Segmentation faultin TensorFlow when converting a Python string to `tf.float16`

Impact

Converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode.

This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value.

Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions.

This can be easily reproduced by tf.constant("hello", tf.float16), if eager execution is enabled.

Patches

We have patched the vulnerability in GitHub commit [5ac1b9](https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf).

We are additionally releasing TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched.

TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected.

We encourage users to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.

For more information

Please consult [SECURITY.md](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.