Missing validation during checkpoint loading

Impact

An attacker can trigger undefined behavior, integer overflows, segfaults and CHECK-fail crashes if they can change saved checkpoints from outside of TensorFlow.

This is because the checkpoints loading infrastructure is missing validation for invalid file formats.

Patches

We have patched the issue in GitHub commits [b619c6f865715ca3b15ef1842b5b95edbaa710ad](https://github.com/tensorflow/tensorflow/commit/b619c6f865715ca3b15ef1842b5b95edbaa710ad), [e8dc63704c88007ee4713076605c90188d66f3d2](https://github.com/tensorflow/tensorflow/commit/e8dc63704c88007ee4713076605c90188d66f3d2), [368af875869a204b4ac552b9ddda59f6a46a56ec](https://github.com/tensorflow/tensorflow/commit/368af875869a204b4ac552b9ddda59f6a46a56ec), and [abcced051cb1bd8fb05046ac3b6023a7ebcc4578](https://github.com/tensorflow/tensorflow/commit/abcced051cb1bd8fb05046ac3b6023a7ebcc4578).

These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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.