### Description

https://github.com/apache/airflow/pull/17946 implements a `/robots.txt` endpoint to block search engines crawling Airflow - in the cases where it is (accidentally) exposed to the public Internet.

If we record any GET requests to that end-point we'd have a strong warning flag that the deployment is exposed, and could issue a warning in the UI, or even enable some kill-switch on the deployment. 

Some deployments are likely intentionally available and rely on auth mechanisms on the `login` endpoint, so there should be a config option to suppress the warnings.

An alternative approach would be to monitor for requests from specific user-agents used by crawlers for the same reasons

### Use case/motivation

People who accidentally expose airflow have a slightly higher chance of realising they've done so and tighten their security.

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/www/views.py
dag = dag.partial_subset(task_ids_or_regex=root, include_downstream=False, include_upstream=True)
        num_runs = request.args.get('num_runs', type=int)
        if num_runs is None:
            num_runs = conf.getint('webserver', 'default_dag_run_display_number')
        try:
            base_date = timezone.parse(request.args["base_date"])
        except (KeyError, ValueError):
            base_date = dag.get_latest_execution_date() or timezone.utcnow()
        with create_session() as session:
            dag_runs = (
                session.query(DagRun)
                .filter(DagRun.dag_id == dag.dag_id, DagRun.execution_date <= base_date)
                .order_by(DagRun.execution_date.desc())
                .limit(num_runs)
                .all()
            )
            dag_runs.reverse()
            encoded_runs = [wwwutils.encode_dag_run(dr) for dr in dag_runs]
            dag_run_dates = {dr.execution_date: alchemy_to_dict(dr) for dr in dag_runs}
            min_date = min(dag_run_dates, default=None)
            tis = dag.get_task_instances(start_date=min_date, end_date=base_date, session=session)
            data = {
                'groups': task_group_to_tree(dag.task_group, dag, dag_runs, tis),
                'dag_runs': encoded_runs,
            }
        
        return htmlsafe_json_dumps(data, separators=(',', ':'))
    @expose('/robots.txt')
    @action_logging
    def robots(self):