Bot-detector:
- B1.1: campaign_id and raw_anomaly_score now inserted into ml_detected_anomalies
- B1.4/B1.5: log_decision argument order fixed (cycle_id, name)
- B1.7: AE broadcast error — model now returns features list, scoring
uses model's features instead of current cycle's (prevents dim mismatch)
- B1.8: Anubis ALLOW bots now get bot_name from anubis_bot_name
Dashboard:
- C1.1: XSS in ip_detail.html — {{ ip | tojson }} instead of raw string
- C1.2: Stored XSS via innerHTML — added escapeHtml() helper, all user-facing
formatters (fmtIP, fmtASN, fmtCountry, fmtJA4, fmtBotName, fmtLabel) sanitized
- C2.1: status filter now correctly filters http_version column
- C2.2: heatmap toDayOfWeek() - 1 for 0-indexed JS days
SQL:
- B1.3: view_ip_recurrence worst_score uses max() not min() (0=normal, 1=anomal)
- B1.6: view_resource_cascade_1h joined into view_thesis_features_1h (§5.4)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- EIF: Extended Isolation Forest via isotree (fallback to sklearn IF)
- Benford's Law deviation feature on inter-request timing
- Lag-1 autocorrelation feature for cadence analysis
- Validation gate: reject model if val_anomaly_rate > 20%
- Feature pruning: remove variance < 1e-6 features before training
- Quantile drift: replace N(μ,σ) synthetic with quantile interpolation
- Thread safety: Lock for _service_healthy/_consecutive_failures
- Score normalization: inverted to [0,1] where 1=most anomalous
SQL: add lag1_autocorrelation + benford_deviation to view_thesis_features_1h
Tests: 10 new test functions covering all improvements
Integration: verify_mvs.py checks new thesis feature columns
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
