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refactor: suppression dépendance User-Agent de la détection navigateur

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Changements SQL :
- modern_browser_score : sec-ch-ua→100, Sec-Fetch→70 (plus de UA fallback)
- Ajout has_sec_ch_ua (UInt8) dans agg_header_fingerprint_1h et ml_all_scores
- mss_mobile_mismatch utilise has_sec_ch_ua au lieu de modern_browser_score
- header_order_confidence : PARTITION BY ja4 au lieu de first_ua
- sec_ch_mobile_mismatch : comparaison Client Hints interne (sans UA)
- Migration 03_remove_ua_browser_detection.sql

Changements Python :
- browser.py Axe 3 : Client Hints + Sec-Fetch + is_fake_navigation (PAS de UA)
- Pondération axes : ja4_known 0.30, tls_coherence 0.20 (signaux TLS renforcés)
- preprocessing.py : has_sec_ch_ua ajouté aux features et binary_features

Fichiers modifiés : 8 SQL/Python + 1 migration, 36/36 tests passent.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
toto
2026-04-09 23:06:01 +02:00
parent 00e99e5464
commit 14db3d9040
9 changed files with 101 additions and 38 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
services/bot-detector/anubis/view_ai_features_anubis.sql
View File

@ -38,6 +38,7 @@ WITH base_data AS (
h.header_order_hash AS header_order_hash, h.header_count AS header_count,
h.has_accept_language AS has_accept_language, h.has_cookie AS has_cookie,
h.has_referer AS has_referer, h.modern_browser_score AS modern_browser_score,
h.has_sec_ch_ua AS has_sec_ch_ua,
h.ua_ch_mismatch AS ua_ch_mismatch,
(a.count_post / (a.hits + 1)) AS post_ratio,
(a.uniq_query_params / (a.uniq_paths + 1)) AS fuzzing_index,
@ -46,7 +47,7 @@ WITH base_data AS (
(a.orphan_count / (a.hits + 1)) AS orphan_ratio,
(a.ip_id_zero_count / (a.hits + 1)) AS ip_id_zero_ratio,
(a.hits / (a.unique_conn_id + 1)) AS multiplexing_efficiency,
IF(a.mss_1460_count > (a.hits * 0.8) AND h.modern_browser_score > 70, 1, 0) AS mss_mobile_mismatch,
IF(a.mss_1460_count > (a.hits * 0.8) AND h.has_sec_ch_ua > 0, 1, 0) AS mss_mobile_mismatch,
a.request_size_variance AS request_size_variance,
IF(a.tls_alpn = 'h2' AND a.http_version != '2', 1, 0) AS alpn_http_mismatch,
IF(length(a.tls_alpn) = 0 OR a.tls_alpn = '00', 1, 0) AS is_alpn_missing,
@ -62,7 +63,7 @@ WITH base_data AS (
(sum(a.hits) OVER (PARTITION BY a.ja4, a.src_asn) / (sum(a.hits) OVER (PARTITION BY a.ja4) + 1)) AS ja4_asn_concentration,
(sum(a.hits) OVER (PARTITION BY a.ja4, a.src_country_code) / (sum(a.hits) OVER (PARTITION BY a.ja4) + 1)) AS ja4_country_concentration,
IF(sum(a.hits) OVER (PARTITION BY a.ja4) < 100, 1, 0) AS is_rare_ja4,
(count() OVER (PARTITION BY h.header_order_hash, a.first_ua) / (count() OVER (PARTITION BY a.first_ua) + 1)) AS header_order_confidence,
(count() OVER (PARTITION BY h.header_order_hash, a.ja4) / (count() OVER (PARTITION BY a.ja4) + 1)) AS header_order_confidence,
uniqExact(h.header_order_hash) OVER (PARTITION BY a.src_ip) AS distinct_header_orders,
(a.uniq_paths / (a.hits + 1)) AS path_diversity_ratio,
a.url_depth_variance AS url_depth_variance,
@ -127,7 +128,8 @@ WITH base_data AS (
window_start, src_ip, any(header_order_hash) AS header_order_hash,
max(header_count) AS header_count, max(has_accept_language) AS has_accept_language,
max(has_cookie) AS has_cookie, max(has_referer) AS has_referer,
max(modern_browser_score) AS modern_browser_score, max(ua_ch_mismatch) AS ua_ch_mismatch,
max(modern_browser_score) AS modern_browser_score, max(has_sec_ch_ua) AS has_sec_ch_ua,
max(ua_ch_mismatch) AS ua_ch_mismatch,
any(sec_fetch_mode) AS sec_fetch_mode, any(sec_fetch_dest) AS sec_fetch_dest
FROM ja4_processing.agg_header_fingerprint_1h
WHERE window_start >= now() - INTERVAL 24 HOUR

28
services/bot-detector/bot_detector/browser.py
View File

@ -1,8 +1,8 @@
"""A9 — Identification multifactorielle des navigateurs.
5 axes indépendants combinés pour identifier les navigateurs légitimes.
Chaque axe produit un score [0,1]. La combinaison pondérée produit
browser_confidence [0,1], remplaçant l'ancien système binaire JA4-only.
Aucun axe ne repose sur le User-Agent (trivalement falsifiable).
Signaux principaux : JA4 (TLS), Client Hints, Sec-Fetch-*, comportement.
"""
import pandas as pd
import numpy as np
@ -22,10 +22,11 @@ _BROWSER_JA4_PROFILES = {
}
# Pondération des 5 axes pour le score browser_confidence.
# Favorise les signaux TLS (difficiles à falsifier) sur HTTP.
_AXIS_WEIGHTS = {
'ja4_known': 0.25, # Axe 1 — Signature JA4 dans dict_browser_ja4
'ja4_known': 0.30, # Axe 1 — Signature JA4 dans dict_browser_ja4 (TLS fingerprint)
'ja4_struct': 0.15, # Axe 2 — Structure JA4 (TLS1.3, h2, nb ciphers/ext)
'http_modern': 0.25, # Axe 3 — Headers HTTP modernes (sec-ch-ua, Sec-Fetch-*)
'http_modern': 0.20, # Axe 3 — Client Hints + Sec-Fetch-* (PAS de User-Agent)
'nav_behavior': 0.15, # Axe 4 — Comportement de navigation (assets, referers)
'tls_coherence': 0.20, # Axe 5 — Cohérence TLS/TCP (pas de mismatch)
}
@ -80,18 +81,21 @@ def _compute_browser_axes(df: pd.DataFrame) -> pd.DataFrame:
is_tls13 * 0.35 + is_h2h3 * 0.25 + ciphers_ok * 0.20 + exts_ok * 0.20
)
# ── Axe 3 — Headers HTTP modernes ──
mbs = df.get('modern_browser_score', pd.Series(0, index=df.index)).fillna(0)
# ── Axe 3 — Signaux HTTP sans User-Agent ──
# Client Hints (sec-ch-ua) = signal fort, nécessite un vrai moteur Chromium.
# Sec-Fetch-* = signal moyen, envoyé automatiquement par les navigateurs modernes.
# Le User-Agent n'est PAS utilisé (trivalement falsifiable par n'importe quel bot).
scu = df.get('has_sec_ch_ua', pd.Series(0, index=df.index)).fillna(0)
hal = df.get('has_accept_language', pd.Series(0, index=df.index)).fillna(0)
sfa = df.get('sec_fetch_absence_rate', pd.Series(1, index=df.index)).fillna(1)
gar = df.get('generic_accept_ratio', pd.Series(1, index=df.index)).fillna(1)
uam = df.get('ua_ch_mismatch', pd.Series(0, index=df.index)).fillna(0)
ifn = df.get('is_fake_navigation', pd.Series(0, index=df.index)).fillna(0)
axes['axis_http_modern'] = (
(mbs >= 50).astype(float) * 0.35
+ (hal > 0).astype(float) * 0.20
+ (sfa < 0.3).astype(float) * 0.25
+ (gar < 0.3).astype(float) * 0.10
+ (uam == 0).astype(float) * 0.10
(scu > 0).astype(float) * 0.30
+ (sfa < 0.2).astype(float) * 0.30
+ (hal > 0).astype(float) * 0.15
+ (gar < 0.3).astype(float) * 0.15
+ (ifn == 0).astype(float) * 0.10
)
# ── Axe 4 — Comportement de navigation ──

5
services/bot-detector/bot_detector/preprocessing.py
View File

@ -20,7 +20,7 @@ FEATURES = [
'hits', 'hit_velocity', 'fuzzing_index', 'post_ratio', 'port_exhaustion_ratio',
'orphan_ratio', 'max_keepalives', 'tcp_shared_count', 'header_order_shared_count',
'header_count', 'has_accept_language', 'has_cookie', 'has_referer',
'modern_browser_score', 'ua_ch_mismatch', 'ip_id_zero_ratio',
'modern_browser_score', 'ua_ch_mismatch', 'has_sec_ch_ua', 'ip_id_zero_ratio',
'request_size_variance', 'multiplexing_efficiency', 'mss_mobile_mismatch',
'asset_ratio', 'direct_access_ratio', 'is_ua_rotating', 'distinct_ja4_count',
'src_port_density', 'ja4_asn_concentration', 'ja4_country_concentration', 'is_rare_ja4',
@ -103,7 +103,8 @@ def preprocess_df(df: pd.DataFrame) -> pd.DataFrame:
# Imputation intelligente
binary_features = {
'has_accept_language', 'has_cookie', 'has_referer', 'ua_ch_mismatch',
'has_accept_language', 'has_cookie', 'has_referer', 'has_sec_ch_ua',
'ua_ch_mismatch',
'is_ua_rotating', 'is_alpn_missing', 'sni_host_mismatch', 'alpn_http_mismatch',
'mss_mobile_mismatch', 'anubis_is_flagged', 'is_rare_ja4',
'is_fake_navigation', 'has_xff', 'sec_ch_mobile_mismatch',

8
services/bot-detector/bot_detector/tests/test_detector.py
View File

@ -606,23 +606,23 @@ def test_browser_consistency_score_range():
"""browser_consistency_score is in [0, 5] and sums 5 binary signals."""
df = pd.DataFrame({
'browser_family': ['Chromium', '', 'Firefox', 'Safari'],
'modern_browser_score': [100, 0, 80, 50],
'has_sec_ch_ua': [1, 0, 1, 0],
'has_accept_language': [1, 0, 1, 1],
'has_cookie': [1, 0, 1, 0],
'sec_fetch_absence_rate': [0.0, 1.0, 0.1, 0.6],
})
is_known = (df['browser_family'] != '').astype(int)
mbs_ok = (df['modern_browser_score'] >= 50).astype(int)
scu_ok = (df['has_sec_ch_ua'] > 0).astype(int)
hal_ok = (df['has_accept_language'] > 0).astype(int)
hck_ok = (df['has_cookie'] > 0).astype(int)
sfa_ok = (df['sec_fetch_absence_rate'] < 0.5).astype(int)
bcs = is_known + mbs_ok + hal_ok + hck_ok + sfa_ok
bcs = is_known + scu_ok + hal_ok + hck_ok + sfa_ok
assert bcs.min() >= 0 and bcs.max() <= 5
assert bcs.iloc[0] == 5, "Chromium with all signals should score 5"
assert bcs.iloc[1] == 0, "Empty browser with no signals should score 0"
assert bcs.iloc[2] == 5, "Firefox with all signals should score 5"
assert bcs.iloc[3] == 3, "Safari without cookie and high sec_fetch_absence should score 3"
assert bcs.iloc[3] == 2, "Safari without CH/cookie and high sec_fetch_absence should score 2"
def test_legitimate_browser_classification_threshold():

26
services/bot-detector/deploy_views.sql
View File

@ -178,6 +178,7 @@ CREATE TABLE ja4_processing.agg_header_fingerprint_1h
has_cookie SimpleAggregateFunction(max, UInt8),
has_referer SimpleAggregateFunction(max, UInt8),
modern_browser_score SimpleAggregateFunction(max, UInt8),
has_sec_ch_ua SimpleAggregateFunction(max, UInt8),
ua_ch_mismatch SimpleAggregateFunction(max, UInt8),
sec_fetch_mode SimpleAggregateFunction(any, String),
sec_fetch_dest SimpleAggregateFunction(any, String)
@ -200,7 +201,8 @@ SELECT
max(toUInt8(if(position(src.client_headers, 'Accept-Language') > 0, 1, 0))) AS has_accept_language,
max(toUInt8(if(position(src.client_headers, 'Cookie') > 0, 1, 0))) AS has_cookie,
max(toUInt8(if(position(src.client_headers, 'Referer') > 0, 1, 0))) AS has_referer,
max(toUInt8(if(length(src.header_sec_ch_ua) > 0, 100, if(length(src.header_user_agent) > 0, 50, 0)))) AS modern_browser_score,
max(toUInt8(if(length(src.header_sec_ch_ua) > 0, 100, if(length(src.header_sec_fetch_site) > 0, 70, 0)))) AS modern_browser_score,
max(toUInt8(if(length(src.header_sec_ch_ua) > 0, 1, 0))) AS has_sec_ch_ua,
max(toUInt8(if((position(src.header_user_agent, 'Windows') > 0 AND position(src.header_sec_ch_ua_platform, 'Windows') == 0) OR (position(src.header_user_agent, 'iPhone') > 0 AND position(src.header_sec_ch_ua_platform, 'iOS') == 0), 1, 0))) AS ua_ch_mismatch,
any(src.header_sec_fetch_mode) AS sec_fetch_mode,
any(src.header_sec_fetch_dest) AS sec_fetch_dest
@ -219,7 +221,7 @@ CREATE TABLE ja4_processing.ml_detected_anomalies
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,
is_headless UInt8, ua_ch_mismatch UInt8, header_order_shared_count UInt32, ip_id_zero_ratio Float32,
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,
@ -303,12 +305,13 @@ WITH base_data AS (
a.true_window_size AS true_window_size, a.window_mss_ratio AS window_mss_ratio, a.max_keepalives AS max_keepalives,
h.header_order_hash AS header_order_hash, h.header_count AS header_count,
h.has_accept_language AS has_accept_language, h.has_cookie AS has_cookie,
h.has_referer AS has_referer, h.modern_browser_score AS modern_browser_score, h.ua_ch_mismatch AS ua_ch_mismatch,
h.has_referer AS has_referer, h.modern_browser_score AS modern_browser_score,
h.has_sec_ch_ua AS has_sec_ch_ua, h.ua_ch_mismatch AS ua_ch_mismatch,
(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,
(a.unique_src_ports / (a.hits + 1)) AS port_exhaustion_ratio, (a.orphan_count / (a.hits + 1)) AS orphan_ratio,
(a.ip_id_zero_count / (a.hits + 1)) AS ip_id_zero_ratio, (a.hits / (a.unique_conn_id + 1)) AS multiplexing_efficiency,
IF(a.mss_1460_count > (a.hits * 0.8) AND h.modern_browser_score > 70, 1, 0) AS mss_mobile_mismatch,
IF(a.mss_1460_count > (a.hits * 0.8) AND h.has_sec_ch_ua > 0, 1, 0) AS mss_mobile_mismatch,
a.request_size_variance AS request_size_variance,
IF(a.tls_alpn = 'h2' AND a.http_version != '2', 1, 0) AS alpn_http_mismatch,
IF(length(a.tls_alpn) = 0 OR a.tls_alpn = '00', 1, 0) AS is_alpn_missing,
@ -322,7 +325,7 @@ WITH base_data AS (
(sum(a.hits) OVER (PARTITION BY a.ja4, a.src_asn) / (sum(a.hits) OVER (PARTITION BY a.ja4) + 1)) AS ja4_asn_concentration,
(sum(a.hits) OVER (PARTITION BY a.ja4, a.src_country_code) / (sum(a.hits) OVER (PARTITION BY a.ja4) + 1)) AS ja4_country_concentration,
IF(sum(a.hits) OVER (PARTITION BY a.ja4) < 100, 1, 0) AS is_rare_ja4,
(count() OVER (PARTITION BY h.header_order_hash, a.first_ua) / (count() OVER (PARTITION BY a.first_ua) + 1)) AS header_order_confidence,
(count() OVER (PARTITION BY h.header_order_hash, a.ja4) / (count() OVER (PARTITION BY a.ja4) + 1)) AS header_order_confidence,
uniqExact(h.header_order_hash) OVER (PARTITION BY a.src_ip) AS distinct_header_orders,
(a.uniq_paths / (a.hits + 1)) AS path_diversity_ratio,
a.url_depth_variance AS url_depth_variance,
@ -375,7 +378,8 @@ WITH base_data AS (
window_start, src_ip, any(header_order_hash) AS header_order_hash,
max(header_count) AS header_count, max(has_accept_language) AS has_accept_language,
max(has_cookie) AS has_cookie, max(has_referer) AS has_referer,
max(modern_browser_score) AS modern_browser_score, max(ua_ch_mismatch) AS ua_ch_mismatch,
max(modern_browser_score) AS modern_browser_score, max(has_sec_ch_ua) AS has_sec_ch_ua,
max(ua_ch_mismatch) AS ua_ch_mismatch,
any(sec_fetch_mode) AS sec_fetch_mode, any(sec_fetch_dest) AS sec_fetch_dest
FROM ja4_processing.agg_header_fingerprint_1h
WHERE window_start >= now() - INTERVAL 24 HOUR
@ -450,12 +454,13 @@ WITH base_data AS (
a.true_window_size AS true_window_size, a.window_mss_ratio AS window_mss_ratio, a.max_keepalives AS max_keepalives,
h.header_order_hash AS header_order_hash, h.header_count AS header_count,
h.has_accept_language AS has_accept_language, h.has_cookie AS has_cookie,
h.has_referer AS has_referer, h.modern_browser_score AS modern_browser_score, h.ua_ch_mismatch AS ua_ch_mismatch,
h.has_referer AS has_referer, h.modern_browser_score AS modern_browser_score,
h.has_sec_ch_ua AS has_sec_ch_ua, h.ua_ch_mismatch AS ua_ch_mismatch,
(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,
(a.unique_src_ports / (a.hits + 1)) AS port_exhaustion_ratio, (a.orphan_count / (a.hits + 1)) AS orphan_ratio,
(a.ip_id_zero_count / (a.hits + 1)) AS ip_id_zero_ratio, (a.hits / (a.unique_conn_id + 1)) AS multiplexing_efficiency,
IF(a.mss_1460_count > (a.hits * 0.8) AND h.modern_browser_score > 70, 1, 0) AS mss_mobile_mismatch,
IF(a.mss_1460_count > (a.hits * 0.8) AND h.has_sec_ch_ua > 0, 1, 0) AS mss_mobile_mismatch,
a.request_size_variance AS request_size_variance,
IF(a.tls_alpn = 'h2' AND a.http_version != '2', 1, 0) AS alpn_http_mismatch,
IF(length(a.tls_alpn) = 0 OR a.tls_alpn = '00', 1, 0) AS is_alpn_missing,
@ -469,7 +474,7 @@ WITH base_data AS (
(sum(a.hits) OVER (PARTITION BY a.ja4, a.src_asn) / (sum(a.hits) OVER (PARTITION BY a.ja4) + 1)) AS ja4_asn_concentration,
(sum(a.hits) OVER (PARTITION BY a.ja4, a.src_country_code) / (sum(a.hits) OVER (PARTITION BY a.ja4) + 1)) AS ja4_country_concentration,
IF(sum(a.hits) OVER (PARTITION BY a.ja4) < 100, 1, 0) AS is_rare_ja4,
(count() OVER (PARTITION BY h.header_order_hash, a.first_ua) / (count() OVER (PARTITION BY a.first_ua) + 1)) AS header_order_confidence,
(count() OVER (PARTITION BY h.header_order_hash, a.ja4) / (count() OVER (PARTITION BY a.ja4) + 1)) AS header_order_confidence,
uniqExact(h.header_order_hash) OVER (PARTITION BY a.src_ip) AS distinct_header_orders,
(a.uniq_paths / (a.hits + 1)) AS path_diversity_ratio,
a.url_depth_variance AS url_depth_variance,
@ -519,7 +524,8 @@ WITH base_data AS (
src_ip, any(header_order_hash) AS header_order_hash,
max(header_count) AS header_count, max(has_accept_language) AS has_accept_language,
max(has_cookie) AS has_cookie, max(has_referer) AS has_referer,
max(modern_browser_score) AS modern_browser_score, max(ua_ch_mismatch) AS ua_ch_mismatch,
max(modern_browser_score) AS modern_browser_score, max(has_sec_ch_ua) AS has_sec_ch_ua,
max(ua_ch_mismatch) AS ua_ch_mismatch,
any(sec_fetch_mode) AS sec_fetch_mode, any(sec_fetch_dest) AS sec_fetch_dest
FROM ja4_processing.agg_header_fingerprint_1h
WHERE window_start >= now() - INTERVAL 24 HOUR

45
services/correlator/sql/migrations/03_remove_ua_browser_detection.sql Normal file
View File

@ -0,0 +1,45 @@
-- === 03_remove_ua_browser_detection.sql — Suppression dépendance User-Agent ===
--
-- Contexte : l'identification navigateur ne doit PAS se baser sur le User-Agent
-- (trivalement falsifiable). Cette migration :
-- 1. Ajoute has_sec_ch_ua à agg_header_fingerprint_1h
-- 2. Recréé la MV avec modern_browser_score basé sur Client Hints + Sec-Fetch
-- 3. Recréé sec_ch_mobile_mismatch sans UA (Client Hints only)
-- 4. Ajoute has_sec_ch_ua à ml_all_scores
-- ---------------------------------------------------------------------------
-- 1. Nouvelle colonne has_sec_ch_ua
ALTER TABLE ja4_processing.agg_header_fingerprint_1h
ADD COLUMN IF NOT EXISTS has_sec_ch_ua SimpleAggregateFunction(max, UInt8)
AFTER modern_browser_score;
-- 2. Recréer la MV sans dépendance UA
DROP VIEW IF EXISTS ja4_processing.mv_agg_header_fingerprint_1h;
CREATE MATERIALIZED VIEW ja4_processing.mv_agg_header_fingerprint_1h
TO ja4_processing.agg_header_fingerprint_1h AS
SELECT
toStartOfHour(src.time) AS window_start,
toIPv6(src.src_ip) AS src_ip,
any(toString(cityHash64(src.client_headers))) AS header_order_hash,
max(toUInt16(length(src.client_headers) - length(replaceAll(src.client_headers, ',', '')) + 1)) AS header_count,
max(toUInt8(if(position(src.client_headers, 'Accept-Language') > 0, 1, 0))) AS has_accept_language,
max(toUInt8(if(position(src.client_headers, 'Cookie') > 0, 1, 0))) AS has_cookie,
max(toUInt8(if(position(src.client_headers, 'Referer') > 0, 1, 0))) AS has_referer,
-- modern_browser_score : sec-ch-ua → 100, Sec-Fetch → 70, sinon → 0 (PAS de UA)
max(toUInt8(if(length(src.header_sec_ch_ua) > 0, 100, if(length(src.header_sec_fetch_site) > 0, 70, 0)))) AS modern_browser_score,
max(toUInt8(if(length(src.header_sec_ch_ua) > 0, 1, 0))) AS has_sec_ch_ua,
max(toUInt8(if((position(src.header_user_agent, 'Windows') > 0 AND position(src.header_sec_ch_ua_platform, 'Windows') == 0) OR (position(src.header_user_agent, 'iPhone') > 0 AND position(src.header_sec_ch_ua_platform, 'iOS') == 0), 1, 0))) AS ua_ch_mismatch,
-- sec_ch_mobile_mismatch : incohérence interne Client Hints (pas de UA)
max(toUInt8(if(
(src.header_sec_ch_ua_mobile = '?1' AND position(src.header_sec_ch_ua_platform, 'Windows') > 0)
OR (src.header_sec_ch_ua_mobile = '?0' AND position(src.header_sec_ch_ua_platform, 'Android') > 0),
1, 0))) AS sec_ch_mobile_mismatch,
any(src.header_sec_fetch_mode) AS sec_fetch_mode,
any(src.header_sec_fetch_dest) AS sec_fetch_dest
FROM ja4_logs.http_logs AS src
GROUP BY window_start, src.src_ip;
-- 3. Ajouter has_sec_ch_ua à ml_all_scores
ALTER TABLE ja4_processing.ml_all_scores
ADD COLUMN IF NOT EXISTS has_sec_ch_ua UInt8 DEFAULT 0;

8
shared/clickhouse/05_aggregation_tables.sql
View File

@ -202,6 +202,7 @@ CREATE TABLE IF NOT EXISTS ja4_processing.agg_header_fingerprint_1h
has_cookie SimpleAggregateFunction(max, UInt8),
has_referer SimpleAggregateFunction(max, UInt8),
modern_browser_score SimpleAggregateFunction(max, UInt8),
has_sec_ch_ua SimpleAggregateFunction(max, UInt8),
ua_ch_mismatch SimpleAggregateFunction(max, UInt8),
sec_ch_mobile_mismatch SimpleAggregateFunction(max, UInt8),
sec_fetch_mode SimpleAggregateFunction(any, String),
@ -222,11 +223,12 @@ SELECT
max(toUInt8(if(position(src.client_headers, 'Accept-Language') > 0, 1, 0))) AS has_accept_language,
max(toUInt8(if(position(src.client_headers, 'Cookie') > 0, 1, 0))) AS has_cookie,
max(toUInt8(if(position(src.client_headers, 'Referer') > 0, 1, 0))) AS has_referer,
max(toUInt8(if(length(src.header_sec_ch_ua) > 0, 100, if(length(src.header_user_agent) > 0, 50, 0)))) AS modern_browser_score,
max(toUInt8(if(length(src.header_sec_ch_ua) > 0, 100, if(length(src.header_sec_fetch_site) > 0, 70, 0)))) AS modern_browser_score,
max(toUInt8(if(length(src.header_sec_ch_ua) > 0, 1, 0))) AS has_sec_ch_ua,
max(toUInt8(if((position(src.header_user_agent, 'Windows') > 0 AND position(src.header_sec_ch_ua_platform, 'Windows') == 0) OR (position(src.header_user_agent, 'iPhone') > 0 AND position(src.header_sec_ch_ua_platform, 'iOS') == 0), 1, 0))) AS ua_ch_mismatch,
max(toUInt8(if(
(src.header_sec_ch_ua_mobile = '?1' AND position(src.header_user_agent, 'Mobile') == 0 AND position(src.header_user_agent, 'Android') == 0 AND position(src.header_user_agent, 'iPhone') == 0)
OR (src.header_sec_ch_ua_mobile = '?0' AND (position(src.header_user_agent, 'iPhone') > 0 OR position(src.header_user_agent, 'Android') > 0)),
(src.header_sec_ch_ua_mobile = '?1' AND position(src.header_sec_ch_ua_platform, 'Windows') > 0)
OR (src.header_sec_ch_ua_mobile = '?0' AND position(src.header_sec_ch_ua_platform, 'Android') > 0),
1, 0))) AS sec_ch_mobile_mismatch,
any(src.header_sec_fetch_mode) AS sec_fetch_mode,
any(src.header_sec_fetch_dest) AS sec_fetch_dest

3
shared/clickhouse/06_ml_tables.sql
View File

@ -33,7 +33,8 @@ CREATE TABLE IF NOT EXISTS ja4_processing.ml_detected_anomalies
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, is_headless 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,

8
shared/clickhouse/07_ai_features_view.sql
View File

@ -44,6 +44,7 @@ WITH base_data AS (
h.header_order_hash AS header_order_hash, h.header_count AS header_count,
h.has_accept_language AS has_accept_language, h.has_cookie AS has_cookie,
h.has_referer AS has_referer, h.modern_browser_score AS modern_browser_score,
h.has_sec_ch_ua AS has_sec_ch_ua,
h.ua_ch_mismatch AS ua_ch_mismatch,
(a.count_post / (a.hits + 1)) AS post_ratio,
(a.uniq_query_params / (a.uniq_paths + 1)) AS fuzzing_index,
@ -52,7 +53,7 @@ WITH base_data AS (
(a.orphan_count / (a.hits + 1)) AS orphan_ratio,
(a.ip_id_zero_count / (a.hits + 1)) AS ip_id_zero_ratio,
(a.hits / (a.unique_conn_id + 1)) AS multiplexing_efficiency,
IF(a.mss_1460_count > (a.hits * 0.8) AND h.modern_browser_score > 70, 1, 0) AS mss_mobile_mismatch,
IF(a.mss_1460_count > (a.hits * 0.8) AND h.has_sec_ch_ua > 0, 1, 0) AS mss_mobile_mismatch,
a.request_size_variance AS request_size_variance,
IF(a.tls_alpn = 'h2' AND a.http_version != '2', 1, 0) AS alpn_http_mismatch,
IF(length(a.tls_alpn) = 0 OR a.tls_alpn = '00', 1, 0) AS is_alpn_missing,
@ -68,7 +69,7 @@ WITH base_data AS (
(sum(a.hits) OVER (PARTITION BY a.ja4, a.src_asn) / (sum(a.hits) OVER (PARTITION BY a.ja4) + 1)) AS ja4_asn_concentration,
(sum(a.hits) OVER (PARTITION BY a.ja4, a.src_country_code) / (sum(a.hits) OVER (PARTITION BY a.ja4) + 1)) AS ja4_country_concentration,
IF(sum(a.hits) OVER (PARTITION BY a.ja4) < 100, 1, 0) AS is_rare_ja4,
(count() OVER (PARTITION BY h.header_order_hash, a.first_ua) / (count() OVER (PARTITION BY a.first_ua) + 1)) AS header_order_confidence,
(count() OVER (PARTITION BY h.header_order_hash, a.ja4) / (count() OVER (PARTITION BY a.ja4) + 1)) AS header_order_confidence,
uniqExact(h.header_order_hash) OVER (PARTITION BY a.src_ip) AS distinct_header_orders,
(a.uniq_paths / (a.hits + 1)) AS path_diversity_ratio,
a.url_depth_variance AS url_depth_variance,
@ -141,7 +142,8 @@ WITH base_data AS (
window_start, src_ip, any(header_order_hash) AS header_order_hash,
max(header_count) AS header_count, max(has_accept_language) AS has_accept_language,
max(has_cookie) AS has_cookie, max(has_referer) AS has_referer,
max(modern_browser_score) AS modern_browser_score, max(ua_ch_mismatch) AS ua_ch_mismatch,
max(modern_browser_score) AS modern_browser_score, max(has_sec_ch_ua) AS has_sec_ch_ua,
max(ua_ch_mismatch) AS ua_ch_mismatch,
max(sec_ch_mobile_mismatch) AS sec_ch_mobile_mismatch,
any(sec_fetch_mode) AS sec_fetch_mode, any(sec_fetch_dest) AS sec_fetch_dest
FROM ja4_processing.agg_header_fingerprint_1h