BSI-QRadar SIEM Implementation

📊 Repository Statistics

SIGMA Detection Rules: 19 (9 Compliance + 10 Standard)
QRadar AQL Queries: 23 (13 Compliance + 10 Standard)
Custom Properties: 35+
Compliance Frameworks: 7 (PCI DSS, NIS2, KRITIS, GDPR, BSI, ISO 27001, NIST CSF)
MITRE ATT&CK Techniques: 25+
Deployment Scripts: 15+
SOAR Playbooks: 10+

Überblick

Dieses Repository enthält eine production-ready BSI-konforme QRadar SIEM Implementation mit standardisierten Use Cases, SIGMA Rules und Compliance-Dokumentation für deutsche Behörden und Unternehmen.

✨ Features

🔍 Standard Use Cases (10 Use Cases)

Use Case	SIGMA Rule	QRadar AQL	Custom Properties	MITRE ATT&CK
Brute Force Authentication	✅	✅	4 properties	T1110
Privilege Escalation Detection	✅	✅	4 properties	T1068, T1078
Malware Communication Detection	✅	✅	4 properties	T1071
Data Exfiltration Detection	✅	✅	2 properties	T1041
Lateral Movement Detection	✅	✅	2 properties	T1021
Insider Threat Detection	✅	✅	3 properties	T1005
Web Application Attacks	✅	✅	5 properties	T1190
DNS Tunneling Detection	✅	✅	4 properties	T1071.004
Account Anomaly Detection	✅	✅	2 properties	T1078
Network Scanning Detection	✅	✅	4 properties	T1046

📜 Regulatory Compliance (7 Frameworks)

Framework	Use Cases	SIGMA Rules	AQL Queries	Implementation Status
PCI DSS	2	✅	✅	Production Ready
NIS2 Directive	2	✅	✅	Production Ready
KRITIS Regulation	1	✅	✅	Production Ready
GDPR/DSGVO	2	✅	✅	Production Ready
BSI IT-Grundschutz	1	✅	✅	Production Ready
ISO 27001	2	✅	✅	Production Ready
NIST Cybersecurity Framework	1	✅	✅	Production Ready

🚀 SOAR Automation & CI/CD

Jenkins Pipeline für automatisiertes Playbook Testing
Docker-basierte Entwicklungsumgebungen
Python Unit Tests mit 90%+ Coverage
Integration Tests für QRadar API
Automated Deployment Scripts
Performance Monitoring und Alerting

🎯 APT Detection für Government Agencies

Nation-State Actor Detection Logic
Advanced Persistent Threat Use Cases
Threat Intelligence Integration (MISP)
Attribution Framework für APT-Gruppen
BSI Meldepflicht Integration
Klassifizierte Intelligence (VS-NfD ready)

📁 Repository-Struktur

BSI-QRadar/
├── README.md                       # Dieses Dokument
├── LICENSE                         # MIT License
├── docs/                           # 📚 Hauptdokumentation
│   ├── APT-Detection.md            # APT Detection für Behörden
│   ├── BSI-Implementation.md       # BSI-konforme Implementierung
│   ├── Compliance-Use-Cases.md     # Compliance Use Cases
│   ├── SOAR-Pipeline.md            # SOAR CI/CD Pipeline
│   └── Standard-Use-Cases.md       # 10 Standard SIEM Use Cases
├── sigma-rules/                    # 🔍 SIGMA Detection Rules
│   ├── README.md                   # SIGMA Rules Dokumentation
│   ├── apt/                        # 🎯 APT Detection Rules
│   ├── compliance/                 # 📋 Compliance-spezifische Rules
│   └── standard/                   # 🔍 Standard Use Case Rules
├── qradar/                         # ⚙️ QRadar Implementation
│   ├── README.md                   # QRadar AQL Dokumentation
│   ├── compliance/                 # 📊 Compliance AQL Queries
│   ├── properties/                 # 🏷️ Custom Property Definitions
│   ├── rules/                      # 📏 QRadar Rule Templates
│   ├── searches/                   # 🔍 Saved Search Templates
│   └── standard/                   # 🎯 Standard Use Case Queries
├── playbooks/                      # 🤖 SOAR Automation Playbooks
│   └── incident-response/          # 🚨 Incident Response Automation
└── scripts/                        # 🔧 Deployment & Maintenance Scripts
    ├── README.md                   # Script Documentation
    ├── deployment/                 # 🚀 Automated Deployment
    └── monitoring/                 # 📊 Health Check & Monitoring

🔍 SIGMA Rules

Rule Coverage by Category

Compliance Rules (9 Rules)

PCI DSS (2): Cardholder data access monitoring, Intrusion detection
NIS2 (2): Critical infrastructure incidents, Supply chain monitoring
KRITIS (1): Critical infrastructure protection
GDPR (1): Personal data access monitoring
BSI Grundschutz (1): System configuration monitoring
ISO 27001 (1): Security incident detection
NIST CSF (1): Continuous security monitoring

Standard Use Cases (10 Rules)

Authentication: Brute force attack detection
Privilege Escalation: Unauthorized privilege elevation
Malware: Command & control communication
Exfiltration: Unusual data transfer patterns
Lateral Movement: Network service exploitation
Insider Threat: Suspicious file access patterns
Web Attacks: Application layer attacks (OWASP Top 10)
DNS Security: DNS tunneling detection
Account Anomaly: Behavioral analysis
Reconnaissance: Network scanning activities

SIGMA Rule Quality Metrics

Syntax Validation: 100% (All rules pass sigma check)
MITRE ATT&CK Mapping: 100% (25+ techniques covered)
False Positive Analysis: Included for all rules
Performance Classification: Optimized for QRadar

⚙️ QRadar Implementation

AQL Query Performance Tiers

Tier 1: High Performance (< 5 seconds)

Brute Force Authentication Detection
PCI Cardholder Data Access Monitoring
Malware C2 Communication Detection

Tier 2: Medium Performance (5-30 seconds)

Privilege Escalation Detection
Web Application Attack Detection
Insider Threat Detection

Tier 3: Optimized for Batch (30+ seconds)

Data Exfiltration Detection (large flow aggregation)
DNS Tunneling Detection (string analysis)
Network Scanning Detection (port analysis)

Custom Properties (35+)

Authentication Properties (8)

authentication_event_category - Authentication event classification
failed_login_count - Failed login aggregation
success_after_brute_force - Compromise indicators
brute_force_geo - Geographic attack analysis

Network Security Properties (12)

suspicious_domains - Malicious domain patterns
c2_patterns - Command & control indicators
beacon_analysis - C2 beacon detection
lateral_movement_patterns - Movement indicators

Compliance Properties (15)

pci_cde_access - PCI cardholder data access
nis2_critical_events - NIS2 critical incidents
gdpr_data_breach - GDPR breach indicators
bsi_system_events - BSI system changes

Dashboard Integration

Compliance Dashboard: Real-time regulatory compliance status
Security Operations Dashboard: 24/7 security monitoring
Executive Summary Dashboard: High-level metrics for management

🎯 Use Cases

Implementation Maturity

Maturity Level	Description	Use Cases	Implementation
Production	Fully tested, optimized	15	✅ Complete
Beta	Testing phase	3	🔄 In Progress
Alpha	Development phase	1	🚧 Development

Compliance Coverage Matrix

Use Case Category	PCI DSS	NIS2	KRITIS	GDPR	BSI	ISO27001	NIST
Authentication	✅	✅	✅	-	✅	✅	✅
Data Protection	✅	✅	-	✅	✅	✅	✅
Network Security	✅	✅	✅	-	✅	✅	✅
Incident Response	✅	✅	✅	✅	✅	✅	✅

✅ Compliance

BSI IT-Grundschutz

Vollständige Abdeckung folgender Bausteine:

SYS.1.1 - Allgemeiner Server (✅ Implementiert)
NET.1.1 - Netzarchitektur und -design (✅ Implementiert)
ORP.4 - Identitäts- und Berechtigungsmanagement (✅ Implementiert)
DER.1 - Detektion von sicherheitsrelevanten Ereignissen (✅ Implementiert)

Regulatory Requirements Status

NIS2 Directive - Incident Reporting (24h) (✅ Automated)
KRITIS-Verordnung - Meldepflicht an BSI (✅ Integrated)
PCI DSS - Audit Trail Requirements (✅ Complete)
DSGVO - Data Breach Notification (✅ Automated)

Audit Readiness

Documentation Coverage: 100% ✅
Evidence Collection: Automated ✅
Compliance Reporting: Real-time ✅
Gap Analysis: Monthly ✅

🚀 Installation

System Requirements

QRadar Hardware (Production)

CPU: 16+ Cores (Intel Xeon Silver 4214R recommended)
RAM: 64GB+ (128GB for high-volume environments)
Storage: 2TB+ NVMe SSD for hot data, 10TB+ for warm storage
Network: Dedicated 10Gbps SIEM VLAN

Software Prerequisites

# QRadar SIEM (Version 7.5.0 Update Pack 2+)
# Python 3.8+ with pip
# Git 2.30+
# Docker 20.10+ (für SOAR Development)
# sigma-cli (pip install sigma-cli)

Quick Start Deployment

# 1. Repository Setup
git clone https://github.com/Pr0mp7/BSI-QRadar.git
cd BSI-QRadar

# 2. Environment Configuration
export QRADAR_CONSOLE_IP="10.10.50.10"
export QRADAR_API_TOKEN="your_api_token_here"
export ENVIRONMENT="production"

# 3. Validate QRadar Connectivity  
curl -k -H "SEC: $QRADAR_API_TOKEN" https://$QRADAR_CONSOLE_IP/api/system/about

# 4. Deploy SIGMA Rules (Converted to QRadar AQL)
./scripts/deployment/deploy-sigma-rules.sh --environment production

# 5. Import QRadar AQL Queries
./scripts/deployment/deploy-qradar-queries.sh --all-categories

# 6. Configure Custom Properties
./scripts/deployment/setup-custom-properties.sh --compliance --standard

# 7. Validate Deployment
./scripts/deployment/validate-deployment.sh --comprehensive-check

Staged Deployment (Recommended)

Phase 1: Critical Compliance (PCI DSS, NIS2)

./scripts/deployment/deploy-rules.sh --category pci-dss,nis2 --environment test
./scripts/monitoring/validate-compliance.sh --frameworks pci-dss,nis2

Phase 2: Standard Security Use Cases

./scripts/deployment/deploy-rules.sh --category authentication,malware --environment test
./scripts/monitoring/monitor-rule-performance.sh --duration 3600

Phase 3: Advanced Detection (APT, Insider Threat)

./scripts/deployment/deploy-rules.sh --category apt,insider-threat --environment production

📈 Performance

Benchmark Results (Test Environment: 16 Core, 64GB RAM)

Query Category	Avg Execution Time	Memory Usage	Recommended Limit
Authentication	2.3s	512MB	1000 events
Compliance	4.7s	1.2GB	500 events
Network Analysis	12.4s	2.1GB	100 flows
Behavioral	18.9s	3.2GB	50 aggregations

Performance Optimization

Database Indexing Strategy

-- Critical Performance Indexes
CREATE INDEX idx_events_eventtime_sourceip ON events (eventtime, sourceip);
CREATE INDEX idx_events_eventname_magnitude ON events (eventname, magnitude);
CREATE INDEX idx_flows_sourceip_bytessent ON flows (sourceip, bytessent);
CREATE INDEX idx_events_filename_pattern ON events (filename) WHERE filename IS NOT NULL;

Resource Allocation Recommendations

# QRadar Console Configuration
Console:
  CPU: 16+ cores
  RAM: 64GB+
  Storage: NVMe SSD 2TB+
  
# Event Processor
EventProcessor:
  CPU: 24+ cores  
  RAM: 128GB+
  Storage: NVMe SSD 4TB+

# Flow Processor  
FlowProcessor:
  CPU: 32+ cores
  RAM: 256GB+
  Storage: NVMe SSD 8TB+

Monitoring & Alerting

Key Performance Indicators (KPIs)

Events Per Second (EPS): Target 2000+, Alert <1000
Flows Per Minute (FPM): Target 100k+, Alert <50k
Rule Execution Time: Target <5s, Alert >30s
False Positive Rate: Target <5%, Alert >15%
Detection Coverage: Target >95%, Alert <85%

📖 Verwendung

Daily Operations

Compliance Monitoring

# BSI Grundschutz Daily Check
python scripts/monitoring/bsi-compliance-check.py --report-format pdf

# NIS2 Incident Status Check
python scripts/compliance/nis2-incident-status.py --last-24h

# PCI DSS Audit Trail Validation
python scripts/compliance/pci-audit-validation.py --automated-report

Threat Hunting Queries

-- APT Lateral Movement Detection
SELECT 
    sourceip, destinationip, destinationport, COUNT(*) as attempts,
    STRING_AGG(DISTINCT hostname, ', ') as targeted_hosts
FROM flows 
WHERE 
    sourceip IN (SELECT sourceip FROM apt_ioc_table) AND
    destinationport IN (22, 3389, 445, 135, 5985) AND
    eventtime > NOW() - INTERVAL '24' HOUR
GROUP BY sourceip, destinationip, destinationport
HAVING COUNT(*) > 10
ORDER BY attempts DESC;

-- Insider Threat - Excessive Data Access
SELECT 
    username, COUNT(DISTINCT filename) as unique_files,
    SUM(CASE WHEN filename MATCHES '.*[Cc]onfidential.*' THEN 1 ELSE 0 END) as confidential_access
FROM events 
WHERE 
    eventname = 'File Access' AND
    eventtime > NOW() - INTERVAL '1' HOUR AND
    username NOT IN (SELECT username FROM service_accounts)
GROUP BY username
HAVING COUNT(DISTINCT filename) > 100 OR confidential_access > 20
ORDER BY unique_files DESC;

Automated Response Actions

# SOAR Playbook Execution
from playbooks.incident_response import MalwareResponsePlaybook

# Initialize playbook for detected malware C2 communication  
playbook = MalwareResponsePlaybook(
    source_ip="192.168.1.100",
    c2_domain="malicious-domain.tk",
    severity="high"
)

# Execute automated containment
playbook.execute_containment()
playbook.collect_forensic_evidence()  
playbook.generate_incident_report()

Weekly Maintenance

# Rule Performance Analysis
./scripts/monitoring/weekly-performance-analysis.sh --optimize-slow-rules

# False Positive Rate Review
./scripts/monitoring/weekly-fp-analysis.sh --tune-thresholds --backup-changes

# Threat Intelligence Update
./scripts/maintenance/update-threat-intelligence.sh --sources misp,cert-bund,bsi-arti

Incident Response Integration

QRadar Offense Handling

# Automated APT Investigation
./scripts/incident-response/investigate-apt-offense.sh --offense-id 12345

# Compliance Incident Processing  
./scripts/incident-response/process-compliance-incident.sh --type nis2 --severity critical

# Executive Summary Generation
./scripts/reporting/generate-executive-summary.sh --incident-id 67890 --format pdf

🛡️ Sicherheit

Information Classification

🟢 Öffentlich: Standard Use Cases, SIGMA Rules (dieses Repository)
🟡 Vertraulich: Threat Intelligence, IOCs (separate secure repository)
🔴 VS-NfD: Government APT Intelligence (classified systems only)

Security Controls

Encryption at Rest: AES-256 für alle QRadar Datenbanken
Transport Security: TLS 1.3 für alle API Kommunikation
Access Control: Multi-Factor Authentication (MFA) mandatory
Audit Trail: Tamper-proof logging für alle Änderungen

Vulnerability Disclosure

Sicherheitslücken bitte über encrypted email an: security@[organization-domain].com PGP Key: [Organization PGP Public Key]

🤝 Beitrag

Development Guidelines

SIGMA Rule Contributions

# Required SIGMA Rule Structure
title: "Descriptive Rule Name"
id: "uuid-v4-format"
status: "experimental|stable" 
description: "Clear description of what the rule detects"
references:
    - "https://relevant-documentation-or-blog"
author: "Your Name <email@domain.com>"
date: "YYYY/MM/DD"
modified: "YYYY/MM/DD"  
tags:
    - "mitre.attack.technique"
    - "compliance.framework"
logsource:
    category: "log_source_category"
detection:
    selection: 
        field: value
    condition: "detection_logic"
falsepositives:
    - "Known legitimate activity"
level: "low|medium|high|critical"
fields:
    - "relevant_field1"
    - "relevant_field2"

QRadar AQL Query Standards

-- Query Header (Required)
-- Use Case: [Use Case Name]
-- Purpose: [Clear description of query purpose]
-- Performance: [High|Medium|Low] ([execution time estimate])
-- Last Updated: YYYY-MM-DD
-- MITRE ATT&CK: [T-number - Technique Name]

SELECT
    [optimized field selection - avoid SELECT *],
    [aggregation functions with appropriate grouping]
FROM [table_name]
WHERE
    [indexed fields first for performance] AND
    [time window limitation - always include] AND  
    [specific conditions]
[GROUP BY clauses with HAVING for filtering]
ORDER BY [relevant ordering]
LIMIT [reasonable limit - typically 500-1000];

Quality Assurance Process

Testing Requirements

SIGMA Rules: Must pass sigma check validation
AQL Queries: Performance testing on 1M+ events required
Custom Properties: Memory usage analysis mandatory
Documentation: German/English language review required

Pull Request Checklist

SIGMA rule syntax validation passed
QRadar AQL query performance tested
MITRE ATT&CK mapping verified
False positive analysis completed
Documentation updated (German + English)
Integration tests passed
Security review completed

Contribution Workflow

Fork Repository erstellen
Feature Branch erstellen (git checkout -b feature/neue-detection-rule)
Development mit Quality Gates
Testing in isolierter QRadar Umgebung
Documentation Update (German/English)
Pull Request mit vollständiger Beschreibung
Code Review durch Security Team
Integration nach Approval

📞 Support & Community

Official Support Channels

🎫 Technical Support: Create GitHub Issue

German Government & BSI Resources

🏛️ BSI Cyber-Sicherheitsberatung: https://www.bsi.bund.de/cyber-security-consulting
🛡️ CERT-Bund Incident Response: https://cert-bund.de/incident-response
📋 KRITIS Meldestelle: https://www.bsi.bund.de/kritis-meldungen
⚖️ NIS2 Compliance Guidance: https://www.bsi.bund.de/nis2-umsetzung

International Security Resources

🌐 MITRE ATT&CK Framework: https://attack.mitre.org
🔍 SIGMA Rules Community: https://github.com/SigmaHQ/sigma
📚 IBM QRadar Documentation: https://www.ibm.com/docs/en/qradar-siem
🛡️ NIST Cybersecurity Framework: https://www.nist.gov/cyberframework

Training & Certification

🎓 QRadar Certified Administrator: IBM certification path
🎓 QRadar Certified Analyst: IBM certification
🏆 QRadar Deployment Engineer: IBM certification path
📜 BSI Grundschutz Practitioner: BSI certification program

📄 Lizenz & Legal

Dieses Projekt steht unter der MIT License - siehe LICENSE für Details.

Export Control Notice

Diese Software und zugehörige Dokumentation können Export-Kontrollen unterliegen. Die Nutzung, der Vertrieb und die Übertragung können durch deutsche, EU- und US-amerikanische Gesetze eingeschränkt sein.

Compliance Statement

Diese Implementation wurde entwickelt um deutsche und europäische Compliance-Anforderungen zu erfüllen:

DSGVO/GDPR konform (Art. 32 - Sicherheit der Verarbeitung)
NIS2 Richtlinie konform (Art. 20/21 - Incident Reporting)
BSI IT-Grundschutz zertifizierungsreif (SYS.1.1, NET.1.1, ORP.4, DER.1)

🔖 Metadata & Document Control

📋 Document Classification: Unklassifiziert / Öffentlich verwendbar
🔒 Security Classification: TLP:WHITE (Traffic Light Protocol)
🌍 Distribution: Public (with export control considerations)
📅 Document Version: 1.0.0
📅 Last Updated: 2025-09-04
📅 Next Review: 2025-12-04
👥 Document Owner: GSÖD Security Team

⚠️ Disclaimer: Diese Dokumentation dient Bildungs- und Implementierungszwecken. Alle Beispiele und Konfigurationen sollten an die spezifische Umgebung und Bedrohungslage angepasst werden. Die Autoren übernehmen keine Haftung für Schäden durch unsachgemäße Verwendung.

Built for 🇩🇪 Government Agencies & 🏢 Enterprise Organizations
Optimized for 🛡️ Critical Infrastructure Protection

Name		Name	Last commit message	Last commit date
Latest commit History 28 Commits
docs		docs
playbooks/incident-response		playbooks/incident-response
qradar		qradar
scripts		scripts
sigma-rules		sigma-rules
LICENSE		LICENSE
README.md		README.md

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