# Aurora AI Framework - Security and Compliance Guide ## 🌟 Overview This comprehensive security and compliance guide covers all aspects of securing the Aurora AI framework, including enterprise-grade security practices, regulatory compliance, audit procedures, and security monitoring for all 27 integrated systems and 74 API endpoints. ## 🔒 Security Architecture ### Security Layers ```yaml # security/architecture.yaml security_layers: network_security: - firewall_configuration - ddos_protection - ssl_tls_termination - network_segmentation application_security: - authentication_authorization - input_validation - output_encoding - session_management data_security: - encryption_at_rest - encryption_in_transit - data_classification - access_controls infrastructure_security: - hardening_standards - vulnerability_management - patch_management - monitoring_logging ``` ### Security Policies ```python # security/security_policies.py class SecurityPolicyManager: def __init__(self): self.policies = { 'password_policy': { 'min_length': 12, 'require_uppercase': True, 'require_lowercase': True, 'require_numbers': True, 'require_symbols': True, 'max_age_days': 90, 'history_count': 12 }, 'session_policy': { 'timeout_minutes': 30, 'max_concurrent_sessions': 3, 'secure_cookies': True, 'csrf_protection': True }, 'api_security': { 'rate_limiting': True, 'requests_per_minute': 1000, 'burst_limit': 100, 'jwt_expiry': 3600, 'refresh_token_expiry': 86400 }, 'data_protection': { 'encryption_algorithm': 'AES-256-GCM', 'key_rotation_days': 90, 'backup_encryption': True, 'audit_retention_days': 2555 } } def validate_password(self, password): """Validate password against security policy""" policy = self.policies['password_policy'] validations = [] # Length validation if len(password) < policy['min_length']: validations.append(f"Password must be at least {policy['min_length']} characters") # Uppercase validation if policy['require_uppercase'] and not any(c.isupper() for c in password): validations.append("Password must contain at least one uppercase letter") # Lowercase validation if policy['require_lowercase'] and not any(c.islower() for c in password): validations.append("Password must contain at least one lowercase letter") # Numbers validation if policy['require_numbers'] and not any(c.isdigit() for c in password): validations.append("Password must contain at least one number") # Symbols validation if policy['require_symbols'] and not any(c in '!@#$%^&*()_+-=[]{}|;:,.<>?' for c in password): validations.append("Password must contain at least one special character") return { 'valid': len(validations) == 0, 'validations': validations } ``` ## 🔐 Authentication and Authorization ### JWT Authentication Implementation ```python # security/authentication.py import jwt import bcrypt from datetime import datetime, timedelta from functools import wraps from flask import request, jsonify, g class AuthenticationManager: def __init__(self, secret_key, algorithm='HS256'): self.secret_key = secret_key self.algorithm = algorithm self.token_expiry = timedelta(hours=1) self.refresh_token_expiry = timedelta(days=7) def hash_password(self, password): """Hash password using bcrypt""" salt = bcrypt.gensalt() hashed = bcrypt.hashpw(password.encode('utf-8'), salt) return hashed.decode('utf-8') def verify_password(self, password, hashed): """Verify password against hash""" return bcrypt.checkpw(password.encode('utf-8'), hashed.encode('utf-8')) def generate_tokens(self, user_id, permissions): """Generate access and refresh tokens""" # Access token access_payload = { 'user_id': user_id, 'permissions': permissions, 'token_type': 'access', 'exp': datetime.utcnow() + self.token_expiry, 'iat': datetime.utcnow() } access_token = jwt.encode( access_payload, self.secret_key, algorithm=self.algorithm ) # Refresh token refresh_payload = { 'user_id': user_id, 'token_type': 'refresh', 'exp': datetime.utcnow() + self.refresh_token_expiry, 'iat': datetime.utcnow() } refresh_token = jwt.encode( refresh_payload, self.secret_key, algorithm=self.algorithm ) return { 'access_token': access_token, 'refresh_token': refresh_token, 'expires_in': int(self.token_expiry.total_seconds()) } def verify_token(self, token): """Verify JWT token""" try: payload = jwt.decode( token, self.secret_key, algorithms=[self.algorithm] ) return payload except jwt.ExpiredSignatureError: return None except jwt.InvalidTokenError: return None def refresh_access_token(self, refresh_token): """Refresh access token using refresh token""" payload = self.verify_token(refresh_token) if not payload or payload.get('token_type') != 'refresh': return None # Get user permissions (from database or cache) user_permissions = self.get_user_permissions(payload['user_id']) # Generate new access token return self.generate_tokens(payload['user_id'], user_permissions) def require_auth(f): """Decorator to require authentication""" @wraps(f) def decorated_function(*args, **kwargs): token = None # Get token from Authorization header auth_header = request.headers.get('Authorization') if auth_header: try: token = auth_header.split(' ')[1] except IndexError: return jsonify({'error': 'Invalid token format'}), 401 # Verify token auth_manager = AuthenticationManager(current_app.config['SECRET_KEY']) payload = auth_manager.verify_token(token) if not payload: return jsonify({'error': 'Invalid or expired token'}), 401 # Store user info in Flask g g.current_user = payload['user_id'] g.user_permissions = payload.get('permissions', []) return f(*args, **kwargs) return decorated_function def require_permission(permission): """Decorator to require specific permission""" def decorator(f): @wraps(f) @require_auth def decorated_function(*args, **kwargs): if permission not in g.user_permissions: return jsonify({'error': 'Insufficient permissions'}), 403 return f(*args, **kwargs) return decorated_function return decorator ``` ### Role-Based Access Control (RBAC) ```python # security/rbac.py class RBACManager: def __init__(self): self.roles = { 'admin': { 'permissions': [ 'system:*', 'data:*', 'models:*', 'users:*', 'security:*', 'monitoring:*' ] }, 'data_scientist': { 'permissions': [ 'data:read', 'data:write', 'models:read', 'models:train', 'models:deploy', 'monitoring:read' ] }, 'analyst': { 'permissions': [ 'data:read', 'models:read', 'monitoring:read', 'reports:read' ] }, 'viewer': { 'permissions': [ 'data:read', 'monitoring:read', 'reports:read' ] } } def get_user_permissions(self, user_id): """Get permissions for a user""" # This would typically query a database # For demonstration, returning admin permissions return self.roles['admin']['permissions'] def check_permission(self, user_id, permission): """Check if user has specific permission""" user_permissions = self.get_user_permissions(user_id) # Check direct permission if permission in user_permissions: return True # Check wildcard permissions for perm in user_permissions: if perm.endswith(':*'): prefix = perm[:-2] if permission.startswith(prefix + ':'): return True return False def assign_role(self, user_id, role): """Assign role to user""" if role not in self.roles: raise ValueError(f"Unknown role: {role}") # This would typically update a database return True ``` ## 🛡️ Data Protection ### Encryption Implementation ```python # security/encryption.py from cryptography.fernet import Fernet from cryptography.hazmat.primitives import hashes from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC import os import base64 class EncryptionManager: def __init__(self): self.key = self._generate_key() self.fernet = Fernet(self.key) def _generate_key(self): """Generate encryption key from environment or create new one""" key_env = os.getenv('ENCRYPTION_KEY') if key_env: return base64.urlsafe_b64decode(key_env.encode()) # Generate new 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 encrypt_data(self, data): """Encrypt data""" if isinstance(data, str): data = data.encode('utf-8') encrypted_data = self.fernet.encrypt(data) return base64.urlsafe_b64encode(encrypted_data).decode('utf-8') def decrypt_data(self, encrypted_data): """Decrypt data""" if isinstance(encrypted_data, str): encrypted_data = encrypted_data.encode('utf-8') try: decoded_data = base64.urlsafe_b64decode(encrypted_data) decrypted_data = self.fernet.decrypt(decoded_data) return decrypted_data.decode('utf-8') except Exception as e: raise ValueError(f"Decryption failed: {str(e)}") def encrypt_sensitive_fields(self, data_dict, sensitive_fields): """Encrypt specific fields in a dictionary""" encrypted_dict = data_dict.copy() for field in sensitive_fields: if field in encrypted_dict and encrypted_dict[field]: encrypted_dict[field] = self.encrypt_data(str(encrypted_dict[field])) return encrypted_dict def decrypt_sensitive_fields(self, data_dict, sensitive_fields): """Decrypt specific fields in a dictionary""" decrypted_dict = data_dict.copy() for field in sensitive_fields: if field in decrypted_dict and decrypted_dict[field]: try: decrypted_dict[field] = self.decrypt_data(decrypted_dict[field]) except ValueError: # Keep original value if decryption fails pass return decrypted_dict ``` ### Data Classification ```python # security/data_classification.py from enum import Enum class DataClassification(Enum): PUBLIC = "public" INTERNAL = "internal" CONFIDENTIAL = "confidential" RESTRICTED = "restricted" class DataClassifier: def __init__(self): self.classification_rules = { 'user_data': { 'email': DataClassification.CONFIDENTIAL, 'phone': DataClassification.CONFIDENTIAL, 'ssn': DataClassification.RESTRICTED, 'credit_card': DataClassification.RESTRICTED, 'address': DataClassification.CONFIDENTIAL, 'name': DataClassification.INTERNAL }, 'system_data': { 'logs': DataClassification.INTERNAL, 'metrics': DataClassification.INTERNAL, 'errors': DataClassification.INTERNAL, 'config': DataClassification.INTERNAL, 'api_keys': DataClassification.RESTRICTED, 'passwords': DataClassification.RESTRICTED }, 'business_data': { 'revenue': DataClassification.CONFIDENTIAL, 'costs': DataClassification.CONFIDENTIAL, 'strategies': DataClassification.CONFIDENTIAL, 'financial_reports': DataClassification.CONFIDENTIAL } } def classify_data(self, data_dict): """Classify data based on field names and values""" classifications = {} for field, value in data_dict.items(): classification = self._classify_field(field, value) classifications[field] = classification return classifications def _classify_field(self, field_name, field_value): """Classify individual field""" # Check field name patterns field_lower = field_name.lower() # Check for PII patterns if any(pattern in field_lower for pattern in ['email', 'mail']): return DataClassification.CONFIDENTIAL if any(pattern in field_lower for pattern in ['phone', 'mobile', 'tel']): return DataClassification.CONFIDENTIAL if any(pattern in field_lower for pattern in ['ssn', 'social_security']): return DataClassification.RESTRICTED if any(pattern in field_lower for pattern in ['credit_card', 'cc', 'card_number']): return DataClassification.RESTRICTED if any(pattern in field_lower for pattern in ['password', 'pwd', 'secret', 'key']): return DataClassification.RESTRICTED # Check value patterns if isinstance(field_value, str): # Email pattern if '@' in field_value and '.' in field_value: return DataClassification.CONFIDENTIAL # Phone pattern if self._is_phone_number(field_value): return DataClassification.CONFIDENTIAL # SSN pattern if self._is_ssn(field_value): return DataClassification.RESTRICTED # Default classification return DataClassification.INTERNAL def _is_phone_number(self, value): """Check if value looks like a phone number""" import re phone_pattern = re.compile(r'^\+?1?-?\.?\s?\(?=\d{3})\d{3}[-.\s]?\d{4}$') return bool(phone_pattern.match(value)) def _is_ssn(self, value): """Check if value looks like SSN""" import re ssn_pattern = re.compile(r'^\d{3}-\d{2}-\d{4}$') return bool(ssn_pattern.match(value)) ``` ## 🔍 Security Monitoring ### Security Event Monitoring ```python # security/security_monitoring.py import json import logging from datetime import datetime from collections import defaultdict, deque class SecurityMonitor: def __init__(self): self.logger = logging.getLogger('security') self.security_events = deque(maxlen=10000) self.event_counts = defaultdict(int) self.alert_thresholds = { 'failed_logins': 5, 'suspicious_requests': 10, 'data_access_violations': 1, 'privilege_escalation': 1 } def log_security_event(self, event_type, user_id, details, severity='medium'): """Log security event""" event = { 'timestamp': datetime.utcnow().isoformat(), 'event_type': event_type, 'user_id': user_id, 'details': details, 'severity': severity, 'source_ip': details.get('source_ip', 'unknown'), 'user_agent': details.get('user_agent', 'unknown') } # Store event self.security_events.append(event) self.event_counts[event_type] += 1 # Log to file self.logger.warning(f"Security Event: {event_type} - User: {user_id} - {details}") # Check for alerts self._check_alert_conditions(event_type, event) def _check_alert_conditions(self, event_type, event): """Check if security event should trigger alert""" threshold = self.alert_thresholds.get(event_type, float('inf')) if self.event_counts[event_type] >= threshold: self._send_security_alert(event_type, event) def _send_security_alert(self, event_type, event): """Send security alert""" alert = { 'alert_type': 'SECURITY_VIOLATION', 'event_type': event_type, 'severity': 'high', 'event': event, 'event_count': self.event_counts[event_type], 'timestamp': datetime.utcnow().isoformat() } # Send to monitoring system self._send_to_monitoring_system(alert) # Send to Slack/email self._send_notification(alert) def _send_to_monitoring_system(self, alert): """Send alert to monitoring system""" # Integration with monitoring system pass def _send_notification(self, alert): """Send notification via Slack/email""" # Integration with notification system pass def get_security_report(self, hours=24): """Generate security report""" cutoff_time = datetime.utcnow() - timedelta(hours=hours) recent_events = [ event for event in self.security_events if datetime.fromisoformat(event['timestamp']) > cutoff_time ] report = { 'report_period': f"Last {hours} hours", 'total_events': len(recent_events), 'event_breakdown': defaultdict(int), 'severity_breakdown': defaultdict(int), 'top_events': [], 'recommendations': [] } # Analyze events for event in recent_events: report['event_breakdown'][event['event_type']] += 1 report['severity_breakdown'][event['severity']] += 1 # Top events sorted_events = sorted( report['event_breakdown'].items(), key=lambda x: x[1], reverse=True ) report['top_events'] = sorted_events[:10] # Recommendations if report['event_breakdown'].get('failed_logins', 0) > 10: report['recommendations'].append( "High number of failed logins detected - consider implementing account lockout" ) if report['event_breakdown'].get('data_access_violations', 0) > 0: report['recommendations'].append( "Data access violations detected - review user permissions" ) return report ``` ### Intrusion Detection ```python # security/intrusion_detection.py import time import hashlib from collections import defaultdict class IntrusionDetector: def __init__(self): self.request_patterns = defaultdict(list) self.ip_reputations = {} self.anomaly_thresholds = { 'requests_per_minute': 1000, 'failed_requests_per_minute': 50, 'unique_ips_per_minute': 100, 'suspicious_patterns': 5 } def analyze_request(self, request_data): """Analyze request for suspicious patterns""" ip_address = request_data.get('source_ip') user_agent = request_data.get('user_agent', '') endpoint = request_data.get('endpoint') timestamp = time.time() # Track request patterns key = f"{ip_address}:{hashlib.md5(user_agent.encode()).hexdigest()}" self.request_patterns[key].append({ 'timestamp': timestamp, 'endpoint': endpoint, 'user_id': request_data.get('user_id'), 'status': request_data.get('status_code', 200) }) # Clean old patterns (older than 1 hour) cutoff_time = timestamp - 3600 self.request_patterns[key] = [ req for req in self.request_patterns[key] if req['timestamp'] > cutoff_time ] # Check for anomalies anomalies = self._detect_anomalies(key, request_data) if anomalies: self._handle_intrusion_attempt(key, request_data, anomalies) return anomalies def _detect_anomalies(self, key, request_data): """Detect anomalous request patterns""" anomalies = [] patterns = self.request_patterns[key] if len(patterns) == 0: return anomalies # Rate limiting check recent_requests = [ req for req in patterns if time.time() - req['timestamp'] < 60 ] if len(recent_requests) > self.anomaly_thresholds['requests_per_minute']: anomalies.append({ 'type': 'rate_limit_exceeded', 'count': len(recent_requests), 'threshold': self.anomaly_thresholds['requests_per_minute'] }) # Failed requests check failed_requests = [ req for req in recent_requests if req['status'] >= 400 ] if len(failed_requests) > self.anomaly_thresholds['failed_requests_per_minute']: anomalies.append({ 'type': 'high_failure_rate', 'count': len(failed_requests), 'threshold': self.anomaly_thresholds['failed_requests_per_minute'] }) # Suspicious endpoint access sensitive_endpoints = ['/api/users', '/api/admin', '/api/config/secrets'] sensitive_access = [ req for req in recent_requests if req['endpoint'] in sensitive_endpoints ] if len(sensitive_access) > self.anomaly_thresholds['suspicious_patterns']: anomalies.append({ 'type': 'sensitive_endpoint_access', 'count': len(sensitive_access), 'endpoints': list(set(req['endpoint'] for req in sensitive_access)) }) return anomalies def _handle_intrusion_attempt(self, key, request_data, anomalies): """Handle detected intrusion attempt""" ip_address = request_data.get('source_ip') # Update IP reputation if ip_address not in self.ip_reputations: self.ip_reputations[ip_address] = {'score': 100, 'violations': 0} self.ip_reputations[ip_address]['violations'] += 1 self.ip_reputations[ip_address]['score'] -= 20 # Log intrusion attempt logging.warning(f"Intrusion attempt detected from {ip_address}: {anomalies}") # Take action based on severity if self.ip_reputations[ip_address]['score'] < 50: self._block_ip(ip_address) def _block_ip(self, ip_address): """Block IP address""" # Integration with firewall or load balancer logging.critical(f"Blocking IP address: {ip_address}") ``` ## 📋 Compliance Framework ### GDPR Compliance ```python # compliance/gdpr.py class GDPRComplianceManager: def __init__(self): self.data_subject_requests = [] self.consent_records = {} self.data_processing_records = [] def record_consent(self, user_id, consent_data, purpose): """Record user consent""" consent_record = { 'user_id': user_id, 'consent_given': datetime.utcnow().isoformat(), 'consent_data': consent_data, 'purpose': purpose, 'legal_basis': 'explicit_consent', 'retention_period': consent_data.get('retention_period', 2555), # 7 years in days 'withdrawn': None } self.consent_records[user_id] = consent_record # Log consent record logging.info(f"Consent recorded for user {user_id} for purpose: {purpose}") def withdraw_consent(self, user_id): """Withdraw user consent""" if user_id in self.consent_records: self.consent_records[user_id]['withdrawn'] = datetime.utcnow().isoformat() # Schedule data deletion self._schedule_data_deletion(user_id) logging.info(f"Consent withdrawn for user {user_id}") def handle_data_subject_request(self, request_type, user_id, contact_info): """Handle GDPR data subject request""" request_record = { 'request_id': f"DSR-{datetime.utcnow().strftime('%Y%m%d%H%M%S')}", 'request_type': request_type, # access, rectification, erasure, portability 'user_id': user_id, 'contact_info': contact_info, 'request_date': datetime.utcnow().isoformat(), 'status': 'received', 'response_date': None } self.data_subject_requests.append(request_record) # Process request based on type if request_type == 'access': self._provide_data_access(user_id, request_record['request_id']) elif request_type == 'erasure': self._erase_user_data(user_id, request_record['request_id']) elif request_type == 'portability': self._provide_data_portability(user_id, request_record['request_id']) return request_record def _provide_data_access(self, user_id, request_id): """Provide data access to user""" user_data = self._collect_user_data(user_id) # Format data for user accessible_data = { 'personal_data': user_data.get('personal', {}), 'usage_data': user_data.get('usage', {}), 'consent_records': self.consent_records.get(user_id, {}), 'data_retention': user_data.get('retention', {}) } # Update request status for request in self.data_subject_requests: if request['request_id'] == request_id: request['status'] = 'completed' request['response_date'] = datetime.utcnow().isoformat() break logging.info(f"Data access provided for user {user_id}") def _erase_user_data(self, user_id, request_id): """Erase user data (Right to be forgotten)""" # Anonymize or delete user data self._anonymize_user_data(user_id) # Update consent records if user_id in self.consent_records: self.consent_records[user_id]['erased'] = datetime.utcnow().isoformat() # Update request status for request in self.data_subject_requests: if request['request_id'] == request_id: request['status'] = 'completed' request['response_date'] = datetime.utcnow().isoformat() break logging.info(f"User data erased for user {user_id}") def _anonymize_user_data(self, user_id): """Anonymize user data while preserving analytics""" # Replace user identifiers with anonymous equivalents # This would integrate with your database systems pass def generate_data_protection_impact_assessment(self): """Generate DPIA for new data processing""" dpia = { 'assessment_id': f"DPIA-{datetime.utcnow().strftime('%Y%m%d%H%M%S')}", 'assessment_date': datetime.utcnow().isoformat(), 'controller': "Aurora AI Systems", 'data_processor': "Aurora AI Systems", 'purposes': [ "Machine learning model training", "User analytics", "System optimization" ], 'categories_of_data': [ "Personal identifiers", "Usage patterns", "Performance metrics" ], 'recipients': [ "Internal teams", "Service providers" ], 'retention_period': "7 years", 'security_measures': [ "Encryption at rest and in transit", "Access controls", "Audit logging" ], 'rights_of_data_subjects': [ "Right to access", "Right to rectification", "Right to erasure", "Right to portability", "Right to object" ], 'legitimate_interests': [ "System improvement", "Fraud prevention", "Security monitoring" ] } return dpia ``` ### SOC 2 Compliance ```python # compliance/soc2.py class SOC2ComplianceManager: def __init__(self): self.control_mappings = { 'access_control': { 'controls': [ 'AC-1: Access Control Policy', 'AC-2: Access Control Program', 'AC-3: Access Enforcement', 'AC-4: Access Control Review' ], 'implementation': 'RBAC system with role-based permissions' }, 'system_operations': { 'controls': [ 'CC-1: Change Control Policy', 'CC-2: Change Control Program', 'CC-3: Change Control Implementation', 'CC-4: Change Control Monitoring' ], 'implementation': 'CI/CD pipeline with automated testing' }, 'risk_assessment': { 'controls': [ 'RA-1: Risk Assessment Policy', 'RA-2: Risk Assessment Program', 'RA-3: Risk Assessment Implementation', 'RA-4: Risk Assessment Monitoring' ], 'implementation': 'Regular security assessments and penetration testing' } } def generate_soc2_report(self): """Generate SOC 2 Type II compliance report""" report = { 'report_id': f"SOC2-{datetime.utcnow().strftime('%Y%m%d%H%M%S')}", 'report_period': f"{(datetime.utcnow() - timedelta(days=90)).strftime('%Y-%m-%d')} to {datetime.utcnow().strftime('%Y-%m-%d')}", 'service_organization': "Aurora AI Systems", 'criteria_reference': 'SOC 2 Type II', 'trust_services_criteria': { 'security': self._assess_security_controls(), 'availability': self._assess_availability_controls(), 'processing_integrity': self._assess_integrity_controls(), 'confidentiality': self._assess_confidentiality_controls(), 'privacy': self._assess_privacy_controls() }, 'system_description': self._describe_system_architecture(), 'control_environment': self._describe_control_environment(), 'relevant_aspects': self._identify_relevant_aspects(), 'tested_controls': self._list_tested_controls(), 'test_results': self._summarize_test_results(), 'opinion': 'Unqualified opinion' } return report def _assess_security_controls(self): """Assess security controls""" return { 'AC-1': { 'status': 'Implemented', 'description': 'Comprehensive access control policy established', 'evidence': 'Policy documents, access control logs' }, 'AC-2': { 'status': 'Implemented', 'description': 'Formal access control program in place', 'evidence': 'Program documentation, training records' }, 'AC-3': { 'status': 'Implemented', 'description': 'Automated access enforcement for all systems', 'evidence': 'System logs, access control configuration' } } def _assess_availability_controls(self): """Assess availability controls""" return { 'A-1': { 'status': 'Implemented', 'description': 'Availability objectives defined and monitored', 'evidence': 'SLA documents, monitoring dashboards' }, 'A-2': { 'status': 'Implemented', 'description': 'System availability monitoring in place', 'evidence': 'Monitoring logs, uptime reports' } } def _assess_integrity_controls(self): """Assess processing integrity controls""" return { 'I-1': { 'status': 'Implemented', 'description': 'Input data validation controls in place', 'evidence': 'Validation logs, data quality reports' }, 'I-2': { 'status': 'Implemented', 'description': 'Data processing integrity controls implemented', 'evidence': 'Processing logs, audit trails' } } def _assess_confidentiality_controls(self): """Assess confidentiality controls""" return { 'C-1': { 'status': 'Implemented', 'description': 'Data confidentiality controls established', 'evidence': 'Encryption logs, access logs' }, 'C-2': { 'status': 'Implemented', 'description': 'Data confidentiality agreements in place', 'evidence': 'Agreements, policy documents' } } def _assess_privacy_controls(self): """Assess privacy controls""" return { 'P-1': { 'status': 'Implemented', 'description': 'Privacy policy and notices available', 'evidence': 'Privacy policy, website notices' }, 'P-2': { 'status': 'Implemented', 'description': 'User consent management system in place', 'evidence': 'Consent logs, user interface' } } ``` ## 🔍 Security Auditing ### Security Audit Framework ```python # security/auditing.py class SecurityAuditor: def __init__(self): self.audit_findings = [] self.audit_recommendations = [] def conduct_security_audit(self): """Conduct comprehensive security audit""" audit_report = { 'audit_id': f"AUDIT-{datetime.utcnow().strftime('%Y%m%d%H%M%S')}", 'audit_date': datetime.utcnow().isoformat(), 'auditor': "Security Team", 'scope': "Full System Security Assessment", 'findings': [], 'risk_assessment': {}, 'recommendations': [], 'compliance_status': {} } # Conduct audit checks audit_checks = [ self._audit_authentication, self._audit_authorization, self._audit_data_protection, self._audit_network_security, self._audit_infrastructure_security, self._audit_logging_monitoring, self._audit_incident_response ] for check in audit_checks: finding = check() audit_report['findings'].append(finding) # Generate risk assessment audit_report['risk_assessment'] = self._assess_overall_risk(audit_report['findings']) # Generate recommendations audit_report['recommendations'] = self._generate_recommendations(audit_report['findings']) # Assess compliance audit_report['compliance_status'] = self._assess_compliance(audit_report['findings']) return audit_report def _audit_authentication(self): """Audit authentication controls""" findings = [] # Check password policies password_policy_check = self._check_password_policy() findings.append(password_policy_check) # Check MFA implementation mfa_check = self._check_mfa_implementation() findings.append(mfa_check) # Check session management session_check = self._check_session_management() findings.append(session_check) return { 'area': 'Authentication', 'findings': findings, 'overall_score': self._calculate_score(findings) } def _audit_authorization(self): """Audit authorization controls""" findings = [] # Check RBAC implementation rbac_check = self._check_rbac_implementation() findings.append(rbac_check) # Check privilege escalation privilege_check = self._check_privilege_escalation() findings.append(privilege_check) return { 'area': 'Authorization', 'findings': findings, 'overall_score': self._calculate_score(findings) } def _audit_data_protection(self): """Audit data protection controls""" findings = [] # Check encryption implementation encryption_check = self._check_encryption_implementation() findings.append(encryption_check) # Check data classification classification_check = self._check_data_classification() findings.append(classification_check) return { 'area': 'Data Protection', 'findings': findings, 'overall_score': self._calculate_score(findings) } def _check_password_policy(self): """Check password policy implementation""" return { 'control': 'Password Policy', 'status': 'Compliant', 'details': 'Strong password policy implemented with complexity requirements', 'risk_level': 'Low', 'evidence': 'Configuration files, user interface validation' } def _check_mfa_implementation(self): """Check MFA implementation""" return { 'control': 'Multi-Factor Authentication', 'status': 'Partially Implemented', 'details': 'MFA available for admin users but not all users', 'risk_level': 'Medium', 'evidence': 'Authentication configuration, user settings' } def _check_session_management(self): """Check session management""" return { 'control': 'Session Management', 'status': 'Compliant', 'details': 'Secure session management with timeout and invalidation', 'risk_level': 'Low', 'evidence': 'Session configuration, security logs' } def _calculate_score(self, findings): """Calculate security score for findings""" total_score = 0 max_score = 0 for finding in findings: if finding['status'] == 'Compliant': total_score += 100 elif finding['status'] == 'Partially Implemented': total_score += 60 elif finding['status'] == 'Non-Compliant': total_score += 0 max_score += 100 return (total_score / max_score) * 100 if max_score > 0 else 0 ``` ## 📊 Security Metrics and Reporting ### Security Dashboard ```python # security/dashboard.py class SecurityDashboard: def __init__(self): self.metrics_collector = SecurityMetricsCollector() def get_security_dashboard_data(self): """Get security dashboard data""" return { 'overview': self._get_security_overview(), 'threat_landscape': self._get_threat_landscape(), 'compliance_status': self._get_compliance_status(), 'security_events': self._get_recent_security_events(), 'vulnerability_status': self._get_vulnerability_status(), 'risk_assessment': self._get_risk_assessment() } def _get_security_overview(self): """Get security overview metrics""" return { 'security_score': 92.5, 'active_threats': 3, 'blocked_attacks': 127, 'security_posture': 'Strong', 'last_assessment': '2026-05-01', 'compliance_percentage': 94.2 } def _get_threat_landscape(self): """Get threat landscape data""" return { 'top_threats': [ { 'threat_type': 'Brute Force Attack', 'count': 45, 'trend': 'Decreasing', 'severity': 'Medium' }, { 'threat_type': 'SQL Injection', 'count': 12, 'trend': 'Stable', 'severity': 'High' }, { 'threat_type': 'DDoS Attack', 'count': 8, 'trend': 'Increasing', 'severity': 'High' } ], 'threat_trends': { 'overall_trend': 'Improving', 'new_threats_this_month': 23, 'resolved_threats_this_month': 31 } } ``` --- **Aurora AI Security and Compliance Guide** *Enterprise Security • Data Protection • Compliance • Risk Management*