ja4-platform/shared/clickhouse/06_ml_tables.sql

-- =============================================================================
-- 06_ml_tables.sql — ML detection results tables
-- Source: bot_detector/deploy_views.sql sections 6-6b + deploy_schema.sql items 11-12
--
-- Optimisations de performance :
--   - ml_detected_anomalies : PARTITION BY date → élagage de partitions sur
--     les requêtes temporelles (WHERE detected_at >= now() - INTERVAL N DAY)
--   - INDEX idx_detected_at (minmax) → skip des granules hors plage temporelle
--   - INDEX idx_threat_level (set) → skip pour les filtres par niveau de menace
--   - ml_all_scores : PARTITION BY date + INDEX identiques
-- =============================================================================

-- -----------------------------------------------------------------------------
-- ml_detected_anomalies — anomaly detections above threat threshold
--
-- Déduplication : ReplacingMergeTree(detected_at) sur ORDER BY (src_ip)
--   → conserve la détection la plus récente par IP.
-- PARTITION BY : élagage journalier (les requêtes 24h/7j ignorent les vieilles
--   partitions sans lire aucune donnée).
-- INDEX idx_detected_at : skip des granules 8192 lignes hors de la plage
--   temporelle demandée (minmax = min/max par granule).
-- INDEX idx_threat_level : skip pour countIf(threat_level = 'CRITICAL') etc.
-- -----------------------------------------------------------------------------
CREATE TABLE IF NOT EXISTS ja4_processing.ml_detected_anomalies
(
    detected_at DateTime, src_ip IPv6, ja4 String, host String, bot_name String,
    browser_family LowCardinality(String) DEFAULT '',
    anomaly_score Float32, threat_level String, model_name String, recurrence UInt32,
    asn_number String, asn_org String, asn_detail String, asn_domain String,
    country_code String, asn_label String,
    hits UInt64, hit_velocity Float32, fuzzing_index Float32, post_ratio Float32,
    port_exhaustion_ratio Float32, max_keepalives UInt32, orphan_ratio Float32,
    tcp_jitter_variance Float32, tcp_shared_count UInt32, true_window_size UInt64,
    window_mss_ratio Float32, alpn_http_mismatch UInt8, is_alpn_missing UInt8,
    sni_host_mismatch UInt8, header_count UInt16, has_accept_language UInt8,
    has_cookie UInt8, has_referer UInt8, modern_browser_score UInt8, has_sec_ch_ua UInt8,
    is_headless UInt8,
    ua_ch_mismatch UInt8, header_order_shared_count UInt32, ip_id_zero_ratio Float32,
    request_size_variance Float32, multiplexing_efficiency Float32,
    mss_mobile_mismatch UInt8, correlated UInt8, reason String,
    asset_ratio Float32, direct_access_ratio Float32, is_ua_rotating UInt8,
    distinct_ja4_count UInt32, src_port_density Float32, ja4_asn_concentration Float32,
    ja4_country_concentration Float32, is_rare_ja4 UInt8, header_order_confidence Float32,
    distinct_header_orders UInt32, temporal_entropy Float32, path_diversity_ratio Float32,
    url_depth_variance Float32, anomalous_payload_ratio Float32,
    -- v11 additions
    campaign_id       Int32   DEFAULT -1,
    raw_anomaly_score Float32 DEFAULT 0,
    -- Anubis enrichment (deploy_schema.sql item 11)
    anubis_bot_name     LowCardinality(String) DEFAULT '',
    anubis_bot_action   LowCardinality(String) DEFAULT '',
    anubis_bot_category LowCardinality(String) DEFAULT '',

    -- Index de saut : skip des granules hors plage temporelle
    INDEX idx_detected_at  detected_at  TYPE minmax        GRANULARITY 4,
    -- Index de saut : skip pour les filtres sur threat_level (CRITICAL/HIGH/...)
    INDEX idx_threat_level threat_level TYPE set(8)         GRANULARITY 4,
    -- Index de saut : skip pour les filtres bot_name != ''
    INDEX idx_bot_name     bot_name     TYPE bloom_filter() GRANULARITY 4
)
ENGINE = ReplacingMergeTree(detected_at)
PARTITION BY toYYYYMMDD(detected_at)
ORDER BY (src_ip)
TTL detected_at + INTERVAL 30 DAY
SETTINGS
    index_granularity  = 8192,
    ttl_only_drop_parts = 1;  -- supprime la partition entière à expiration (plus efficace)


-- -----------------------------------------------------------------------------
-- ml_all_scores — all classifications (no threshold, for observability)
--
-- PARTITION BY date : TTL de 3 jours → les partitions expirées sont supprimées
--   entièrement sans avoir à lire chaque granule (ttl_only_drop_parts).
-- INDEX idx_detected_at : idem ml_detected_anomalies.
-- -----------------------------------------------------------------------------
CREATE TABLE IF NOT EXISTS ja4_processing.ml_all_scores
(
    detected_at       DateTime,
    window_start      DateTime,
    src_ip            IPv6,
    ja4               String,
    host              String,
    bot_name          String,
    browser_family    LowCardinality(String) DEFAULT '',
    anomaly_score     Float32,
    raw_anomaly_score Float32,
    threat_level      String,
    model_name        String,
    correlated        UInt8,
    asn_number        String,
    asn_org           String,
    country_code      String,
    asn_label         String,
    hits              UInt64,
    hit_velocity      Float32,
    fuzzing_index     Float32,
    post_ratio        Float32,
    campaign_id       Int32,
    -- Autoencoder reconstruction error (parallel scorer)
    ae_recon_error    Float32 DEFAULT 0,
    -- XGBoost supervised probability (third voice)
    xgb_prob          Float32 DEFAULT 0,
    -- Anubis enrichment (deploy_schema.sql item 12)
    anubis_bot_name     LowCardinality(String) DEFAULT '',
    anubis_bot_action   LowCardinality(String) DEFAULT '',
    anubis_bot_category LowCardinality(String) DEFAULT '',

    INDEX idx_detected_at  detected_at  TYPE minmax GRANULARITY 4,
    INDEX idx_threat_level threat_level TYPE set(8) GRANULARITY 4
)
ENGINE = ReplacingMergeTree(detected_at)
PARTITION BY toYYYYMMDD(window_start)
ORDER BY (window_start, src_ip, ja4, host, model_name)
TTL window_start + INTERVAL 3 DAY
SETTINGS
    index_granularity  = 8192,
    ttl_only_drop_parts = 1;


-- -----------------------------------------------------------------------------
-- view_ip_recurrence — récurrence des détections par IP
--
-- Agrège ml_detected_anomalies (ORDER BY src_ip) pour obtenir le profil
-- de récurrence de chaque IP détectée.
--
-- Optimisation : avec PARTITION BY toYYYYMMDD(detected_at) (ajouté en P1),
-- chaque GROUP BY src_ip bénéficie de l'élagage de partitions si la vue est
-- filtrée par date en amont (les routes filtrent généralement sur 30 jours max).
-- Le ORDER BY (src_ip) garantit que le GROUP BY src_ip lit des données
-- contiguës en mémoire (co-localisation des lignes d'une même IP).
-- -----------------------------------------------------------------------------
CREATE OR REPLACE VIEW ja4_processing.view_ip_recurrence AS
SELECT
    src_ip,
    count()                              AS recurrence,
    min(detected_at)                     AS first_seen,
    max(detected_at)                     AS last_seen,
    max(anomaly_score)                   AS worst_score,
    argMax(threat_level, anomaly_score)  AS worst_threat_level,
    argMax(threat_level, anomaly_score)  AS worst_threat,
    argMax(ja4,          anomaly_score)  AS top_ja4,
    argMax(host,         hits)           AS top_host
FROM ja4_processing.ml_detected_anomalies
WHERE detected_at >= now() - INTERVAL 30 DAY
GROUP BY src_ip;