Commit Graph

21 Commits

Author SHA1 Message Date
9a48fb9d29 feat: LEGITIMATE_BROWSER classification from JA4 + behavioral consistency
Add browser legitimacy classification (A9) to the bot detection pipeline:

- New features: is_known_browser (binary) and browser_consistency_score [0..5]
  combining 5 signals: JA4 browser match, modern_browser_score, Accept-Language,
  cookies, Sec-Fetch-* presence
- Post-scoring: sessions with known browser JA4 + consistency >= 4/5 + NORMAL/LOW
  threat level are reclassified as LEGITIMATE_BROWSER
- Spoofing detection: inconsistent behavior (known JA4 but low consistency) stays
  in normal anomaly scoring — prevents evasion via JA4 spoofing
- XGBoost treats LEGITIMATE_BROWSER as non-threat (negative label)
- ClickHouse: browser_family column added to ml_detected_anomalies and ml_all_scores
- Dashboard: browser_family filter/sort on detections and scores endpoints,
  legitimate_browsers count and browser_stats in overview
- 6 new unit tests covering classification threshold, spoofing, exclusion logic

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 15:46:22 +02:00
7d09c614c3 feat: browser JA4 detection, Anubis bot rules, worldwide ASN data
- Add generate_browser_ja4.py: 1,186 browser JA4 fingerprints from FoxIO + ja4db.com
  covering 11 families (Chromium, Firefox, Safari, Edge, Tor, Opera, Vivaldi...)
- Rewrite generate_bot_ip.py: Anubis YAML rules (Google, Bing, Apple, DuckDuck,
  OpenAI, Perplexity bots) + Tor exit nodes + cloud scanner IPs (3,555 entries)
- Rewrite generate_asn_data.py: worldwide iptoasn.com data (78,049 ASNs, 714K CIDRs)
- Add dict_browser_ja4 ClickHouse dictionary + browser_family in AI features views
- Add /api/browsers dashboard endpoint
- Fix CSV quoting for fields containing commas (User-Agent strings)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 15:27:37 +02:00
b6184e6529 feat: CSV generation scripts, API filter params, enriched CSV stubs
- scripts/generate_bot_ip.py: download Tor exit nodes + curate scanner IPs (1353 entries)
- scripts/generate_bot_ja4.py: 31 bot JA4 fingerprints across 16 families
- scripts/generate_asn_data.py: 38 ASNs + 96 IP-to-ASN prefixes
- scripts/update-csv-data.sh: master orchestrator with --install-stubs
- api.py: add asn_org/country_code/ja4/bot_name filters on detections+scores
- pages.py: add /network route
- csv-stubs: enriched with generated data (Tor nodes, scanner IPs, etc.)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 15:05:43 +02:00
c6ca352db9 feat(dashboard): add clickable drill-down to all data elements
Add navigation helpers (fmtASN, fmtCountry, fmtJA4, fmtBotName,
fmtThreatLink, fmtLabel) to base.html for SOC analyst drill-down.

Update all templates:
- overview.html: clickable table cells + ECharts click handlers for
  ASN, country, JA4, bot, and threat charts
- detections.html: URL param pre-filters, active filter bar with
  clear buttons, clickable ASN/country/JA4/threat in table
- scores.html: URL param pre-filters, clickable threat/JA4/country
- traffic.html: clickable JA4 and country columns
- ip_detail.html: clickable threat/JA4 in detections, clickable
  asn_org/country_code/asn_label in AI features grid
- network.html: click handlers on ASN treemap and country sunburst,
  fmtJA4Full/fmtLabel/fmtBotName/fmtASN in tables
- features.html: scatter plot click navigates to /ip/{ip}

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 14:58:48 +02:00
f448dcb4b0 fix(rpm): standardize systemd scriptlets and unit installation paths
- Add BuildRequires: systemd-rpm-macros to sentinel and correlator specs
- Replace manual systemctl calls with %systemd_post, %systemd_preun,
  %systemd_postun_with_restart macros (handles daemon-reload, stop/disable,
  try-restart on upgrade correctly and is a no-op in containers)
- ja4sentinel.spec: use %{_unitdir} macro instead of hardcoded path
  (/usr/lib/systemd/system); remove cross-service /var/run/logcorrelator
  from %files and %post (owned by logcorrelator package, not sentinel)
- logcorrelator.spec: move unit from /etc/systemd/system (admin namespace)
  to %{_unitdir} (/usr/lib/systemd/system) — correct packaging location;
  move user/group creation from %post to %pre so file ownership is valid
  during RPM install phase; add Requires(pre): shadow-utils; fix bare
  directory entries in %files with %dir macro; add version fallback macro
  so spec is buildable without --define version
- test-rpm.sh: auto-build RPM via Dockerfile.package if dist/rpm/ is
  empty; update service file path check to /usr/lib/systemd/system/

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 10:49:21 +02:00
f7ee5e63f8 fix(docker): add g++ for isotree build, add dashboard Dockerfile.tests
- bot-detector Dockerfile + Dockerfile.tests: install g++ for isotree C++ extension
- dashboard Dockerfile.tests: new smoke test (verify FastAPI app loads)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 08:08:13 +02:00
b735bab5a5 feat(dashboard): rebuild SOC dashboard + fix ClickHouse SQL
Complete rewrite of the SOC dashboard using FastAPI + Jinja2 + htmx + Chart.js + Tailwind CSS.
Replaces the old React/Vite frontend with server-rendered templates.

Dashboard pages:
- Overview: KPIs, timeline chart, threat distribution, top IPs
- Detections: paginated/filterable anomaly table
- Scores: ml_all_scores with AE error & XGB prob columns
- Traffic: HTTP logs with method/host filters
- IP Investigation: full deep-dive (scores, features, HTTP logs, classify)
- Classification: SOC feedback form + history
- Features: AI + thesis feature stats
- Models: scoring stats + model metadata

API: 9 JSON endpoints with parameterized queries, sort whitelists

SQL fixes:
- 05_aggregation_tables: add deduplicate_merge_projection_mode
- 11_views: fix nested aggregate (argMax inside sum)
- 12_thesis_features: remove invalid 'let' bindings, fix groupArrayIf type

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 03:21:05 +02:00
8d58f2b932 feat(bot-detector): add XGBoost supervised third voice (#10)
Triple-voice ensemble architecture:
- EIF (non-supervisé, anomalies zero-day)
- Autoencoder (non-supervisé, corrélations non-linéaires)
- XGBoost (supervisé, patterns connus + feedback SOC)

XGBoost implementation:
- Trained on historical ml_all_scores labels (NORMAL=0, HIGH/CRITICAL/DENY/KNOWN=1)
- Weekly retraining (XGB_RETRAIN_INTERVAL_H=168), min 100 labels required
- Score = predict_proba, combined via meta-learner: (1-β)*(EIF+AE) + β*xgb_prob
- Configurable: XGB_WEIGHT (β=0.20), XGB_MIN_LABELS, XGB_RETRAIN_INTERVAL_HOURS
- Graceful fallback: if xgboost unavailable or labels insufficient, EIF+AE only
- ClickHouse: xgb_prob column added to ml_all_scores
- Tests: 4 new tests (availability, train/predict, meta-learner, save/load)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 02:45:57 +02:00
57cf6c3828 feat(bot-detector): add parallel Autoencoder scorer (#9)
- TrafficAutoEncoder class: symmetric AE (n→64→32→16→32→64→n) with BatchNorm+ReLU
- Trained alongside EIF on human_baseline, saved/loaded with model versioning
- Score = per-sample MSE reconstruction error, combined with EIF via AE_WEIGHT (α=0.30)
- AE latent space (16-dim) used for HDBSCAN clustering instead of raw features
- Configurable: AE_WEIGHT, AE_EPOCHS, AE_LATENT_DIM, AE_LEARNING_RATE
- Graceful fallback: if torch unavailable or AE fails, EIF-only scoring continues
- ClickHouse: ae_recon_error column added to ml_all_scores
- Tests: 5 new tests (AE train/score, encode latent, state dict save/load, weight combination)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 02:40:39 +02:00
f6e2d3c0ca feat(bot-detector): implement 8 state-of-art improvements
- 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>
2026-04-08 02:31:26 +02:00
3ae8c7d9c9 feat(bot-detector): upgrade to state-of-the-art detection pipeline
- Fix UnboundLocalError on global _consecutive_failures/_service_healthy
- Add SQL identifier validation for DB names at startup
- Replace Z-score drift detection with KS test (scipy.stats.ks_2samp)
- Replace DBSCAN with HDBSCAN (adaptive clustering, no epsilon needed)
- Fix NaN→0 blanket imputation with per-feature median/sentinel strategy
- Add 80/20 temporal train/validation split with offline metrics logging
- Integrate thesis §5 features from view_thesis_features_1h:
  path_transition_entropy, cadence_cv, burst/pause ratios,
  host_diversity, host_sweep_speed, host_coverage_uniformity,
  ja4_drift_ratio (Complet model only)
- Add SOC feedback loop: read classifications from audit_logs,
  reclassify FP IPs as human, exclude TP IPs from baseline
- Update dependencies: clickhouse-connect 0.8.12, scikit-learn 1.6.1,
  pandas 2.2.3, shap 0.47.2, add scipy>=1.14, hdbscan>=0.8.38

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-08 02:09:18 +02:00
51b8eb57a8 feat: port v14 schema fixes, migration, MV verifier, thesis from ja4/
deploy_views.sql (v13 → v14):
- CRITICAL: ml_detected_anomalies ORDER BY (src_ip) → (src_ip, ja4, host, model_name)
  ReplacingMergeTree was collapsing all detections to 1 row per IP on merge
- Add PARTITION BY toDate + ttl_only_drop_parts on all 4 data tables
- ml_all_scores TTL 3d → 7d; ml_detected_anomalies TTL 30d → 7d
- agg_host_ip_ja4_1h + agg_header_fingerprint_1h: add partition + TTL 7d
- view_ip_recurrence: add WHERE detected_at >= now() - 7 DAY (was full scan)
- Remove dead views: summary/timeseries/threat_dist/variability
- Add view_dashboard_entities (fixes HTTP 500 in clustering/incidents/fingerprints)
- Add view_dashboard_user_agents (fixes HTTP 500 in fingerprints/metrics)
- Add view_ai_features_24h (enables ENABLE_MULTIWINDOW in bot_detector)
- Mark max_requests_per_sec as DEPRECATED (always 0)

New files:
- correlator/sql/migrations/01_ttl_adjustments.sql: ALTER TABLE migration
- tests/integration/verify_mvs.py: MV pipeline verification assertions
- docs/THESIS_HTTP_Traffic_Detection.md: detection techniques thesis

All DB references use ja4_processing/ja4_logs (no mabase_prod).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 23:51:56 +02:00
ecceb04174 perf(clickhouse): P3 — view_ip_recurrence avec filtre TTL + supprimer FINAL
view_ip_recurrence :
  Ajout de WHERE detected_at >= now() - INTERVAL 30 DAY
  → Avec PARTITION BY (P1), ClickHouse élagage les partitions hors de cette
    plage avant même de lire les données. La vue ne scanne que les partitions
    actives (au lieu des 30 partitions journalières complètes).
  → ORDER BY (src_ip) garantit que le GROUP BY src_ip lit des données
    contiguës (aucune réorganisation mémoire).

rotation.py — supprimer FINAL sur ml_detected_anomalies :
  FINAL force une déduplication complète du ReplacingMergeTree en mémoire
  (équivalent à un DISTINCT sur toute la table) — une des opérations les plus
  coûteuses dans ClickHouse.
  Fix : remplacer le sous-SELECT FINAL par view_ip_recurrence (déjà aggrégée
  par src_ip, retourne recurrence directement sans FINAL).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 22:33:29 +02:00
2bfb4b7282 perf(dashboard): P2 — remplacer replaceRegexpAll dans les WHERE par IPv4MappedToIPv6
Problème : 8 clauses WHERE appliquaient une fonction sur la colonne src_ip :
  WHERE replaceRegexpAll(toString(src_ip), '^::ffff:', '') = %(ip)s
→ ClickHouse ne peut pas utiliser l'index de tri ou les skipping indexes
  quand une fonction est appliquée à la colonne filtrée.

Fix : transformer l'INPUT (le paramètre) plutôt que la colonne :
  WHERE src_ip = IPv4MappedToIPv6(toIPv4(%(ip)s))
→ src_ip reste intact → ClickHouse utilise les indexes (P1) et la
  projection proj_by_ip (P1) pour ces requêtes.

Fichiers modifiés :
  investigation_summary.py — 6 WHERE (ml_detected_anomalies, agg_host_ip_ja4_1h,
                              view_form_bruteforce_detected, view_host_ip_ja4_rotation,
                              view_ip_recurrence)
  ml_features.py           — 1 WHERE (view_ai_features_1h)
  rotation.py              — 1 WHERE (agg_host_ip_ja4_1h)

Note : les 27 autres occurrences de replaceRegexpAll dans les SELECT sont des
transformations d'affichage (IPv6→IPv4 pour l'UI) et ne bloquent pas les indexes.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 22:31:57 +02:00
14323f7b05 perf(clickhouse): P10 — créer les 4 vues métier manquantes + corriger préfixes DB
Bug de production : view_form_bruteforce_detected, view_host_ip_ja4_rotation,
view_dashboard_entities, view_dashboard_user_agents étaient référencées dans
13 endpoints du dashboard mais n'existaient nulle part dans le schéma.
Tous ces endpoints retournaient HTTP 500 en production.

shared/clickhouse/11_views.sql (nouveau) :

  view_form_bruteforce_detected
    Source : agg_host_ip_ja4_1h (24h)
    Logique : GROUP BY (src_ip, host) HAVING count_post >= 10
    Usage   : bruteforce.py (3 endpoints), investigation_summary.py

  view_host_ip_ja4_rotation
    Source : agg_host_ip_ja4_1h (24h)
    Logique : uniqExact(ja4) par src_ip, HAVING >= 2 (rotation de fingerprint)
    Usage   : rotation.py (3 endpoints), investigation_summary.py

  view_dashboard_entities
    Source : http_logs (7 jours), UNION ALL 5 branches (ip/ja4/country/asn/host)
    Colonnes : entity_type, entity_value, src_ip, ja4, host, log_date,
               client_headers Array(String), asns Array, countries Array,
               user_agents Array
    Usage   : entities.py (5 endpoints), clustering.py

  view_dashboard_user_agents
    Source : http_logs (7 jours), GROUP BY (src_ip, ja4, hour)
    Colonnes : src_ip, ja4, hour, log_date, user_agents Array(String), requests
    Usage   : variability.py (4 endpoints), fingerprints.py (5 endpoints)
              attributes.py (2 endpoints)

deploy_schema.sh : ajout de 10_perf_indexes.sql et 11_views.sql dans la liste

routes/variability.py + fingerprints.py :
  Correction de 9 requêtes utilisant view_dashboard_user_agents sans préfixe
  de base de données → remplacé par {settings.CLICKHOUSE_DB_PROCESSING}.view_*

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 22:30:09 +02:00
3b8c06b86d docs: add Doxygen comments to mod_reqin_log.c
- File header: French multi-line description block
- 7 section banners in French (/* ====== Section ====== */ format):
  Configuration du serveur, Buffer dynamique, Sérialisation JSON,
  Gestionnaires de directives, Socket Unix, Journalisation, Hooks Apache
- 26 @brief/@param/@return blocks on every function:
  server config, dynbuf_*, JSON helpers, cmd_set_* handlers,
  socket helpers (try_connect/ensure_connected/write_to_socket),
  log_request, Apache hooks (post_read_request, child_init, etc.)
- No logic changes (1033 → 1268 lines, comments only)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 21:35:19 +02:00
3dfeba860b docs: add standardized comments to all services (Python, Go, Bash)
- Add docs/commenting-standard.md defining per-language comment standards
  (Go godoc, Python PEP-257, C Doxygen, Bash header blocks, SQL banners)

- services/dashboard: 100% docstring coverage (100/100 functions)
  - All FastAPI route handlers, helpers, classes, and models documented
  - Language: French (project convention)

- services/bot-detector: 100% docstring coverage (53/53 symbols)
  - bot_detector.py: 14 functions + module docstring
  - anubis/fetch_rules.py: 9 functions

- shared/python/ja4_common: full docstrings on ClickHouseClient (7 methods)
  and ClickHouseSettings class

- services/correlator: 24 godoc comments added across 6 Go files
  - correlation_service.go: 10 private helpers
  - unixsocket/source.go: 6 parsing/socket helpers
  - correlated_log.go: 4 field extraction helpers
  - orchestrator.go, logger.go, main.go: 4 comments

- services/correlator/scripts/audit-architecture.sh: standardized header block

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 21:32:29 +02:00
a985661369 fix: build correlator RPM on Rocky Linux instead of Debian
Replace golang:1.24 (Debian) builder with rockylinux:9 + dnf golang.
All three RPM packages (sentinel, correlator, mod-reqin-log) now build
entirely on Rocky Linux Docker images, ensuring native ABI compatibility.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 20:52:27 +02:00
9f3e0621e5 feat: split ClickHouse into dual configurable databases (ja4_logs / ja4_processing)
Architecture:
- ja4_logs: raw log ingestion (http_logs_raw, http_logs, mv_http_logs)
- ja4_processing: analytics, aggregation, ML, dictionaries, audit

Configuration (env vars):
- CLICKHOUSE_DB_LOGS (default: ja4_logs)
- CLICKHOUSE_DB_PROCESSING (default: ja4_processing)

Changes:
- SQL migrations (10 files): all mabase_prod refs → ja4_logs or ja4_processing
  with correct cross-database references (MVs, views, dicts)
- deploy_schema.sh: substitutes DB names from env vars at deploy time
- Python shared settings: added CLICKHOUSE_DB_LOGS + CLICKHOUSE_DB_PROCESSING
- Dashboard routes (19 files): replaced ~80 hardcoded mabase_prod refs
  with settings.CLICKHOUSE_DB_LOGS / settings.CLICKHOUSE_DB_PROCESSING
- Bot-detector: DB → CLICKHOUSE_DB_PROCESSING, fetch_rules.py configurable
- Correlator: DSN example updated to ja4_logs
- Docker-compose + .env files: new env vars with defaults
- All documentation updated (14 markdown files)

All tests pass: sentinel 10/10, correlator 67.1%, bot-detector 11, dashboard 20, ja4_common 18

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 19:10:35 +02:00
b6391afbeb refactor: replace hardcoded mabase_prod DB prefix with configurable settings
Replace all hardcoded 'mabase_prod.' table prefixes in dashboard route
SQL queries with configurable database names from settings:

- http_logs, http_logs_raw → settings.CLICKHOUSE_DB_LOGS
- All other tables → settings.CLICKHOUSE_DB_PROCESSING

Also qualify previously unqualified table references (bare FROM/JOIN
table_name) with the appropriate database prefix for consistency.

Each route file now imports 'from ..config import settings' and uses
f-strings with {settings.CLICKHOUSE_DB_PROCESSING} or
{settings.CLICKHOUSE_DB_LOGS} for database-qualified table names.

Files updated: analysis, attributes, audit, botnets, bruteforce,
clustering, detections, entities, fingerprints, header_fingerprint,
heatmap, incidents, investigation_summary, metrics, ml_features,
rotation, search, tcp_spoofing, variability (19 files).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 19:03:05 +02:00
d469e39da7 feat: ja4-platform monorepo — 5 services unified, tests & RPM builds standardized
Services:
- ja4sentinel: TLS/JA4 fingerprint capture daemon (Go, libpcap)
- logcorrelator: JA4 log correlation engine (Go, ClickHouse)
- mod_reqin_log: Apache module (C, JSON request logging)
- bot_detector: ML bot detection pipeline (Python)
- dashboard: FastAPI/Streamlit analytics UI (Python)

Shared libraries:
- shared/go/ja4common: logger, config, shutdown, ipfilter (Go module)
- shared/python/ja4_common: ClickHouseClient, ClickHouseSettings (Python package)
- shared/clickhouse/: canonical SQL migrations (10 files)

Build & packaging:
- Unified 3-stage Dockerfile.package for Go RPMs (el8/el9/el10)
- go.work workspace linking sentinel, correlator, ja4common
- Makefile with test-all, build-all, rpm-* targets

Fixes applied:
- go.work: 1.21 → 1.24.6 (required by sentinel)
- correlator Dockerfiles: golang:1.21 → golang:1.24
- replace directives in go.mod for ja4common local path
- pyproject.toml: setuptools.backends → setuptools.build_meta
- Removed static libpcap linking (unavailable on Rocky 9)
- Fixed data races in output/writers_test.go (sync.Mutex + atomic.Int32)
- Rewrote corrupted test files (logger_test.go × 2)

Test coverage:
- correlator: 67.1% total (unixsocket 80.5%, config 91.7%, app 83.3%, multi 87.7%, stdout 100%)
- sentinel: all 10 packages pass (api, capture, config, fingerprint, ipfilter, logging, output, tlsparse)

Documentation:
- README.md + docs/ (architecture, development, 5 services, shared libs, DB schema & migrations)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-07 16:42:59 +02:00