Given the following code containing errors, provide Common Weakness Enumeration (CWE) identifiers and corresponding messages in JSON format. Each identified weakness should have a unique entry in the JSON array.
    Code: Status ShapeRefiner::InferShapesForFunctionSubNode(
    const Node* node, InferenceContext* outer_context) {
  TF_RETURN_IF_ERROR(AddNodeInternal(node, outer_context));
  InferenceContext* node_context = CHECK_NOTNULL(GetContext(node));

  if (StringPiece(node->type_string()) == kArgOp) {
    // Handle special node: function input.
    // Shapes for these nodes are provided in the outer inference
    // context.

    int index;
    TF_RETURN_IF_ERROR(GetNodeAttr(AttrSlice(node->def()), "index", &index));

    if (index < 0 || outer_context->num_inputs() <= index) {
      return errors::Internal(
          "Function instantiation included invalid input index: ", index,
          " not in [0, ", outer_context->num_inputs(), ").");
    }

    // TODO(b/134547156): TEMPORARY WORKAROUND. If input shape handle is not set
    // in outer context, set _Arg node output shape to unknown.
    if (outer_context->input(index).SameHandle(ShapeHandle())) {
      VLOG(1) << "Function instantiation has undefined input shape at "
              << "index: " << index << " in the outer inference context.";
      node_context->set_output(0, node_context->UnknownShape());
    } else {
      node_context->set_output(0, outer_context->input(index));
    }

    auto* resource = outer_context->input_handle_shapes_and_types(index);
    if (resource) {
      node_context->set_output_handle_shapes_and_types(0, *resource);
    }
  } else if (StringPiece(node->type_string()) == kRetvalOp) {
    // Handle special node: function output.
    // Shapes inferred for these nodes go into the outer inference
    // context.

    int index;
    TF_RETURN_IF_ERROR(GetNodeAttr(AttrSlice(node->def()), "index", &index));

    if (index < 0 || outer_context->num_outputs() <= index) {
      return errors::Internal(
          "Function instantiation included invalid output index: ", index,
          " not in [0, ", outer_context->num_outputs(), ").");
    }

    // outer_context outlives node_context, therefore we need to create
    // a new shape handle owned by outer_context instead.
    ShapeHandle handle;
    TensorShapeProto proto;
    node_context->ShapeHandleToProto(node_context->input(0), &proto);
    TF_RETURN_IF_ERROR(outer_context->MakeShapeFromShapeProto(proto, &handle));
    outer_context->set_output(index, handle);

    auto* resource = node_context->input_handle_shapes_and_types(0);
    if (resource) {
      outer_context->set_output_handle_shapes_and_types(index, *resource);
    }
  }

  return Status::OK();
} ; Sample JSON Format Confermily Expected output: "examples" => "cwe": "xxx"; "message": "xxx"
    
 'cwe': ['CWE-416', 'CWE-369'], 'message': 'Fix segmentation fault in shape inference logic.

When running shape functions, some functions (such as `MutableHashTableShape`)
produce extra output information in the form of a `ShapeAndType` struct.  The
shapes embedded in this struct are owned by an inference context that is
cleaned up almost immediately; if the upstream code attempts to access this
shape information, it can trigger a segfault.

`ShapeRefiner` is mitigating this for normal output shapes by cloning them
(and thus putting the newly created shape under ownership of an inference
context that will not die), but we were not doing the same for shapes and
types.  This commit fixes that by doing similar logic on output shapes and
types.

PiperOrigin-RevId: 384761124
Change-Id: I07c0c42d29dfbb55bfa13ec1f09ef825fb0a1a1d'