""" ATOM Enterprise Security Service Advanced enterprise-grade security with AI-powered threat detection and compliance automation """ import asyncio import base64 from collections import Counter, defaultdict from dataclasses import asdict, dataclass from datetime import datetime, timedelta, timezone from enum import Enum import hashlib from ipaddress import ip_address, ip_network import json import logging import os import re import time from typing import Any, Callable, Dict, List, Optional, Tuple, Union import aiohttp from cryptography.fernet import Fernet from cryptography.hazmat.primitives import hashes from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC import geoip2.database import httpx import jwt import numpy as np import pandas as pd from core.circuit_breaker import circuit_breaker from core.rate_limiter import rate_limiter, should_retry, calculate_backoff from core.audit_logger import log_integration_call, log_integration_error, log_integration_attempt, log_integration_complete from fastapi import HTTPException # Import existing ATOM services try: from ai_enhanced_service import ( AIModelType, AIRequest, AIResponse, AIServiceType, AITaskType, ai_enhanced_service, ) from atom_ai_integration import atom_ai_integration from atom_ingestion_pipeline import AtomIngestionPipeline from atom_memory_service import AtomMemoryService from atom_search_service import AtomSearchService from atom_workflow_service import AtomWorkflowService except ImportError as e: logging.warning(f"Enterprise security services not available: {e}") # Configure logging logger = logging.getLogger(__name__) class SecurityLevel(Enum): """Security levels for enterprise""" BASIC = "basic" STANDARD = "standard" ADVANCED = "advanced" ENTERPRISE = "enterprise" GOVERNMENT = "government" class ComplianceStandard(Enum): """Compliance standards""" GDPR = "gdpr" CCPA = "ccpa" HIPAA = "hipaa" SOX = "sox" SOC2 = "soc2" ISO27001 = "iso27001" PCI_DSS = "pci_dss" NIST = "nist" FEDRAMP = "fedramp" class ThreatType(Enum): """Threat types for detection""" SQL_INJECTION = "sql_injection" XSS = "xss" CSRF = "csrf" AUTH_BYPASS = "auth_bypass" PRIVILEGE_ESCALATION = "privilege_escalation" DATA_EXFILTRATION = "data_exfiltration" DDoS = "ddos" MALWARE = "malware" PHISHING = "phishing" INSIDER_THREAT = "insider_threat" ANOMALOUS_BEHAVIOR = "anomalous_behavior" COMPROMISED_ACCOUNT = "compromised_account" class AuditEventType(Enum): """Audit event types""" USER_LOGIN = "user_login" USER_LOGOUT = "user_logout" ACCESS_GRANTED = "access_granted" ACCESS_DENIED = "access_denied" DATA_ACCESS = "data_access" DATA_MODIFICATION = "data_modification" FILE_UPLOAD = "file_upload" FILE_DOWNLOAD = "file_download" MESSAGE_SENT = "message_sent" WORKFLOW_EXECUTED = "workflow_executed" CONFIG_CHANGED = "config_changed" SECURITY_ALERT = "security_alert" COMPLIANCE_CHECK = "compliance_check" @dataclass class SecurityPolicy: """Security policy data model""" policy_id: str name: str description: str security_level: SecurityLevel compliance_standards: List[ComplianceStandard] rules: List[Dict[str, Any]] enforcement_actions: List[str] exceptions: List[str] created_at: datetime updated_at: datetime created_by: str is_active: bool = True version: int = 1 @dataclass class ThreatDetection: """Threat detection data model""" detection_id: str threat_type: ThreatType severity: str confidence: float source_ip: str user_id: str session_id: str timestamp: datetime description: str indicators: List[str] mitigated: bool = False mitigation_actions: List[str] = None metadata: Dict[str, Any] = None @dataclass class ComplianceReport: """Compliance report data model""" report_id: str standard: ComplianceStandard period: str overall_score: float findings: List[Dict[str, Any]] recommendations: List[str] artifacts: List[str] generated_at: datetime generated_by: str @dataclass class SecurityAudit: """Security audit data model""" audit_id: str event_type: AuditEventType user_id: str resource: str action: str result: str ip_address: str user_agent: str timestamp: datetime metadata: Dict[str, Any] = None class AtomEnterpriseSecurityService: """Enterprise-grade security service with AI-powered threat detection""" def __init__(self, tenant_id: str = "default", config: Dict[str, Any] = None): if config is None: config = {} self.config = config self.db = config.get('database') self.cache = config.get('cache') self.ai_service = config.get('ai_service') # Security configurations self.security_config = { 'encryption_key': config.get('encryption_key') or self._generate_encryption_key(), 'session_timeout': config.get('session_timeout', 3600), # 1 hour 'max_login_attempts': config.get('max_login_attempts', 5), 'lockout_duration': config.get('lockout_duration', 900), # 15 minutes 'password_policy': config.get('password_policy', { 'min_length': 12, 'require_upper': True, 'require_lower': True, 'require_numbers': True, 'require_special': True, 'prevent_reuse': 5 }), 'geoip_database': config.get('geoip_database', 'GeoLite2-City.mmdb'), 'threat_intelligence_apis': config.get('threat_intelligence_apis', []), 'ai_threat_detection': config.get('ai_threat_detection', True), 'compliance_standards': config.get('compliance_standards', [ ComplianceStandard.GDPR, ComplianceStandard.CCPA, ComplianceStandard.SOC2, ComplianceStandard.ISO27001 ]) } # Initialize encryption self.cipher_suite = Fernet(self.security_config['encryption_key']) # Security state self.active_policies: Dict[str, SecurityPolicy] = {} self.threat_detections: List[ThreatDetection] = [] self.audit_logs: List[SecurityAudit] = [] self.compliance_reports: Dict[str, ComplianceReport] = {} # IP and session management self.blocked_ips: Dict[str, datetime] = {} self.active_sessions: Dict[str, Dict[str, Any]] = {} self.user_security_contexts: Dict[str, Dict[str, Any]] = {} # Threat detection patterns self.malicious_patterns = self._load_malicious_patterns() self.anomaly_baselines = {} self.threat_intelligence_cache = {} # HTTP sessions for security APIs self.http_session = aiohttp.ClientSession( timeout=aiohttp.ClientTimeout(total=30) ) # Performance metrics self.security_metrics = { 'total_threats_detected': 0, 'threats_mitigated': 0, 'audit_events_logged': 0, 'compliance_checks_passed': 0, 'security_policies_enforced': 0, 'false_positives': 0, 'average_threat_detection_time': 0.0 } logger.info("Enterprise Security Service initialized") async def initialize(self) -> bool: """Initialize enterprise security service""" try: # Initialize encryption await self._initialize_encryption() # Load security policies await self._load_security_policies() # Initialize threat detection await self._initialize_threat_detection() # Start security monitoring await self._start_security_monitoring() # Initialize compliance monitoring await self._initialize_compliance_monitoring() logger.info("Enterprise Security Service initialized successfully") return True except Exception as e: logger.error(f"Error initializing enterprise security service: {e}") return False async def create_security_policy(self, policy_data: Dict[str, Any], user_id: str) -> Dict[str, Any]: """Create enterprise security policy""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "initialize", locals()) try: # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) policy_id = f"policy_{int(time.time())}_{hashlib.md5(policy_data['name'].encode()).hexdigest()[:8]}" security_policy = SecurityPolicy( policy_id=policy_id, name=policy_data['name'], description=policy_data['description'], security_level=SecurityLevel(policy_data['security_level']), compliance_standards=[ComplianceStandard(standard) for standard in policy_data['compliance_standards']], rules=policy_data['rules'], enforcement_actions=policy_data['enforcement_actions'], exceptions=policy_data.get('exceptions', []), created_at=datetime.utcnow(), updated_at=datetime.utcnow(), created_by=user_id ) # Validate policy validation_result = await self._validate_security_policy(security_policy) if not validation_result['valid']: return { 'ok': False, 'error': f"Policy validation failed: {validation_result['errors']}" } # Store policy self.active_policies[policy_id] = security_policy # Store in database if self.db: await self.db.store_security_policy(asdict(security_policy)) # Log audit event await self._log_security_audit( event_type=AuditEventType.CONFIG_CHANGED, user_id=user_id, resource='security_policy', action='create', result='success', metadata={'policy_id': policy_id, 'policy_name': policy_data['name']} ) return { 'ok': True, 'policy_id': policy_id, 'policy': asdict(security_policy), 'message': "Security policy created successfully" } except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) logger.error(f"Error creating security policy: {e}") return {'ok': False, 'error': str(e)} async def detect_threat(self, event_data: Dict[str, Any]) -> ThreatDetection: """Detect security threats using AI and pattern matching""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "create_security_policy", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) try: start_time = time.time() # Extract event metadata source_ip = event_data.get('source_ip') user_id = event_data.get('user_id') session_id = event_data.get('session_id') event_type = event_data.get('event_type') # Pattern-based detection pattern_threats = await self._pattern_based_detection(event_data) # Behavioral anomaly detection anomaly_threats = await self._behavioral_anomaly_detection(event_data) # AI-powered threat detection ai_threats = [] if self.security_config['ai_threat_detection'] and self.ai_service: ai_threats = await self._ai_threat_detection(event_data) # Consolidate threats all_threats = pattern_threats + anomaly_threats + ai_threats # Create threat detection records threat_detections = [] for threat_info in all_threats: detection_id = f"threat_{int(time.time())}_{hashlib.md5(str(threat_info).encode()).hexdigest()[:8]}" threat_detection = ThreatDetection( detection_id=detection_id, threat_type=ThreatType(threat_info['type']), severity=threat_info['severity'], confidence=threat_info['confidence'], source_ip=source_ip, user_id=user_id, session_id=session_id, timestamp=datetime.utcnow(), description=threat_info['description'], indicators=threat_info.get('indicators', []), metadata=threat_info.get('metadata', {}) ) threat_detections.append(threat_detection) self.threat_detections.append(threat_detection) # Mitigate high-severity threats for threat in threat_detections: if threat.severity in ['critical', 'high']: await self._mitigate_threat(threat) # Update metrics detection_time = time.time() - start_time self.security_metrics['total_threats_detected'] += len(threat_detections) self.security_metrics['average_threat_detection_time'] = ( (self.security_metrics['average_threat_detection_time'] * (self.security_metrics['total_threats_detected'] - len(threat_detections)) + detection_time) / self.security_metrics['total_threats_detected'] ) return threat_detections[0] if threat_detections else None except Exception as e: logger.error(f"Error detecting threat: {e}") return None async def audit_event(self, event_data: Dict[str, Any]) -> SecurityAudit: """Audit security events""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "detect_threat", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) try: audit_id = f"audit_{int(time.time())}_{hashlib.md5(str(event_data).encode()).hexdigest()[:8]}" security_audit = SecurityAudit( audit_id=audit_id, event_type=AuditEventType(event_data['event_type']), user_id=event_data['user_id'], resource=event_data['resource'], action=event_data['action'], result=event_data['result'], ip_address=event_data['ip_address'], user_agent=event_data.get('user_agent', ''), timestamp=datetime.utcnow(), metadata=event_data.get('metadata', {}) ) # Store audit log self.audit_logs.append(security_audit) # Store in database if self.db: await self.db.store_security_audit(asdict(security_audit)) # Update metrics self.security_metrics['audit_events_logged'] += 1 # Check compliance await self._check_compliance_for_event(security_audit) return security_audit except Exception as e: logger.error(f"Error auditing event: {e}") return None async def check_compliance(self, standard: ComplianceStandard, period: str = 'monthly') -> ComplianceReport: """Generate compliance report""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "audit_event", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) try: report_id = f"compliance_{standard.value}_{period}_{int(time.time())}" # Get compliance data compliance_data = await self._get_compliance_data(standard, period) # AI-powered compliance analysis compliance_analysis = await self._ai_compliance_analysis(standard, compliance_data) # Calculate overall score overall_score = self._calculate_compliance_score(compliance_analysis) # Generate findings and recommendations findings = compliance_analysis.get('findings', []) recommendations = compliance_analysis.get('recommendations', []) compliance_report = ComplianceReport( report_id=report_id, standard=standard, period=period, overall_score=overall_score, findings=findings, recommendations=recommendations, artifacts=compliance_analysis.get('artifacts', []), generated_at=datetime.utcnow(), generated_by='enterprise_security_service' ) # Store report self.compliance_reports[report_id] = compliance_report # Update metrics if overall_score >= 80: self.security_metrics['compliance_checks_passed'] += 1 return compliance_report except Exception as e: logger.error(f"Error checking compliance: {e}") return None async def encrypt_data(self, data: str, context: Dict[str, Any] = None) -> str: """Encrypt sensitive data""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "check_compliance", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) try: # Add context to data if provided if context: context_data = json.dumps(context) data_with_context = f"{data}|{context_data}" else: data_with_context = data # Encrypt data encrypted_data = self.cipher_suite.encrypt(data_with_context.encode()) return base64.b64encode(encrypted_data).decode() except Exception as e: logger.error(f"Error encrypting data: {e}") raise async def decrypt_data(self, encrypted_data: str) -> Tuple[str, Optional[Dict[str, Any]]]: """Decrypt sensitive data""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "encrypt_data", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) try: # Decode and decrypt encrypted_bytes = base64.b64decode(encrypted_data.encode()) decrypted_data = self.cipher_suite.decrypt(encrypted_bytes).decode() # Split data and context if '|' in decrypted_data: data, context_json = decrypted_data.split('|', 1) context = json.loads(context_json) if context_json else None return data, context else: return decrypted_data, None except Exception as e: logger.error(f"Error decrypting data: {e}") raise async def validate_password(self, password: str, user_context: Dict[str, Any] = None) -> Dict[str, Any]: """Validate password against security policy""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "decrypt_data", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) try: password_policy = self.security_config['password_policy'] validation_result = { 'valid': True, 'score': 0, 'issues': [], 'suggestions': [] } # Check length if len(password) < password_policy['min_length']: validation_result['valid'] = False validation_result['issues'].append(f"Password must be at least {password_policy['min_length']} characters") else: validation_result['score'] += 20 # Check uppercase if password_policy['require_upper'] and not re.search(r'[A-Z]', password): validation_result['valid'] = False validation_result['issues'].append("Password must contain at least one uppercase letter") elif re.search(r'[A-Z]', password): validation_result['score'] += 20 # Check lowercase if password_policy['require_lower'] and not re.search(r'[a-z]', password): validation_result['valid'] = False validation_result['issues'].append("Password must contain at least one lowercase letter") elif re.search(r'[a-z]', password): validation_result['score'] += 20 # Check numbers if password_policy['require_numbers'] and not re.search(r'\d', password): validation_result['valid'] = False validation_result['issues'].append("Password must contain at least one number") elif re.search(r'\d', password): validation_result['score'] += 20 # Check special characters if password_policy['require_special'] and not re.search(r'[!@#$%^&*(),.?":{}|<>]', password): validation_result['valid'] = False validation_result['issues'].append("Password must contain at least one special character") elif re.search(r'[!@#$%^&*(),.?":{}|<>]', password): validation_result['score'] += 20 # Check for common patterns common_patterns = ['password', '123456', 'qwerty', 'admin', 'user'] for pattern in common_patterns: if pattern.lower() in password.lower(): validation_result['valid'] = False validation_result['issues'].append(f"Password contains common pattern: {pattern}") break # Add suggestions if validation_result['score'] < 80: validation_result['suggestions'].append("Consider using a longer password") validation_result['suggestions'].append("Use a mix of different character types") validation_result['suggestions'].append("Avoid common words and patterns") return validation_result except Exception as e: logger.error(f"Error validating password: {e}") return {'valid': False, 'error': str(e)} async def analyze_user_behavior(self, user_id: str, timeframe: str = '24h') -> Dict[str, Any]: """Analyze user behavior for security threats""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "validate_password", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) try: # Get user activity data user_activities = await self._get_user_activities(user_id, timeframe) # Calculate behavioral metrics behavior_metrics = { 'login_frequency': self._calculate_login_frequency(user_activities), 'access_patterns': self._analyze_access_patterns(user_activities), 'data_access_volume': self._calculate_data_access_volume(user_activities), 'unusual_activities': self._detect_unusual_activities(user_activities), 'risk_score': 0.0, 'anomalies': [] } # AI-powered behavior analysis if self.ai_service: behavior_analysis = await self._ai_behavior_analysis(user_id, user_activities) behavior_metrics['risk_score'] = behavior_analysis.get('risk_score', 0.0) behavior_metrics['anomalies'] = behavior_analysis.get('anomalies', []) return behavior_metrics except Exception as e: logger.error(f"Error analyzing user behavior: {e}") return {'error': str(e)} # Private methods for threat detection async def _pattern_based_detection(self, event_data: Dict[str, Any]) -> List[Dict[str, Any]]: """Pattern-based threat detection""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "analyze_user_behavior", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) threats = [] # Check against malicious patterns for pattern_name, pattern_info in self.malicious_patterns.items(): if self._matches_pattern(event_data, pattern_info): threats.append({ 'type': pattern_info['threat_type'], 'severity': pattern_info['severity'], 'confidence': pattern_info['confidence'], 'description': f"Pattern match detected: {pattern_name}", 'indicators': [pattern_name] }) return threats async def _behavioral_anomaly_detection(self, event_data: Dict[str, Any]) -> List[Dict[str, Any]]: """Behavioral anomaly detection""" threats = [] user_id = event_data.get('user_id') if not user_id: return threats # Get user baseline baseline = self.anomaly_baselines.get(user_id, {}) # Check for anomalies anomalies = self._detect_anomalies(event_data, baseline) for anomaly in anomalies: threats.append({ 'type': ThreatType.ANOMALOUS_BEHAVIOR.value, 'severity': anomaly['severity'], 'confidence': anomaly['confidence'], 'description': anomaly['description'], 'indicators': anomaly['indicators'] }) return threats async def _ai_threat_detection(self, event_data: Dict[str, Any]) -> List[Dict[str, Any]]: """AI-powered threat detection""" threats = [] if not self.ai_service: return threats # Create AI request for threat detection ai_request = AIRequest( request_id=f"threat_ai_{int(time.time())}", task_type=AITaskType.CONVERSATION_ANALYSIS, # Using conversation analysis for threat detection model_type=AIModelType.GPT_4, service_type=AIServiceType.OPENAI, input_data=event_data, context={ 'task': 'threat_detection', 'event_type': event_data.get('event_type'), 'security_level': 'enterprise' }, platform='security' ) # Process AI request ai_response = await self.ai_service.process_ai_request(ai_request) if ai_response.ok and ai_response.confidence > 0.7: # Parse AI threat detection results ai_threats = self._parse_ai_threat_results(ai_response.output_data) threats.extend(ai_threats) except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) return {'ok': False, 'error': str(e)} logger.error(f"Error in AI threat detection: {e}") return threats async def _mitigate_threat(self, threat: ThreatDetection): """Mitigate detected threat""" mitigation_actions = [] # Block IP if high severity if threat.severity in ['critical', 'high'] and threat.source_ip: await self._block_ip(threat.source_ip, duration=3600) # 1 hour mitigation_actions.append(f"Blocked IP: {threat.source_ip}") # Terminate session if compromised if threat.threat_type == ThreatType.COMPROMISED_ACCOUNT and threat.session_id: await self._terminate_session(threat.session_id) mitigation_actions.append(f"Terminated session: {threat.session_id}") # Lock user account if insider threat if threat.threat_type == ThreatType.INSIDER_THREAT and threat.user_id: await self._lock_user_account(threat.user_id) mitigation_actions.append(f"Locked user account: {threat.user_id}") # Update threat record threat.mitigated = True threat.mitigation_actions = mitigation_actions # Update metrics self.security_metrics['threats_mitigated'] += 1 # Log security event await self._log_security_audit( event_type=AuditEventType.SECURITY_ALERT, user_id='security_system', resource='threat_mitigation', action='mitigate', result='success', metadata={ 'threat_id': threat.detection_id, 'threat_type': threat.threat_type.value, 'mitigation_actions': mitigation_actions } ) except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) return {'ok': False, 'error': str(e)} logger.error(f"Error mitigating threat: {e}") # Private methods for compliance async def _get_compliance_data(self, standard: ComplianceStandard, period: str) -> Dict[str, Any]: """Get compliance data for analysis""" # Mock implementation - would pull actual compliance data return { 'standard': standard.value, 'period': period, 'audit_logs': self.audit_logs[-100:], # Last 100 audit logs 'security_policies': list(self.active_policies.values()), 'threat_detections': self.threat_detections[-50], # Last 50 threats 'user_activities': [] # Would pull user activities } async def _ai_compliance_analysis(self, standard: ComplianceStandard, compliance_data: Dict[str, Any]) -> Dict[str, Any]: """AI-powered compliance analysis""" if not self.ai_service: return { 'findings': [], 'recommendations': [], 'score': 0.0 } # Create AI request for compliance analysis ai_request = AIRequest( request_id=f"compliance_ai_{int(time.time())}", task_type=AITaskType.CONTENT_GENERATION, # Using content generation for compliance analysis model_type=AIModelType.GPT_4, service_type=AIServiceType.OPENAI, input_data=compliance_data, context={ 'task': 'compliance_analysis', 'standard': standard.value, 'requirements': self._get_compliance_requirements(standard) }, platform='compliance' ) # Process AI request ai_response = await self.ai_service.process_ai_request(ai_request) if ai_response.ok: return self._parse_ai_compliance_results(ai_response.output_data, standard) else: return { 'findings': [], 'recommendations': [], 'score': 0.0 } except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) return {'ok': False, 'error': str(e)} logger.error(f"Error in AI compliance analysis: {e}") return { 'findings': [], 'recommendations': [], 'score': 0.0 } def _calculate_compliance_score(self, compliance_analysis: Dict[str, Any]) -> float: """Calculate overall compliance score""" findings = compliance_analysis.get('findings', []) # Base score of 100 score = 100.0 # Deduct points for findings for finding in findings: severity = finding.get('severity', 'medium') if severity == 'critical': score -= 20 elif severity == 'high': score -= 15 elif severity == 'medium': score -= 10 elif severity == 'low': score -= 5 return max(0.0, score) except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) return {'ok': False, 'error': str(e)} logger.error(f"Error calculating compliance score: {e}") return 0.0 # Private helper methods def _generate_encryption_key(self) -> bytes: """Generate encryption key""" password = os.urandom(32) salt = os.urandom(16) kdf = PBKDF2HMAC( algorithm=hashes.SHA256(), length=32, salt=salt, iterations=100000, ) key = base64.urlsafe_b64encode(kdf.derive(password)) return key def _load_malicious_patterns(self) -> Dict[str, Any]: """Load malicious patterns for detection""" # Mock patterns - would load from database return { 'sql_injection': { 'threat_type': ThreatType.SQL_INJECTION.value, 'severity': 'high', 'confidence': 0.9, 'patterns': [r"('|(.*--)|(;)|(\b(ALTER|CREATE|DELETE|DROP|EXEC(UTE)?|INSERT( +INTO)?|MERGE|SELECT|UPDATE)\b)"] }, 'xss': { 'threat_type': ThreatType.XSS.value, 'severity': 'medium', 'confidence': 0.8, 'patterns': [r"]*>.*?", r"javascript:", r"on\w+\s*="] }, 'path_traversal': { 'threat_type': ThreatType.AUTH_BYPASS.value, 'severity': 'high', 'confidence': 0.85, 'patterns': [r"\.\.[/\\]", r"%2e%2e[/%5c]", r"\.\./"] } } def _matches_pattern(self, event_data: Dict[str, Any], pattern_info: Dict[str, Any]) -> bool: """Check if event data matches malicious pattern""" for pattern in pattern_info.get('patterns', []): # Check against different fields for field in ['content', 'user_input', 'url', 'headers']: field_value = str(event_data.get(field, '')) if re.search(pattern, field_value, re.IGNORECASE): return True return False async def _block_ip(self, ip_address: str, duration: int): """Block IP address""" self.blocked_ips[ip_address] = datetime.utcnow() + timedelta(seconds=duration) # Log security event await self._log_security_audit( event_type=AuditEventType.SECURITY_ALERT, user_id='security_system', resource='ip_blocking', action='block', result='success', metadata={'ip_address': ip_address, 'duration': duration} ) async def _terminate_session(self, session_id: str): """Terminate user session""" if session_id in self.active_sessions: del self.active_sessions[session_id] # Log security event await self._log_security_audit( event_type=AuditEventType.SECURITY_ALERT, user_id='security_system', resource='session_termination', action='terminate', result='success', metadata={'session_id': session_id} ) async def _lock_user_account(self, user_id: str): """Lock user account""" # Update user security context if user_id in self.user_security_contexts: self.user_security_contexts[user_id]['locked'] = True self.user_security_contexts[user_id]['locked_at'] = datetime.utcnow() # Log security event await self._log_security_audit( event_type=AuditEventType.SECURITY_ALERT, user_id='security_system', resource='user_account', action='lock', result='success', metadata={'user_id': user_id} ) async def _log_security_audit(self, event_type: AuditEventType, user_id: str, resource: str, action: str, result: str, metadata: Dict[str, Any] = None): """Log security audit event""" audit_data = { 'event_type': event_type.value, 'user_id': user_id, 'resource': resource, 'action': action, 'result': result, 'ip_address': 'security_system', 'user_agent': 'enterprise_security_service', 'metadata': metadata or {} } audit = await self.audit_event(audit_data) return audit # Additional private methods would be implemented here async def _initialize_encryption(self): """Initialize encryption system""" logger.info("Initializing encryption system") # Initialize encryption keys and ciphers self.encryption_config = { "algorithm": "AES-256-GCM", "key_rotation_days": 90, "enabled": True } logger.info("Encryption system initialized successfully") except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) return {'ok': False, 'error': str(e)} logger.error(f"Error initializing encryption system: {e}") async def _load_security_policies(self): """Load security policies""" logger.info("Loading security policies") # Load policies from database or configuration self.security_policies = { "password_policy": { "min_length": 12, "require_uppercase": True, "require_lowercase": True, "require_numbers": True, "require_special_chars": True }, "access_policy": { "max_failed_attempts": 5, "lockout_duration_minutes": 30, "session_timeout_minutes": 60 }, "data_policy": { "encryption_at_rest": True, "encryption_in_transit": True, "audit_data_access": True } } logger.info("Security policies loaded successfully") except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) return {'ok': False, 'error': str(e)} logger.error(f"Error loading security policies: {e}") async def _initialize_threat_detection(self): """Initialize threat detection system""" logger.info("Initializing threat detection system") # Initialize threat detection models and rules self.threat_detection_config = { "ai_enabled": True, "rule_based_detection": True, "anomaly_detection": True, "real_time_monitoring": True } logger.info("Threat detection system initialized successfully") except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) return {'ok': False, 'error': str(e)} logger.error(f"Error initializing threat detection system: {e}") async def _start_security_monitoring(self): """Start security monitoring""" logger.info("Starting security monitoring") # Start background monitoring tasks self.monitoring_active = True logger.info("Security monitoring started successfully") except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) return {'ok': False, 'error': str(e)} logger.error(f"Error starting security monitoring: {e}") async def _initialize_compliance_monitoring(self): """Initialize compliance monitoring""" logger.info("Initializing compliance monitoring") # Initialize compliance monitoring for different standards self.compliance_monitoring = { "gdpr": {"enabled": True, "last_check": None}, "hipaa": {"enabled": True, "last_check": None}, "soc2": {"enabled": True, "last_check": None}, "iso27001": {"enabled": True, "last_check": None} } logger.info("Compliance monitoring initialized successfully") except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) logger.error(f"Error initializing compliance monitoring: {e}") async def _validate_security_policy(self, policy: SecurityPolicy) -> Dict[str, Any]: """Validate security policy""" return {'valid': True, 'errors': []} async def _get_user_activities(self, user_id: str, timeframe: str) -> List[Dict[str, Any]]: """Get user activities""" return [] def _calculate_login_frequency(self, activities: List[Dict[str, Any]]) -> float: """Calculate login frequency""" return 0.0 def _analyze_access_patterns(self, activities: List[Dict[str, Any]]) -> Dict[str, Any]: """Analyze access patterns""" return {} def _calculate_data_access_volume(self, activities: List[Dict[str, Any]]) -> int: """Calculate data access volume""" return 0 def _detect_unusual_activities(self, activities: List[Dict[str, Any]]) -> List[Dict[str, Any]]: """Detect unusual activities""" return [] async def _ai_behavior_analysis(self, user_id: str, activities: List[Dict[str, Any]]) -> Dict[str, Any]: """AI-powered behavior analysis""" return {} def _detect_anomalies(self, event_data: Dict[str, Any], baseline: Dict[str, Any]) -> List[Dict[str, Any]]: """Detect anomalies in event data""" return [] def _parse_ai_threat_results(self, ai_output: str) -> List[Dict[str, Any]]: """Parse AI threat detection results""" return [] def _get_compliance_requirements(self, standard: ComplianceStandard) -> List[str]: """Get compliance requirements for standard""" requirements = { ComplianceStandard.GDPR: ['data_protection', 'privacy', 'consent'], ComplianceStandard.HIPAA: ['phi_protection', 'access_control', 'audit_trail'], ComplianceStandard.SOC2: ['security', 'availability', 'confidentiality'], ComplianceStandard.ISO27001: ['information_security', 'risk_management', 'continuous_improvement'] } return requirements.get(standard, []) def _parse_ai_compliance_results(self, ai_output: str, standard: ComplianceStandard) -> Dict[str, Any]: """Parse AI compliance analysis results""" return { 'findings': [], 'recommendations': [], 'score': 0.0 } def _check_compliance_for_event(self, audit_event: SecurityAudit): """Check compliance for audit event""" # Check event against compliance requirements compliance_issues = [] # Example: Check for data access logging if audit_event.action == "data_access" and not audit_event.metadata.get("logged"): compliance_issues.append({ "standard": "SOC2", "requirement": "audit_trail", "issue": "Data access not properly logged" }) # Example: Check for encryption if audit_event.action == "data_export" and not audit_event.metadata.get("encrypted"): compliance_issues.append({ "standard": "GDPR", "requirement": "data_protection", "issue": "Data export not encrypted" }) return compliance_issues except Exception as e: logger.error(f"Operation failed: {e}") log_integration_complete(audit_ctx, error=e) return {'ok': False, 'error': str(e)} logger.error(f"Error checking compliance for event: {e}") return [] async def get_service_info(self) -> Dict[str, Any]: """Get enterprise security service information""" return { "name": "Enterprise Security Service", "version": "6.0.0", "description": "Advanced enterprise-grade security with AI-powered threat detection", "features": [ "multi_platform_integration", "threat_detection", "compliance_automation", "ai_powered_security", "advanced_encryption", "audit_logging", "access_control" ], "supported_platforms": ["slack", "teams", "google_chat", "discord"], "security_level": "enterprise", "status": "ACTIVE" } async def get_security_metrics(self) -> Dict[str, Any]: """Get security service metrics""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "get_service_info", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) return { "total_threats_detected": self.security_metrics['total_threats_detected'], "threats_mitigated": self.security_metrics['threats_mitigated'], "audit_events_logged": self.security_metrics['audit_events_logged'], "compliance_checks_passed": self.security_metrics['compliance_checks_passed'], "security_policies_enforced": self.security_metrics['security_policies_enforced'], "false_positives": self.security_metrics['false_positives'], "average_threat_detection_time": self.security_metrics['average_threat_detection_time'], "active_policies": len(self.active_policies), "blocked_ips": len(self.blocked_ips), "active_sessions": len(self.active_sessions) } async def close(self): """Close enterprise security service""" # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "get_security_metrics", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" ) # Close HTTP session await self.http_session.close() logger.info("Enterprise Security Service closed") # Global enterprise security service instance atom_enterprise_security_service = AtomEnterpriseSecurityService({ 'database': None, # Would be actual database connection 'cache': None, # Would be actual cache client 'ai_service': ai_enhanced_service, 'encryption_key': None, # Would be securely stored 'session_timeout': 3600, 'max_login_attempts': 5, 'lockout_duration': 900, 'password_policy': { 'min_length': 12, 'require_upper': True, 'require_lower': True, 'require_numbers': True, 'require_special': True, 'prevent_reuse': 5 }, 'geoip_database': 'GeoLite2-City.mmdb', 'threat_intelligence_apis': [], 'ai_threat_detection': True, 'compliance_standards': [ ComplianceStandard.GDPR, ComplianceStandard.CCPA, ComplianceStandard.SOC2, ComplianceStandard.ISO27001 ] }) # Start audit logging audit_ctx = log_integration_attempt("atom_enterprise_security", "close", locals()) # Check circuit breaker if not await circuit_breaker.is_enabled("atom_enterprise_security"): logger.warning(f"Circuit breaker is open for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Circuit breaker open")) raise HTTPException( status_code=503, detail=f"Atom_enterprise_security integration temporarily disabled" ) # Check rate limiter is_limited, remaining = await rate_limiter.is_rate_limited("atom_enterprise_security") if is_limited: logger.warning(f"Rate limit exceeded for atom_enterprise_security") log_integration_complete(audit_ctx, error=Exception("Rate limit exceeded")) raise HTTPException( status_code=429, detail=f"Rate limit exceeded for atom_enterprise_security" )