### 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
x_axis_date=True,
            x_axis_format=LINECHART_X_AXIS_TICKFORMAT,
            height=chart_height,
            chart_attr=self.line_chart_attr,
        )
        y_points = defaultdict(list)
        x_points = defaultdict(list)
        cumulative_y = defaultdict(list)
        task_instances = dag.get_task_instances_before(base_date, num_runs, session=session)
        if task_instances:
            min_date = task_instances[0].execution_date
        else:
            min_date = timezone.utc_epoch()
        ti_fails = (
            session.query(TaskFail)
            .filter(
                TaskFail.dag_id == dag.dag_id,
                TaskFail.execution_date >= min_date,
                TaskFail.execution_date <= base_date,
                TaskFail.task_id.in_([t.task_id for t in dag.tasks]),
            )
            .all()
        )
        fails_totals = defaultdict(int)
        for failed_task_instance in ti_fails:
            dict_key = (
                failed_task_instance.dag_id,
                failed_task_instance.task_id,
                failed_task_instance.execution_date,
            )