Segfault in `simplifyBroadcast` in Tensorflow

Impact

The [simplifyBroadcast function in the MLIR-TFRT infrastructure in TensorFlow](https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/mlir/tfrt/jit/transforms/tf_cpurt_symbolic_shape_optimization.cc#L149-L205) is vulnerable to a segfault (hence, denial of service), if called with scalar shapes.

```cc

size_t maxRank = 0;

for (auto shape : llvm::enumerate(shapes)) {

auto found_shape = analysis.dimensionsForShapeTensor(shape.value());

if (!found_shape) return {};

shapes_found.push_back(*found_shape);

maxRank = std::max(maxRank, found_shape->size());

}

SmallVector<const ShapeComponentAnalysis::SymbolicDimension*>

joined_dimensions(maxRank);

`

If all shapes are scalar, then maxRank is 0, so we build an empty SmallVector.

Patches

We have patched the issue in GitHub commit [35f0fabb4c178253a964d7aabdbb15c6a398b69a](https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a).

The fix will be included in TensorFlow 2.8.0. This is the only affected version.

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.