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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"<script[^>]*>.*?</script>", 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"
) |