an attacker to mount a denial of service
+attack.
+
+### Patches
+We have patched the issue in GitHub commit
+[26eb323554ffccd173e8a79a8c05c15b685ae4d1](https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1).
+
+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.