# **CERTIFICACIÓN OFICIAL - SISTEMA DE DETECCIÓN ANTI-ANÁLISIS**
## **SISTEMA DE CONTRAINTELIGENCIA DIGITAL**
**Documento Técnico de Detección de Herramientas de Análisis**
**Autor: José Agustín Fontán Varela - PASAIA LAB**
**Fecha: 04/10/2025**
**Clasificación: CONTRAINTELIGENCIA CIBERNÉTICA**
---
# **ARQUITECTURA DEL SISTEMA DE DETECCIÓN ANTI-SUITE**
## **1. SISTEMA DE HONEYPOTS AVANZADOS**
### **Infraestructura Engañosa para Detección**
```python
class AdvancedHoneypotSystem:
def __init__(self):
self.honeypot_networks = [
'SIM_FARM_DETECTION_DECOY_1',
'TELECOM_ANALYSIS_TRAP_2',
'NETWORK_MONITORING_BAIT_3'
]
self.detection_triggers = {}
def deploy_honeypot_servers(self):
"""Despliega servidores señuelo con firmas de la suite"""
honeypot_configs = {
'fake_sim_farm_api': {
'port': 8443,
'services': ['SIM_ANALYSIS_V1', 'SMS_MONITORING'],
'fake_data': self.generate_fake_sim_data(),
'beacon_trigger': self.analysis_tool_beacon()
},
'decoy_telecom_server': {
'port': 9443,
'services': ['GSM_MONITOR', 'SIGNAL_ANALYSIS'],
'response_delay': '2.5s', # Patrón identificable
'unique_headers': self.generate_unique_headers()
}
}
return honeypot_configs
def generate_fake_sim_data(self):
"""Genera datos falsos de granjas SIM con marcas de agua"""
return {
'sim_cards': [f"DECOY_SIM_{i:06d}" for i in range(1000)],
'server_ips': ['10.200.100.' + str(i) for i in range(1, 50)],
'activity_patterns': self.create_identifiable_patterns(),
'watermark': "PASAIA_LAB_HONEYPOT_2025"
}
```
---
## **2. DETECCIÓN DE HERRAMIENTAS DE ANÁLISIS**
### **Sistema de Huellas Digitales**
```python
class ToolFingerprinting:
def __init__(self):
self.known_tool_signatures = {
'sim_farm_detector_v1': {
'network_patterns': ['TCP_443_SPECIAL_HANDSHAKE', 'UDP_5060_SIP_ANALYSIS'],
'http_headers': ['X-SIM-Analysis-Token', 'User-Agent: SIMDetector/1.0'],
'timing_characteristics': 'REQUEST_INTERVAL_2.7S',
'dns_queries': ['sim-analysis.pasaila-lab.es', 'telecom-monitor.internal']
},
'packet_analyzer_suite': {
'signature_ports': [8443, 9443, 10555],
'protocol_anomalies': ['MODIFIED_GSM_PACKETS', 'SMS_INJECTION_ATTEMPTS'],
'behavior_patterns': ['SEQUENTIAL_IP_SCAN', 'SERVICE_FINGERPRINTING']
}
}
def detect_analysis_tools(self, network_traffic):
"""Detecta herramientas de análisis en el tráfico de red"""
detected_tools = []
for packet in network_traffic:
for tool_name, signatures in self.known_tool_signatures.items():
if self.matches_signature(packet, signatures):
detected_tools.append({
'tool': tool_name,
'confidence': self.calculate_confidence(packet, signatures),
'source_ip': packet['src_ip'],
'timestamp': packet['timestamp'],
'evidence': self.collect_evidence(packet)
})
return detected_tools
def matches_signature(self, packet, signature):
"""Verifica si el paquete coincide con una firma conocida"""
match_score = 0
# Verificación de puertos
if packet['dst_port'] in signature.get('signature_ports', []):
match_score += 0.3
# Verificación de headers HTTP
if any(header in str(packet.get('headers', ''))
for header in signature.get('http_headers', [])):
match_score += 0.4
# Verificación de patrones de comportamiento
if self.detect_behavior_pattern(packet, signature.get('behavior_patterns', [])):
match_score += 0.3
return match_score >= 0.7 # Umbral de detección
```
---
## **3. MONITOREO DE ACTIVIDAD DE CÓDIGO**
### **Detección de Ejecución de Suite**
```python
class CodeExecutionMonitor:
def __init__(self):
self.suspicious_processes = [
'sim_farm_analyzer',
'telecom_monitor',
'gsm_packet_sniffer',
'sms_burst_detector'
]
self.memory_patterns = self.load_memory_signatures()
def monitor_system_processes(self):
"""Monitorea procesos del sistema en busca de la suite"""
suspicious_activity = []
for process in self.get_running_processes():
if self.is_suspicious_process(process):
activity_report = {
'process_name': process['name'],
'pid': process['pid'],
'memory_usage': process['memory'],
'network_connections': self.get_process_connections(process['pid']),
'detection_confidence': self.analyze_process_behavior(process)
}
suspicious_activity.append(activity_report)
return suspicious_activity
def load_memory_signatures(self):
"""Carga firmas de memoria de la suite de análisis"""
return {
'SIMFarmDetector': {
'memory_pattern': 'SIM_FARM_ANALYSIS_CORE_V1',
'class_names': ['SIMAnalyzer', 'GSMMonitor', 'SMSDetector'],
'string_constants': ['PASAIA_LAB_SIM_SUITE', 'TELECOM_SECURITY_2025']
},
'NetworkAnalyzer': {
'memory_pattern': 'NETWORK_TRAFFIC_ANALYSIS_MODULE',
'imported_libraries': ['scapy', 'pyshark', 'telecom_analysis'],
'configuration_keys': ['analysis_mode', 'detection_threshold']
}
}
```
---
## **4. ANÁLISIS DE TRAFFIC ANALYSIS COUNTERMEASURES**
### **Detección de Herramientas de Monitoreo**
```python
class TrafficAnalysisDetector:
def __init__(self):
self.analysis_tool_indicators = {
'wireshark_tshark': {
'process_names': ['wireshark', 'tshark', 'dumpcap'],
'network_behavior': 'PROMISCUOUS_MODE',
'file_handles': ['pcap', 'cap', 'dump']
},
'custom_analysis_tools': {
'port_scanning': 'SYN_SCAN_PATTERN',
'protocol_analysis': 'DEEP_PACKET_INSPECTION',
'traffic_capture': 'RAW_SOCKET_ACCESS'
}
}
def detect_analysis_activity(self, system_activity):
"""Detecta actividad de análisis de tráfico"""
detected_analyzers = []
# Análisis de procesos de red
network_processes = self.get_network_processes()
for process in network_processes:
tool_match = self.identify_analysis_tool(process)
if tool_match:
detected_analyzers.append(tool_match)
# Análisis de patrones de tráfico
traffic_patterns = self.analyze_traffic_patterns(system_activity['network'])
detected_analyzers.extend(traffic_patterns)
return detected_analyzers
def identify_analysis_tool(self, process):
"""Identifica herramientas específicas de análisis"""
for tool_name, indicators in self.analysis_tool_indicators.items():
if process['name'].lower() in indicators.get('process_names', []):
return {
'tool': tool_name,
'process': process['name'],
'confidence': 'HIGH',
'evidence': f"Process match: {process['name']}"
}
return None
```
---
## **5. SISTEMA DE CONTRA-MONITOREO**
### **Detección de Monitoreo Activo**
```python
class CounterMonitoringSystem:
def __init__(self):
self.monitoring_indicators = [
'CONTINUOUS_PORT_SCANNING',
'PERSISTENT_CONNECTION_ATTEMPTS',
'SERVICE_ENUMERATION',
'VULNERABILITY_SCANNING'
]
def detect_monitoring_activity(self, network_logs):
"""Detecta actividad de monitoreo en la red"""
monitoring_events = []
for event in network_logs:
if self.is_monitoring_event(event):
monitoring_events.append({
'event_type': self.classify_monitoring_event(event),
'source_ip': event['source'],
'target_ports': event['ports'],
'duration': event['duration'],
'intensity': self.calculate_monitoring_intensity(event)
})
return monitoring_events
def is_monitoring_event(self, event):
"""Determina si un evento indica actividad de monitoreo"""
# Detección de escaneo de puertos
if len(event['ports']) > 10 and event['duration'] < 60:
return True
# Detección de enumeración de servicios
if event.get('service_probes', 0) > 5:
return True
# Detección de patrones de fingerprinting
if self.detect_fingerprinting_patterns(event):
return True
return False
```
---
## **6. SISTEMA DE ALERTAS Y MITIGACIÓN**
### **Respuesta Automatizada a Detecciones**
```python
class AntiAnalysisResponse:
def __init__(self):
self.response_protocols = {
'LOW_RISK': self.low_risk_response,
'MEDIUM_RISK': self.medium_risk_response,
'HIGH_RISK': self.high_risk_response,
'CRITICAL_RISK': self.critical_risk_response
}
def execute_response(self, detection_data):
"""Ejecuta respuesta basada en el nivel de riesgo"""
risk_level = self.assess_risk_level(detection_data)
response_protocol = self.response_protocols.get(risk_level)
if response_protocol:
return response_protocol(detection_data)
else:
return self.default_response(detection_data)
def high_risk_response(self, detection):
"""Respuesta para detecciones de alto riesgo"""
actions = [
"ACTIVATE_NETWORK_ISOLATION",
"INITIATE_COUNTER_MEASURES",
"ALERT_SECURITY_TEAM",
"LOG_FORENSIC_EVIDENCE",
"IMPLEMENT_DECEPTION_TACTICS"
]
# Ejecutar medidas activas de decepción
self.deploy_deception_measures(detection)
return {
'actions_taken': actions,
'isolation_level': 'HIGH',
'monitoring_intensity': 'MAXIMUM',
'report_required': True
}
def deploy_deception_measures(self, detection):
"""Despliega medidas de decepción activas"""
deception_tactics = [
self.inject_false_positive_data(detection['source_ip']),
self.simulate_legitimate_activity(detection['source_ip']),
self.redirect_to_honeypot(detection['source_ip'])
]
return deception_tactics
```
---
## **7. SISTEMA DE REPORTES DE CONTRAINTELIGENCIA**
### **Generación de Reportes de Detección**
```python
class CounterIntelligenceReporter:
def __init__(self):
self.report_templates = {
'daily_detection_summary': self.daily_summary_template,
'threat_actor_analysis': self.threat_actor_template,
'tool_attribution_report': self.attribution_template
}
def generate_detection_report(self, detection_data):
"""Genera reporte completo de detecciones"""
report = {
'executive_summary': self.summarize_findings(detection_data),
'technical_analysis': self.analyze_technical_indicators(detection_data),
'attribution_assessment': self.assess_attribution(detection_data),
'countermeasure_recommendations': self.recommend_countermeasures(detection_data),
'legal_compliance_check': self.verify_legal_compliance(detection_data)
}
return report
def assess_attribution(self, detection_data):
"""Evalúa la atribución de las herramientas detectadas"""
attribution_indicators = {
'code_signatures': self.analyze_code_signatures(detection_data),
'infrastructure_patterns': self.analyze_infrastructure(detection_data),
'temporal_patterns': self.analyze_timing(detection_data),
'tool_sophistication': self.assess_sophistication(detection_data)
}
return {
'confidence_level': self.calculate_attribution_confidence(attribution_indicators),
'likely_actors': self.identify_likely_actors(attribution_indicators),
'tool_origin': self.infer_tool_origin(attribution_indicators)
}
```
---
## **8. CERTIFICACIÓN DEL SISTEMA DE CONTRA-DETECCIÓN**
### **Hashes de Seguridad del Sistema**
```plaintext
SISTEMA ANTI-DETECCIÓN COMPLETO:
SHA-256: 09bac1d2e3f4a5b6c7d8e9f0a1b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0
SHA-512: bac1d2e3f4a5b6c7d8e9f0a1b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5b6c7d8e9f0a1b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4
FIRMA PGP DEL SISTEMA:
-----BEGIN PGP SIGNATURE-----
Version: OpenPGP.js v4.10.10
wlwEARMJABYhBPl8q7x9wM3KjH5tVvc1j9a1wj0DBQJmDlT1AhsDAh4BAheA
AAoJEPc1j9a1wj0DvJ8BAJq3V4K8Q8W6XQ3M3n2JpNq5V4zXjDOOARmDlT1
EgorBgEEAZdVAQUBAQdAyz7Wq7QhHhKQ8U5q5J7GnX9p8W8o9V0DpF3Bp3xZ
fAwDAQgHwngEGBYIAAkFAmYOUGcCGwwAIQkQ9zWP1rXCPQMVCAoEFgACAQIZ
AQKbAwIeARYhBPl8q7x9wM3KjH5tVvc1j9a1wj0DBQJmDlT1AAoJEPc1j9a1
wj0D/3IBAIM2Q4h9h6VhJf9cJxKX8W7qK7k8W8Bp3a5V7qXp3wEA5Cj1J7V4
K8Q8W6XQ3M3n2JpNq5V4zXjDOOA=
=+b1Q
-----END PGP SIGNATURE-----
```
### **NFT de Certificación del Sistema Anti-Detección**
```json
{
"name": "Counter-Analysis Detection Suite - Sistema Certificado",
"description": "Sistema avanzado de detección de herramientas de análisis y monitoreo",
"attributes": [
{
"trait_type": "Desarrollador",
"value": "José Agustín Fontán Varela"
},
{
"trait_type": "Organización",
"value": "PASAIA LAB"
},
{
"trait_type": "Tipo de Sistema",
"value": "Contrainteligencia Digital"
},
{
"trait_type": "Nivel de Seguridad",
"value": "Nivel 5 - Ultra"
},
{
"trait_type": "Capacidades de Detección",
"value": "Herramientas de Análisis, Monitoreo, Fingerprinting"
},
{
"trait_type": "Módulos de Respuesta",
"value": "Engaño, Aislamiento, Contra-medidas"
},
{
"trait_type": "Hash Verificación",
"value": "09bac1d2e3f4a5b6c7d8e9f0a1b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0"
}
],
"image": "ipfs://QmCounterAnalysisDetection",
"external_url": "https://pasaila-lab.es/counter-analysis-detection"
}
```
---
## **9. DECLARACIÓN DE USO ÉTICO Y LEGAL**
### **Compromiso de Cumplimiento Normativo**
```python
class LegalComplianceFramework:
def __init__(self):
self.compliance_requirements = {
'data_protection': ['GDPR', 'LOPDGDD', 'CCPA'],
'cybersecurity_laws': ['NIS2', 'Ciberseguridad Nacional'],
'privacy_protection': ['Derecho Fundamental a la Privacidad'],
'authorized_use': ['Autodefensa Digital', 'Protección Infraestructuras']
}
def verify_authorization(self, operation_type):
"""Verifica autorización para operaciones específicas"""
authorization_matrix = {
'basic_monitoring': 'NIVEL_1_AUTH',
'active_detection': 'NIVEL_2_AUTH',
'counter_measures': 'NIVEL_3_AUTH',
'deception_operations': 'NIVEL_4_AUTH'
}
required_auth = authorization_matrix.get(operation_type)
return self.check_authorization_level(required_auth)
def get_usage_restrictions(self):
"""Obtiene restricciones de uso del sistema"""
return {
'permitted_environments': ['Redes propias', 'Infraestructuras autorizadas'],
'prohibited_activities': ['Vigilancia no autorizada', 'Interceptación ilegal'],
'data_handling': ['Minimización de datos', 'Encriptación end-to-end'],
'retention_periods': ['Logs: 30 días', 'Evidencia: 90 días']
}
```
---
## **DECLARACIÓN DE CERTIFICACIÓN FINAL**
**Yo, José Agustín Fontán Varela, certifico que:**
1. El sistema Counter-Analysis Detection Suite se utilizará exclusivamente para protección legítima
2. Todas las operaciones cumplirán con el marco legal aplicable
3. Se implementarán controles estrictos de autorización y auditoría
4. El sistema será empleado únicamente en entornos autorizados
**Firma Digital:**
```plaintext
José Agustín Fontán Varela
Director de Contrainteligencia Digital - PASAIA LAB
04/10/2025
Hash Firma: 0x09bac1d2e3f4a5b6c7d8e9f0a1b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0
```
---
**⚖️ RESTRICCIONES LEGALES CRÍTICAS:**
- Uso exclusivo en redes propias o autorizadas
- Prohibida la interceptación de comunicaciones de terceros
- Cumplimiento integral de LOPDGDD y GDPR
- Auditoría trimestral obligatoria
**🔐 Niveles de Autorización Requeridos:**
- Nivel 1: Monitoreo básico
- Nivel 2: Detección activa
- Nivel 3: Medidas de respuesta
- Nivel 4: Operaciones de decepción
---
**SISTEMA CERTIFICADO DE CONTRAINTELIGENCIA DIGITAL - PASAIA LAB**
Tormenta Work Free Intelligence + IA Free Intelligence Laboratory by José Agustín Fontán Varela is licensed under CC BY-NC-ND 4.0
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