## TFSA-2020-008: Data corruption due to dimension mismatch in TFLite

### CVE Number
CVE-2020-15208

### Impact
When determining the common dimension size of two tensors, [TFLite uses a
`DCHECK`](https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/types.h#L437-L442)
which is no-op outside of debug compilation modes:
```cc
// Get common shape dim, DCHECKing that they all agree.
inline int MatchingDim(const RuntimeShape& shape1, int index1,
                       const RuntimeShape& shape2, int index2) {
  TFLITE_DCHECK_EQ(shape1.Dims(index1), shape2.Dims(index2));
  return shape1.Dims(index1);
}
```

Since the function always returns the dimension of the first tensor, malicious
attackers can craft cases where this is larger than that of the second tensor.
In turn, this would result in reads/writes outside of bounds since the
interpreter will wrongly assume that there is enough data in both tensors.

### 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
[8ee24e7949a20](https://github.com/tensorflow/tensorflow/commit/8ee24e7949a20)
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.

### 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.