Files
ja4-platform/shared/clickhouse/11_views.sql
toto b409a70970 fix(views): align SQL views with dashboard API expected columns
- view_form_bruteforce_detected: add post_count, distinct_paths, first_seen, last_seen
- view_host_ip_ja4_rotation: add host, distinct_ja4, ja4_list, window_start
- view_ip_recurrence: add worst_threat alias + top_ja4, top_host columns

All three views were missing columns referenced by /api/brute-force,
/api/ja4-rotation and /api/recurrence endpoints, causing 500 errors
on the Tactiques page.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-10 00:59:57 +02:00

233 lines
10 KiB
SQL

-- =============================================================================
-- 11_views.sql — Vues métier du dashboard
--
-- Ce fichier crée les vues référencées par le dashboard mais absentes du schéma
-- partagé. Ces vues agrègent les données de agg_host_ip_ja4_1h et http_logs
-- pour fournir des perspectives métier aux endpoints FastAPI.
--
-- Vues créées :
-- view_form_bruteforce_detected — IPs/hôtes avec fort volume de requêtes POST
-- view_host_ip_ja4_rotation — IPs changeant de fingerprint JA4 (évasion)
-- view_dashboard_entities — Pivot IP/JA4/pays/ASN/host pour investigation
-- view_dashboard_user_agents — User-Agents agrégés par IP/JA4/heure
-- view_dashboard_summary — Métriques globales 24h (si pas déjà créée)
-- =============================================================================
-- -----------------------------------------------------------------------------
-- view_form_bruteforce_detected
--
-- Détecte les IPs effectuant des attaques par force brute sur des formulaires :
-- - Volume élevé de requêtes POST vers un hôte donné (≥ 10 POST/heure)
-- - Fenêtre glissante 24h depuis agg_host_ip_ja4_1h
--
-- Colonnes :
-- src_ip, host, ja4, hits, post_count, distinct_paths, first_seen, last_seen
-- -----------------------------------------------------------------------------
CREATE OR REPLACE VIEW ja4_processing.view_form_bruteforce_detected AS
SELECT
src_ip,
host,
argMax(ja4, ja4_hits) AS ja4,
sum(ja4_hits) AS hits,
sum(ja4_posts) AS post_count,
-- Alias de compatibilité pour les anciens appels
sum(ja4_posts) AS query_params_count,
uniqExact(ja4) AS distinct_paths,
min(w_min) AS first_seen,
max(w_max) AS last_seen
FROM (
SELECT
src_ip, host, ja4,
sum(hits) AS ja4_hits,
sum(count_post) AS ja4_posts,
min(window_start) AS w_min,
max(window_start) AS w_max
FROM ja4_processing.agg_host_ip_ja4_1h
WHERE window_start >= now() - INTERVAL 24 HOUR
GROUP BY src_ip, host, ja4
) sub
GROUP BY src_ip, host
HAVING post_count >= 10;
-- -----------------------------------------------------------------------------
-- view_host_ip_ja4_rotation
--
-- Détecte les IPs qui changent de fingerprint JA4 (rotation de TLS ClientHello)
-- — indicateur d'évasion de détection par les outils de bot.
--
-- Colonnes :
-- src_ip, host, distinct_ja4, distinct_ja4_count, ja4_list,
-- total_hits, window_start, first_seen, last_seen
-- -----------------------------------------------------------------------------
CREATE OR REPLACE VIEW ja4_processing.view_host_ip_ja4_rotation AS
SELECT
src_ip,
argMax(host, ja4_hits) AS host,
uniqExact(ja4) AS distinct_ja4,
uniqExact(ja4) AS distinct_ja4_count,
groupUniqArray(ja4) AS ja4_list,
sum(ja4_hits) AS total_hits,
max(w_max) AS window_start,
min(w_min) AS first_seen,
max(w_max) AS last_seen
FROM (
SELECT
src_ip, host, ja4,
sum(hits) AS ja4_hits,
min(window_start) AS w_min,
max(window_start) AS w_max
FROM ja4_processing.agg_host_ip_ja4_1h
WHERE window_start >= now() - INTERVAL 24 HOUR
AND ja4 != ''
GROUP BY src_ip, host, ja4
) sub
GROUP BY src_ip
HAVING distinct_ja4 >= 2
ORDER BY distinct_ja4 DESC;
-- -----------------------------------------------------------------------------
-- view_dashboard_user_agents
--
-- Agrégation des User-Agents par IP, JA4 et heure.
-- Utilisée par variability.py et attributes.py avec ARRAY JOIN user_agents.
--
-- Colonnes :
-- src_ip — IPv4 (sans préfixe ::ffff:)
-- ja4 — Fingerprint TLS
-- hour — Début d'heure (toStartOfHour)
-- log_date — Date (pour le TTL de la vue)
-- user_agents — Array(String) des UAs distincts sur cette heure
-- requests — Nombre total de requêtes sur cette heure
-- -----------------------------------------------------------------------------
CREATE OR REPLACE VIEW ja4_processing.view_dashboard_user_agents AS
SELECT
-- Normalisation IPv4 : supprime le préfixe ::ffff: des IPs mappées IPv6→IPv4
toIPv4OrZero(replaceRegexpAll(toString(src_ip), '^::ffff:', '')) AS src_ip,
ja4,
toStartOfHour(time) AS hour,
log_date,
-- Collecte les UAs distincts (max 100 pour éviter les tableaux géants)
groupUniqArray(100)(header_user_agent) AS user_agents,
count() AS requests
FROM ja4_logs.http_logs
WHERE time >= now() - INTERVAL 7 DAY
AND header_user_agent != ''
GROUP BY src_ip, ja4, toStartOfHour(time), log_date;
-- -----------------------------------------------------------------------------
-- view_dashboard_entities
--
-- Vue pivot permettant de naviguer entre entités (IP ↔ JA4 ↔ pays ↔ ASN ↔ hôte).
-- Pour chaque entité (entity_type + entity_value), expose les données associées :
-- ips, ja4s, hosts (via GROUP BY en Python), asns, countries, user_agents,
-- client_headers (array pour clustering.py).
--
-- Structure UNION ALL : une branche par type d'entité.
-- ClickHouse optimise les requêtes WHERE entity_type = 'ip' en éliminant
-- les autres branches (condition constante sur colonne calculée).
--
-- Colonnes :
-- entity_type — 'ip' | 'ja4' | 'country' | 'asn' | 'host'
-- entity_value — Valeur de l'entité (ex: '1.2.3.4', 't13d...', 'FR', ...)
-- src_ip — IPv6 (format natif ClickHouse)
-- ja4 — Fingerprint JA4
-- host — Virtual host HTTP
-- log_date — Date de la requête
-- client_headers — Array des noms de headers (splitByChar depuis http_logs)
-- asns — Array(String) avec l'ASN source (pour groupUniqArrayArray)
-- countries — Array(String) avec le code pays source
-- user_agents — Array(String) avec le User-Agent
-- -----------------------------------------------------------------------------
CREATE OR REPLACE VIEW ja4_processing.view_dashboard_entities AS
-- Perspective IP : entity_value = adresse IPv4 de la source
SELECT
'ip' AS entity_type,
replaceRegexpAll(toString(src_ip), '^::ffff:', '') AS entity_value,
src_ip,
ja4,
host,
log_date,
splitByChar(',', client_headers) AS client_headers,
[toString(src_asn)] AS asns,
[src_country_code] AS countries,
[header_user_agent] AS user_agents
FROM ja4_logs.http_logs
WHERE time >= now() - INTERVAL 7 DAY
UNION ALL
-- Perspective JA4 : entity_value = fingerprint TLS JA4
SELECT
'ja4' AS entity_type,
ja4 AS entity_value,
src_ip,
ja4,
host,
log_date,
splitByChar(',', client_headers) AS client_headers,
[toString(src_asn)] AS asns,
[src_country_code] AS countries,
[header_user_agent] AS user_agents
FROM ja4_logs.http_logs
WHERE time >= now() - INTERVAL 7 DAY
AND ja4 != ''
UNION ALL
-- Perspective pays : entity_value = code pays ISO-3166 (ex: 'FR', 'US')
SELECT
'country' AS entity_type,
src_country_code AS entity_value,
src_ip,
ja4,
host,
log_date,
splitByChar(',', client_headers) AS client_headers,
[toString(src_asn)] AS asns,
[src_country_code] AS countries,
[header_user_agent] AS user_agents
FROM ja4_logs.http_logs
WHERE time >= now() - INTERVAL 7 DAY
AND src_country_code != ''
UNION ALL
-- Perspective ASN : entity_value = numéro ASN (ex: '15169' pour Google)
SELECT
'asn' AS entity_type,
toString(src_asn) AS entity_value,
src_ip,
ja4,
host,
log_date,
splitByChar(',', client_headers) AS client_headers,
[toString(src_asn)] AS asns,
[src_country_code] AS countries,
[header_user_agent] AS user_agents
FROM ja4_logs.http_logs
WHERE time >= now() - INTERVAL 7 DAY
AND src_asn > 0
UNION ALL
-- Perspective hôte : entity_value = virtual host HTTP (ex: 'api.example.com')
SELECT
'host' AS entity_type,
host AS entity_value,
src_ip,
ja4,
host,
log_date,
splitByChar(',', client_headers) AS client_headers,
[toString(src_asn)] AS asns,
[src_country_code] AS countries,
[header_user_agent] AS user_agents
FROM ja4_logs.http_logs
WHERE time >= now() - INTERVAL 7 DAY
AND host != '';