Add GET /api/dashboard/bans/trend endpoint

Implement time-bucketed ban aggregation for dashboard trend charts:

- Add BanTrendBucket / BanTrendResponse Pydantic models and
  BUCKET_SECONDS / BUCKET_SIZE_LABEL / bucket_count helpers to ban.py
- Add ban_service.ban_trend(): queries fail2ban DB with SQL bucket
  grouping, fills zero-count buckets, respects origin filter
- Add GET /api/dashboard/bans/trend route in dashboard.py
- 20 new tests (10 service, 10 router); 480 total pass, 83% coverage
- ruff + mypy --strict clean

Docs/Tasks.md

@@ -226,7 +226,15 @@ Add the `TopCountriesBarChart` to the dashboard alongside the pie chart.
 
 ### Task 4.1 — Add a backend endpoint for time-series ban aggregation
 
-**Status:** `not started`
+**Status:** `done`
+
+Added `GET /api/dashboard/bans/trend`. New Pydantic models `BanTrendBucket` and
+`BanTrendResponse` (plus `BUCKET_SECONDS`, `BUCKET_SIZE_LABEL`, `bucket_count`
+helpers) in `ban.py`. Service function `ban_trend()` in `ban_service.py` groups
+`bans.timeofban` into equal-width buckets via SQL and fills empty buckets with
+zero so the frontend always receives a gap-free series. Route added to
+`dashboard.py`. 20 new tests (10 service, 10 router) — all pass, total suite
+480 passed, 83% coverage.
 
 The existing endpoints return flat lists or country-aggregated counts but **no time-bucketed series**. A dashboard trend chart needs data grouped into time buckets.