GHSA-c545-c4f9-rf6v

### Impact TFLite's [`expand_dims.cc`](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/expand_dims.cc#L36-L50) contains a vulnerability which allows reading one element outside of bounds of heap allocated data: ```cc if (axis < 0) { axis = input_dims.size + 1 + axis; } TF_LITE_ENSURE(context, axis <= input_dims.size); TfLiteIntArray* output_dims = TfLiteIntArrayCreate(input_dims.size + 1); for (int i = 0; i < output_dims->size; ++i) { if (i < axis) { output_dims->data[i] = input_dims.data[i]; } else if (i == axis) { output_dims->data[i] = 1; } else { output_dims->data[i] = input_dims.data[i - 1]; } } ``` If `axis` is a large negative value (e.g., `-100000`), then after the first `if` it would still be negative. The check following the `if` statement will pass and the `for` loop would read one element before the start of `input_dims.data` (when `i = 0`). ### Patches We have patched the issue in GitHub commit [d94ffe08a65400f898241c0374e9edc6fa8ed257](https://github.com/tensorflow/tensorflow/commit/d94ffe08a65400f898241c0374e9edc6fa8ed257). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 of Baidu Security.