Add automatic cleanup of stale geolocation cache entries to prevent
unbounded database growth. Resolves the issue where unique IP addresses
accumulated indefinitely in the geo_cache table, degrading query performance.
## Changes
### Database Schema (Migration 3)
- Add 'last_seen' column to geo_cache table tracking last reference time
- Existing entries default to current timestamp
### Repository Layer (geo_cache_repo.py)
- Update upsert_entry() to set/refresh last_seen on insert/update
- Update upsert_neg_entry() to set/refresh last_seen on negative cache hits
- Update bulk_upsert_entries() to set/refresh last_seen in batch operations
- Add delete_stale_entries(db, cutoff_iso) -> int for purging old entries
### Background Task (geo_cache_cleanup.py)
- New APScheduler task that runs nightly (24-hour interval)
- Calculates cutoff as 90 days ago from current time (UTC)
- Deletes all entries with last_seen older than cutoff
- Logs operation results (info when deleted > 0, debug when 0 deleted)
- Configurable retention period via GEO_CACHE_RETENTION_DAYS constant
### Application Startup (startup.py)
- Register geo_cache_cleanup task in scheduler during app startup
- Placed after geo_cache_flush in task registration order
### Tests
- Add delete_stale_entries test cases covering:
* Removal of old entries beyond cutoff
* No deletion when all entries are recent
* Empty table edge case
- Update existing test fixtures to include last_seen column
- Add full test suite for cleanup task registration and execution
### Documentation
- Architekture.md: Document cleanup task, update schema/diagram
- Backend-Development.md: Add retention policy documentation
## Behavior
When an IP is accessed, its last_seen is refreshed. After 90 days of no
access, an IP is purged by the nightly cleanup. On next encounter, the IP
is re-resolved from MaxMind MMDB or ip-api.com (if configured).
This is acceptable because:
1. Stale geolocation data may become inaccurate over time
2. Re-resolution cost is minimal compared to unbounded storage growth
3. Active IPs maintain fresh data through their last_seen updates
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Replace non-atomic db.executescript() with explicit transaction control.
Wrap each migration's DDL statements and schema_migrations insert in a
single BEGIN IMMEDIATE ... COMMIT transaction to ensure atomicity.
Changes:
- Add _parse_migration_statements() to split migration scripts into
individual statements while handling comments and string literals
- Update _apply_migration() to wrap all statements in a single explicit
transaction with rollback on error
- Ensure _get_current_schema_version() uses execute() instead of
executescript()
- Add 9 new tests for migration atomicity and statement parsing
- Update Backend-Development.md with migration authoring guidelines
If a crash occurs between DDL execution and schema_migrations insert,
the next startup will re-apply the entire migration atomically,
preventing partial migrations and data corruption.
Test coverage: 98% on db.py (up from 55%)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- Store session tokens as one-way SHA256 hashes instead of plaintext
- Hash tokens on write (create_session) and on read (get_session, delete_session)
- Add migration to drop plaintext sessions table and recreate with token_hash column
- Update Session model: token field still contains raw token for signing
- Add test to verify tokens are hashed in database, not plaintext
- Update Architekture.md to document session token hashing
- Update Backend-Development.md with implementation pattern and best practices
Prevents direct session token hijacking if database file is exposed to attacker.
If plaintext DB was readable, sessions are invalidated by the migration anyway.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Add source=archive option for dashboard endpoints and history service; update Docs/Tasks.md; include archive branch for list_bans, bans_by_country, ban_trend, bans_by_jail; tests for archive paths.
- Add persistent geo_cache SQLite table (db.py)
- Rewrite geo_service: batch API (100 IPs/call), two-tier cache,
no caching of failed lookups so they are retried
- Pre-warm geo cache from DB on startup (main.py lifespan)
- Rewrite bans_by_country: SQL GROUP BY ip aggregation + lookup_batch
instead of 2000-row fetch + asyncio.gather individual calls
- Pre-warm geo cache after blocklist import (blocklist_service)
- Add 300ms debounce to useMapData hook to cancel stale requests
- Add perf benchmark asserting <2s for 10k bans
- Add seed_10k_bans.py script for manual perf testing
