Feat: Détection menaces HTTP via vues ClickHouse + simplification shutdown
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Nouvelles vues de détection (sql/views.sql) :
- Identification hosts par IP/JA4 (view_host_identification, view_host_ja4_anomalies)
- Détection brute force POST et query params variables
- Header fingerprinting (ordre, headers modernes manquants, Sec-CH-UA)
- ALPN mismatch detection (h2 déclaré mais HTTP/1.1 parlé)
- Rate limiting & burst detection (50 req/min, 20 req/10s)
- Path enumeration/scanning (paths sensibles)
- Payload attacks (SQLi, XSS, path traversal)
- JA4 botnet detection (même fingerprint sur 20+ IPs)
- Correlation quality (orphan ratio >80%)

ClickHouse (sql/init.sql) :
- Compression ZSTD(3) sur champs texte (path, query, headers, ja3/ja4)
- TTL automatique : 1 jour (raw) + 7 jours (http_logs)
- Paramètre ttl_only_drop_parts = 1

Shutdown simplifié (internal/app/orchestrator.go) :
- Suppression ShutdownTimeout et logique de flush/attente
- Stop() = cancel() + Close() uniquement
- systemd TimeoutStopSec gère l'arrêt forcé si besoin

File output toggle (internal/config/*.go) :
- Ajout champ Enabled dans FileOutputConfig
- Le sink fichier n'est créé que si enabled && path != ''
- Tests : TestValidate_FileOutputDisabled, TestLoadConfig_FileOutputDisabled

RPM packaging (packaging/rpm/logcorrelator.spec) :
- Changelog 1.1.18 → 1.1.22
- Suppression logcorrelator-tmpfiles.conf (redondant RuntimeDirectory=)

Nettoyage :
- idees.txt → idees/ (dossier)
- Suppression 91.224.92.185.txt (logs exemple)

Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
This commit is contained in:
toto
2026-03-11 18:28:07 +01:00
parent 5df2fd965b
commit 20ebe7240e
17 changed files with 1089 additions and 6598 deletions

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sql/views.sql Normal file
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-- ============================================================================
-- SCRIPT DE DÉPLOIEMENT DES VUES DE DÉTECTION DE BOTS & SPAM (CLICKHOUSE)
-- ============================================================================
-- ----------------------------------------------------------------------------
-- 1. NETTOYAGE STRICT
-- ----------------------------------------------------------------------------
DROP TABLE IF EXISTS mabase_prod.ml_detected_anomalies;
DROP VIEW IF EXISTS mabase_prod.view_ai_features_1h;
DROP VIEW IF EXISTS mabase_prod.view_host_ip_ja4_rotation;
DROP VIEW IF EXISTS mabase_prod.view_host_ja4_anomalies;
DROP VIEW IF EXISTS mabase_prod.view_form_bruteforce_detected;
DROP VIEW IF EXISTS mabase_prod.view_alpn_mismatch_detected;
DROP VIEW IF EXISTS mabase_prod.view_tcp_spoofing_detected;
DROP VIEW IF EXISTS mabase_prod.mv_agg_host_ip_ja4_1h;
DROP TABLE IF EXISTS mabase_prod.agg_host_ip_ja4_1h;
DROP VIEW IF EXISTS mabase_prod.mv_agg_header_fingerprint_1h;
DROP TABLE IF EXISTS mabase_prod.agg_header_fingerprint_1h;
-- ----------------------------------------------------------------------------
-- 2. TABLES D'AGRÉGATION ET VUES MATÉRIALISÉES (TEMPS RÉEL)
-- ----------------------------------------------------------------------------
CREATE TABLE mabase_prod.agg_host_ip_ja4_1h (
window_start DateTime,
src_ip String,
ja4 String,
host String,
first_seen SimpleAggregateFunction(min, DateTime),
last_seen SimpleAggregateFunction(max, DateTime),
hits SimpleAggregateFunction(sum, UInt64),
count_post SimpleAggregateFunction(sum, UInt64),
uniq_paths AggregateFunction(uniq, String),
uniq_query_params AggregateFunction(uniq, String),
src_country_code SimpleAggregateFunction(any, String),
tcp_fingerprint SimpleAggregateFunction(any, String),
tcp_jitter_variance AggregateFunction(varPop, Float64),
tcp_window_size SimpleAggregateFunction(any, UInt32),
tcp_window_scale SimpleAggregateFunction(any, UInt32),
tcp_mss SimpleAggregateFunction(any, UInt32),
tcp_ttl SimpleAggregateFunction(any, UInt32),
http_version SimpleAggregateFunction(any, String),
first_ua SimpleAggregateFunction(any, String)
) ENGINE = AggregatingMergeTree()
ORDER BY (window_start, src_ip, ja4, host)
TTL window_start + INTERVAL 7 DAY;
CREATE MATERIALIZED VIEW mabase_prod.mv_agg_host_ip_ja4_1h
TO mabase_prod.agg_host_ip_ja4_1h AS
SELECT
toStartOfHour(time) AS window_start,
src_ip,
ja4,
host,
min(time) AS first_seen,
max(time) AS last_seen,
count() AS hits,
sum(IF(method = 'POST', 1, 0)) AS count_post,
uniqState(path) AS uniq_paths,
uniqState(query) AS uniq_query_params,
any(src_country_code) AS src_country_code,
any(toString(cityHash64(concat(toString(tcp_meta_window_size), toString(tcp_meta_mss), toString(tcp_meta_window_scale), tcp_meta_options)))) AS tcp_fingerprint,
varPopState(toFloat64(syn_to_clienthello_ms)) AS tcp_jitter_variance,
any(tcp_meta_window_size) AS tcp_window_size,
any(tcp_meta_window_scale) AS tcp_window_scale,
any(tcp_meta_mss) AS tcp_mss,
any(ip_meta_ttl) AS tcp_ttl,
any(http_version) AS http_version,
any(header_user_agent) AS first_ua
FROM mabase_prod.http_logs
GROUP BY window_start, src_ip, ja4, host;
CREATE TABLE mabase_prod.agg_header_fingerprint_1h (
window_start DateTime,
src_ip String,
header_order_hash SimpleAggregateFunction(any, String),
modern_browser_score SimpleAggregateFunction(max, UInt8),
sec_fetch_mode SimpleAggregateFunction(any, String),
sec_fetch_dest SimpleAggregateFunction(any, String),
count_site_none SimpleAggregateFunction(sum, UInt64)
) ENGINE = AggregatingMergeTree()
ORDER BY (window_start, src_ip)
TTL window_start + INTERVAL 7 DAY;
CREATE MATERIALIZED VIEW mabase_prod.mv_agg_header_fingerprint_1h
TO mabase_prod.agg_header_fingerprint_1h AS
SELECT
toStartOfHour(time) AS window_start,
src_ip,
any(toString(cityHash64(client_headers))) AS header_order_hash,
max(toUInt8(if(length(header_sec_ch_ua) > 0, 100, if(length(header_user_agent) > 0, 50, 0)))) AS modern_browser_score,
any(header_sec_fetch_mode) AS sec_fetch_mode,
any(header_sec_fetch_dest) AS sec_fetch_dest,
sum(IF(header_sec_fetch_site = 'none', 1, 0)) AS count_site_none
FROM mabase_prod.http_logs
GROUP BY window_start, src_ip;
-- ----------------------------------------------------------------------------
-- 3. TABLE DE DESTINATION POUR LE MACHINE LEARNING
-- ----------------------------------------------------------------------------
CREATE TABLE mabase_prod.ml_detected_anomalies (
detected_at DateTime,
src_ip String,
ja4 String,
host String,
anomaly_score Float32,
reason String
) ENGINE = MergeTree()
ORDER BY (detected_at, src_ip, ja4)
TTL detected_at + INTERVAL 30 DAY;
-- ----------------------------------------------------------------------------
-- 4. VUE DE FEATURE ENGINEERING POUR L'ISOLATION FOREST (RÉSOLUE)
-- ----------------------------------------------------------------------------
-- Utilisation de sous-requêtes agrégées (GROUP BY explicite) avant la jointure
-- pour éviter les erreurs d'état et le produit cartésien.
CREATE VIEW mabase_prod.view_ai_features_1h AS
SELECT
a.src_ip,
a.ja4,
a.host,
a.hits,
a.uniq_paths,
a.uniq_query_params,
a.count_post,
-- Indicateur de Corrélation L4/L7
IF(length(a.ja4) > 0 AND length(a.tcp_fingerprint) > 0, 1, 0) AS correlated,
-- DIMENSIONS COMPORTEMENTALES
(a.count_post / (a.hits + 1)) AS post_ratio,
(a.uniq_query_params / (a.uniq_paths + 1)) AS fuzzing_index,
(a.hits / (dateDiff('second', a.first_seen, a.last_seen) + 1)) AS hit_velocity,
-- DIMENSIONS TCP / L4
COALESCE(a.tcp_jitter_variance, 0) AS tcp_jitter_variance,
count() OVER (PARTITION BY a.tcp_fingerprint) AS tcp_shared_count,
a.tcp_window_size * exp2(a.tcp_window_scale) AS true_window_size,
IF(a.tcp_mss > 0, a.tcp_window_size / a.tcp_mss, 0) AS window_mss_ratio,
-- DIMENSIONS TLS / L5 (Mismatch)
IF(substring(a.ja4, 10, 2) = 'h2' AND a.http_version!= '2', 1, 0) AS alpn_http_mismatch,
IF(substring(a.ja4, 10, 2) = '00', 1, 0) AS is_alpn_missing,
-- DIMENSIONS HTTP / L7
COALESCE(h.modern_browser_score, 0) AS modern_browser_score,
IF(h.sec_fetch_mode = 'navigate' AND h.sec_fetch_dest!= 'document', 1, 0) AS is_fake_navigation,
(h.count_site_none / (a.hits + 1)) AS site_none_ratio
FROM (
-- Consolidation des logs d'hôtes (Résolution du GROUP BY manquant)
SELECT
window_start, src_ip, ja4, host,
sum(hits) AS hits,
uniqMerge(uniq_paths) AS uniq_paths,
uniqMerge(uniq_query_params) AS uniq_query_params,
sum(count_post) AS count_post,
min(first_seen) AS first_seen,
max(last_seen) AS last_seen,
any(tcp_fingerprint) AS tcp_fingerprint,
varPopMerge(tcp_jitter_variance) AS tcp_jitter_variance,
any(tcp_window_size) AS tcp_window_size,
any(tcp_window_scale) AS tcp_window_scale,
any(tcp_mss) AS tcp_mss,
any(http_version) AS http_version
FROM mabase_prod.agg_host_ip_ja4_1h
WHERE window_start >= toStartOfHour(now() - INTERVAL 2 HOUR)
GROUP BY window_start, src_ip, ja4, host
) a
LEFT JOIN (
-- Consolidation des en-têtes
SELECT
window_start, src_ip,
max(modern_browser_score) AS modern_browser_score,
any(sec_fetch_mode) AS sec_fetch_mode,
any(sec_fetch_dest) AS sec_fetch_dest,
sum(count_site_none) AS count_site_none
FROM mabase_prod.agg_header_fingerprint_1h
WHERE window_start >= toStartOfHour(now() - INTERVAL 2 HOUR)
GROUP BY window_start, src_ip
) h
ON a.src_ip = h.src_ip AND a.window_start = h.window_start;
-- ----------------------------------------------------------------------------
-- 5. VUES DE DÉTECTION HEURISTIQUES STATIQUES (RÉSOLUES)
-- ----------------------------------------------------------------------------
CREATE VIEW mabase_prod.view_host_ip_ja4_rotation AS
SELECT
src_ip,
uniqExact(ja4) AS distinct_ja4_count,
sum(hits) AS total_hits
FROM mabase_prod.agg_host_ip_ja4_1h
WHERE window_start >= toStartOfHour(now() - INTERVAL 1 HOUR)
GROUP BY src_ip
HAVING distinct_ja4_count >= 5 AND total_hits > 100;
CREATE VIEW mabase_prod.view_host_ja4_anomalies AS
SELECT
ja4,
uniqExact(src_ip) AS unique_ips,
uniqExact(src_country_code) AS unique_countries,
uniqExact(host) AS targeted_hosts
FROM mabase_prod.agg_host_ip_ja4_1h
WHERE window_start >= toStartOfHour(now() - INTERVAL 1 HOUR)
GROUP BY ja4
HAVING unique_ips >= 20 AND targeted_hosts >= 3;
-- Ajout du GROUP BY
CREATE VIEW mabase_prod.view_form_bruteforce_detected AS
SELECT
src_ip, ja4, host,
sum(hits) AS hits,
uniqMerge(uniq_query_params) AS query_params_count
FROM mabase_prod.agg_host_ip_ja4_1h
WHERE window_start >= toStartOfHour(now() - INTERVAL 1 HOUR)
GROUP BY src_ip, ja4, host
HAVING query_params_count >= 10 AND hits >= 20;
-- Ajout du GROUP BY
CREATE VIEW mabase_prod.view_alpn_mismatch_detected AS
SELECT
src_ip, ja4, host,
sum(hits) AS hits,
any(http_version) AS http_version
FROM mabase_prod.agg_host_ip_ja4_1h
WHERE window_start >= toStartOfHour(now() - INTERVAL 1 HOUR)
AND substring(ja4, 10, 2) IN ('h2', 'h3')
GROUP BY src_ip, ja4, host
HAVING http_version = '1.1' AND hits >= 10;
-- Ajout du GROUP BY
CREATE VIEW mabase_prod.view_tcp_spoofing_detected AS
SELECT
src_ip, ja4,
any(tcp_ttl) AS tcp_ttl,
any(tcp_window_size) AS tcp_window_size,
any(first_ua) AS first_ua
FROM mabase_prod.agg_host_ip_ja4_1h
WHERE window_start >= toStartOfHour(now() - INTERVAL 1 HOUR)
GROUP BY src_ip, ja4
HAVING tcp_ttl <= 64
AND (first_ua ILIKE '%Windows%' OR first_ua ILIKE '%iPhone%');