- Fix loadScorerStatus: was spreading data.state + data.config (both
undefined); API returns flat object; now uses data directly
- Fix v-for to use filteredDetections (was using raw detections array,
breaking the Unacknowledged tab filter)
- Fix double-prefix URL bug: BASE already contains /turnstone, so
fetches to ${BASE}/turnstone/api/... doubled the prefix → returned
SPA HTML → silent JSON parse failure. Fixed all fetch URLs to use
${BASE}/api/... in SecurityAlertsView and DashboardView
- Add CybersecStatus interface to replace Record<string, unknown>
- Add scorer field to Detection interface; show 'cybersec' badge in
label cell when scorer !== 'anomaly'
- Add cybersecStatus.running to cybersec badge (pulse animation)
- Add ANOMALY / CYBERSEC stats rows side-by-side
- Add 'Run cybersec' button with cybersecTriggerLoading state and
runCybersec() function posting to /api/cybersec/run
- Rename 'Run scorer' → 'Run anomaly' for clarity
Closes: #11
Second-pass cybersec classifier using DeBERTa-v3-base-mnli (already
cached — no download required). Runs after each anomaly scoring pass on
entries flagged by the anomaly scorer or with pattern matches.
Architecture:
- app/services/cybersec.py: zero-shot-classification pipeline with 5
cybersec candidate labels (auth failure, privilege escalation, network
intrusion, malware, data exfiltration). Writes ml_score/ml_label/
ml_scored_at to log_entries; inserts high-confidence hits into
detections with scorer='cybersec'.
- app/tasks/cybersec_scorer.py: async background task (same shape as
anomaly_scorer.py).
- REST: GET/POST /turnstone/api/cybersec/status|run|detections.
GET /turnstone/api/anomaly/detections now accepts scorer= filter.
Schema: ml_score, ml_label, ml_scored_at added to log_entries; scorer
column added to detections (idempotent migrations + DDL for both SQLite
and Postgres).
UI: Security Alerts view gains Source dropdown (All / Anomaly / Cybersec)
and cybersec scorer status badge. Label dropdown split into optgroups.
Deployment: TURNSTONE_CYBERSEC_MODEL/DEVICE/THRESHOLD vars added to
.env.example, docker-compose.yml, docker-standalone.sh.
Tests: 10 new tests — no model, no eligible entries, scoring, detection
creation, normal label suppression, threshold filtering, pattern-tag
filtering, idempotency, list filtering, scorer column filter.
416/416 passing.
Closes: #9
- Add app/services/anomaly.py: batch scorer using HF text-classification
pipeline; rewrites anomaly_score/anomaly_label/anomaly_scored_at on
log_entries; inserts high-confidence hits into detections table
- Add app/tasks/anomaly_scorer.py: background task (same shape as
glean_scheduler); triggered after each glean cycle when
TURNSTONE_ANOMALY_MODEL is set
- DB schema: add anomaly_score/anomaly_label/anomaly_scored_at columns to
log_entries (idempotent ALTER TABLE migration); add detections table
- Wire scorer into scheduler_loop and glean_scheduler.run_once; no-op when
model env var is empty (safe to leave unconfigured)
- REST endpoints: GET/POST /api/anomaly/status, /api/anomaly/run,
GET /api/anomaly/detections, POST /api/anomaly/detections/{id}/acknowledge
- Reuses Hybrid-BERT label map from diagnose/classifier.py; works with any
HF text-classification model
- 12 new tests; 406/406 passing
Closes: #10
- Add app/db/ abstraction layer: Backend enum, DbConn wrapper,
dialect helper (q() for ? vs %s paramstyle), get_conn(), tenant_id()
- Auto-detect backend from DATABASE_URL; SQLite remains default when
unset — no config change for local deployments
- Add tenant_id column to all three logical DBs (main, context, incidents);
idempotent ALTER TABLE migration runs before schema scripts on existing DBs
- All INSERTs inject tenant_id; SELECTs use (tenant_id = ? OR tenant_id = '')
for backward compat with pre-namespacing rows
- Add docker-compose.yml with named volume turnstone_pgdata (survives rebuilds)
and optional external Postgres support via DATABASE_URL override
- Add scripts/migrate_sqlite_to_postgres.py — one-shot idempotent migration
for existing SQLite data; ON CONFLICT DO NOTHING for safe re-runs
- Fix SSH glean path in pipeline.py to use ensure_schema + get_conn
(was still using raw sqlite3.connect + old _SCHEMA without tenant_id)
- Fix FTS5 JOIN ambiguity: qualify repeat_count as f.repeat_count in search
- Update all tests to use ensure_*_schema fixtures; add row_factory where needed
- 394/394 tests passing
Closes: #42
Closes: #50
