""" Enterprise Governance and AI Safety Framework for Cyber-LLM Comprehensive model governance, regulatory compliance, and AI safety monitoring Author: Muzan Sano """ import asyncio import json import logging from datetime import datetime, timedelta from typing import Dict, List, Any, Optional, Tuple, Union from dataclasses import dataclass, field from enum import Enum from pathlib import Path import yaml import pandas as pd import numpy as np from collections import defaultdict import hashlib import sqlite3 import aiofiles from ..utils.logging_system import CyberLLMLogger, CyberLLMError, ErrorCategory from ..utils.secrets_manager import get_secrets_manager from ..learning.constitutional_ai import ConstitutionalAIManager class ComplianceFramework(Enum): """Supported compliance frameworks""" GDPR = "gdpr" CCPA = "ccpa" SOC2 = "soc2" ISO27001 = "iso27001" NIST = "nist_cybersecurity_framework" PCI_DSS = "pci_dss" HIPAA = "hipaa" class GovernancePolicy(Enum): """Types of governance policies""" DATA_HANDLING = "data_handling" MODEL_LIFECYCLE = "model_lifecycle" BIAS_DETECTION = "bias_detection" SAFETY_CONSTRAINTS = "safety_constraints" ACCESS_CONTROL = "access_control" AUDIT_LOGGING = "audit_logging" class RiskLevel(Enum): """Risk assessment levels""" LOW = "low" MEDIUM = "medium" HIGH = "high" CRITICAL = "critical" @dataclass class GovernanceRule: """Individual governance rule""" rule_id: str name: str description: str policy_type: GovernancePolicy compliance_frameworks: List[ComplianceFramework] severity: RiskLevel # Rule logic conditions: List[str] actions: List[str] exceptions: List[str] = field(default_factory=list) # Metadata created_at: datetime = field(default_factory=datetime.now) updated_at: datetime = field(default_factory=datetime.now) active: bool = True @dataclass class ComplianceViolation: """Compliance violation record""" violation_id: str rule_id: str violation_type: str severity: RiskLevel # Context description: str evidence: Dict[str, Any] affected_systems: List[str] timestamp: datetime # Resolution status: str = "open" # open, investigating, resolved, false_positive assigned_to: Optional[str] = None resolution_notes: Optional[str] = None resolved_at: Optional[datetime] = None @dataclass class ModelGovernanceRecord: """Model governance tracking record""" model_id: str model_name: str version: str # Lifecycle tracking created_at: datetime last_updated: datetime status: str # development, testing, staging, production, retired # Governance metadata data_lineage: Dict[str, Any] training_metrics: Dict[str, float] validation_results: Dict[str, Any] bias_assessment: Dict[str, float] safety_assessment: Dict[str, float] # Compliance approved_by: List[str] compliance_status: Dict[str, bool] audit_trail: List[Dict[str, Any]] class EnterpriseGovernanceManager: """Comprehensive enterprise governance and compliance management""" def __init__(self, config_path: str = "configs/governance_config.yaml", logger: Optional[CyberLLMLogger] = None): self.logger = logger or CyberLLMLogger(name="enterprise_governance") self.config_path = Path(config_path) self.config = self._load_config() # Initialize components self.constitutional_ai = ConstitutionalAIManager() self.governance_rules = {} self.compliance_violations = [] self.model_registry = {} # Database for governance tracking self.db_path = Path("data/governance.db") self.db_path.parent.mkdir(parents=True, exist_ok=True) # Initialize governance framework asyncio.create_task(self._initialize_governance()) self.logger.info("Enterprise governance manager initialized") def _load_config(self) -> Dict[str, Any]: """Load governance configuration""" default_config = { "compliance_frameworks": ["GDPR", "SOC2", "NIST"], "governance_policies": { "data_retention_days": 90, "model_approval_required": True, "bias_threshold": 0.1, "safety_threshold": 0.9, "audit_log_retention": 365 }, "notification_settings": { "critical_violations": True, "compliance_reports": True, "model_lifecycle_events": True }, "automated_remediation": { "enabled": True, "auto_quarantine_models": True, "auto_generate_reports": True } } if self.config_path.exists(): with open(self.config_path, 'r') as f: user_config = yaml.safe_load(f) default_config.update(user_config) else: # Save default config self.config_path.parent.mkdir(exist_ok=True, parents=True) with open(self.config_path, 'w') as f: yaml.dump(default_config, f) return default_config async def _initialize_governance(self): """Initialize governance framework and database""" try: # Initialize database conn = sqlite3.connect(self.db_path) cursor = conn.cursor() # Create governance tables cursor.execute(""" CREATE TABLE IF NOT EXISTS governance_rules ( rule_id TEXT PRIMARY KEY, name TEXT NOT NULL, description TEXT, policy_type TEXT, compliance_frameworks TEXT, -- JSON severity TEXT, conditions TEXT, -- JSON actions TEXT, -- JSON exceptions TEXT, -- JSON created_at TIMESTAMP, updated_at TIMESTAMP, active BOOLEAN DEFAULT TRUE ) """) cursor.execute(""" CREATE TABLE IF NOT EXISTS compliance_violations ( violation_id TEXT PRIMARY KEY, rule_id TEXT, violation_type TEXT, severity TEXT, description TEXT, evidence TEXT, -- JSON affected_systems TEXT, -- JSON timestamp TIMESTAMP, status TEXT DEFAULT 'open', assigned_to TEXT, resolution_notes TEXT, resolved_at TIMESTAMP ) """) cursor.execute(""" CREATE TABLE IF NOT EXISTS model_governance ( model_id TEXT PRIMARY KEY, model_name TEXT NOT NULL, version TEXT, created_at TIMESTAMP, last_updated TIMESTAMP, status TEXT, data_lineage TEXT, -- JSON training_metrics TEXT, -- JSON validation_results TEXT, -- JSON bias_assessment TEXT, -- JSON safety_assessment TEXT, -- JSON approved_by TEXT, -- JSON compliance_status TEXT, -- JSON audit_trail TEXT -- JSON ) """) cursor.execute(""" CREATE TABLE IF NOT EXISTS audit_logs ( id INTEGER PRIMARY KEY AUTOINCREMENT, timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP, event_type TEXT NOT NULL, user_id TEXT, resource_id TEXT, action TEXT, details TEXT, -- JSON ip_address TEXT, user_agent TEXT ) """) conn.commit() conn.close() # Load default governance rules await self._load_default_governance_rules() self.logger.info("Governance database and rules initialized") except Exception as e: self.logger.error("Failed to initialize governance framework", error=str(e)) raise CyberLLMError("Governance initialization failed", ErrorCategory.SYSTEM) async def _load_default_governance_rules(self): """Load default governance rules""" default_rules = [ GovernanceRule( rule_id="data_privacy_gdpr_001", name="GDPR Data Processing Consent", description="Ensure explicit consent for personal data processing under GDPR", policy_type=GovernancePolicy.DATA_HANDLING, compliance_frameworks=[ComplianceFramework.GDPR], severity=RiskLevel.HIGH, conditions=[ "personal_data_detected == True", "explicit_consent == False" ], actions=[ "block_processing", "notify_data_protection_officer", "log_violation" ] ), GovernanceRule( rule_id="model_bias_detection_001", name="Model Bias Assessment Required", description="Require bias assessment for all production models", policy_type=GovernancePolicy.BIAS_DETECTION, compliance_frameworks=[ComplianceFramework.SOC2, ComplianceFramework.ISO27001], severity=RiskLevel.MEDIUM, conditions=[ "model_status == 'production'", "bias_assessment_completed == False" ], actions=[ "require_bias_assessment", "prevent_deployment", "notify_ml_governance_team" ] ), GovernanceRule( rule_id="safety_constitutional_001", name="Constitutional AI Safety Check", description="Apply constitutional AI safety constraints to all model outputs", policy_type=GovernancePolicy.SAFETY_CONSTRAINTS, compliance_frameworks=[ComplianceFramework.SOC2, ComplianceFramework.NIST], severity=RiskLevel.CRITICAL, conditions=[ "model_output_generated == True", "constitutional_check_passed == False" ], actions=[ "block_output", "apply_constitutional_constraints", "escalate_to_safety_team" ] ), GovernanceRule( rule_id="audit_logging_001", name="Comprehensive Audit Logging", description="Log all model operations and access for compliance", policy_type=GovernancePolicy.AUDIT_LOGGING, compliance_frameworks=[ ComplianceFramework.SOC2, ComplianceFramework.ISO27001, ComplianceFramework.PCI_DSS ], severity=RiskLevel.HIGH, conditions=[ "sensitive_operation_performed == True", "audit_log_created == False" ], actions=[ "create_audit_log", "ensure_log_integrity", "notify_if_log_failure" ] ), GovernanceRule( rule_id="access_control_001", name="Role-Based Access Control", description="Enforce RBAC for all system access", policy_type=GovernancePolicy.ACCESS_CONTROL, compliance_frameworks=[ ComplianceFramework.SOC2, ComplianceFramework.ISO27001, ComplianceFramework.NIST ], severity=RiskLevel.HIGH, conditions=[ "user_access_requested == True", "role_authorization_verified == False" ], actions=[ "verify_user_role", "apply_principle_of_least_privilege", "log_access_attempt" ] ) ] for rule in default_rules: await self._register_governance_rule(rule) self.logger.info(f"Loaded {len(default_rules)} default governance rules") async def _register_governance_rule(self, rule: GovernanceRule): """Register a governance rule in the system""" try: conn = sqlite3.connect(self.db_path) cursor = conn.cursor() cursor.execute(""" INSERT OR REPLACE INTO governance_rules (rule_id, name, description, policy_type, compliance_frameworks, severity, conditions, actions, exceptions, created_at, updated_at, active) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?) """, ( rule.rule_id, rule.name, rule.description, rule.policy_type.value, json.dumps([f.value for f in rule.compliance_frameworks]), rule.severity.value, json.dumps(rule.conditions), json.dumps(rule.actions), json.dumps(rule.exceptions), rule.created_at.isoformat(), rule.updated_at.isoformat(), rule.active )) conn.commit() conn.close() self.governance_rules[rule.rule_id] = rule except Exception as e: self.logger.error(f"Failed to register governance rule: {rule.rule_id}", error=str(e)) async def register_model(self, model_id: str, model_name: str, version: str, metadata: Dict[str, Any]) -> ModelGovernanceRecord: """Register a model in the governance system""" model_record = ModelGovernanceRecord( model_id=model_id, model_name=model_name, version=version, created_at=datetime.now(), last_updated=datetime.now(), status="development", data_lineage=metadata.get("data_lineage", {}), training_metrics=metadata.get("training_metrics", {}), validation_results=metadata.get("validation_results", {}), bias_assessment=metadata.get("bias_assessment", {}), safety_assessment=metadata.get("safety_assessment", {}), approved_by=[], compliance_status={}, audit_trail=[] ) try: conn = sqlite3.connect(self.db_path) cursor = conn.cursor() cursor.execute(""" INSERT OR REPLACE INTO model_governance (model_id, model_name, version, created_at, last_updated, status, data_lineage, training_metrics, validation_results, bias_assessment, safety_assessment, approved_by, compliance_status, audit_trail) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?) """, ( model_id, model_name, version, model_record.created_at.isoformat(), model_record.last_updated.isoformat(), model_record.status, json.dumps(model_record.data_lineage), json.dumps(model_record.training_metrics), json.dumps(model_record.validation_results), json.dumps(model_record.bias_assessment), json.dumps(model_record.safety_assessment), json.dumps(model_record.approved_by), json.dumps(model_record.compliance_status), json.dumps(model_record.audit_trail) )) conn.commit() conn.close() self.model_registry[model_id] = model_record await self._audit_log( event_type="model_registered", resource_id=model_id, action="register_model", details={"model_name": model_name, "version": version} ) self.logger.info(f"Model registered in governance system: {model_id}") return model_record except Exception as e: self.logger.error(f"Failed to register model: {model_id}", error=str(e)) raise CyberLLMError("Model registration failed", ErrorCategory.SYSTEM) async def assess_model_compliance(self, model_id: str) -> Dict[str, Any]: """Assess model compliance against governance rules""" if model_id not in self.model_registry: raise CyberLLMError(f"Model not found in registry: {model_id}", ErrorCategory.VALIDATION) model_record = self.model_registry[model_id] compliance_assessment = { "model_id": model_id, "assessment_timestamp": datetime.now().isoformat(), "framework_compliance": {}, "violations": [], "overall_compliance": True, "recommendations": [] } # Check compliance for each framework for framework in ComplianceFramework: framework_score = await self._assess_framework_compliance(model_record, framework) compliance_assessment["framework_compliance"][framework.value] = framework_score if framework_score["compliance_score"] < 0.8: # 80% threshold compliance_assessment["overall_compliance"] = False # Check for governance rule violations violations = await self._check_governance_violations(model_record) compliance_assessment["violations"] = violations if violations: compliance_assessment["overall_compliance"] = False # Generate recommendations recommendations = await self._generate_compliance_recommendations( model_record, compliance_assessment ) compliance_assessment["recommendations"] = recommendations # Update model compliance status model_record.compliance_status = { f.value: compliance_assessment["framework_compliance"][f.value]["compliant"] for f in ComplianceFramework } await self._update_model_record(model_record) return compliance_assessment async def _assess_framework_compliance(self, model_record: ModelGovernanceRecord, framework: ComplianceFramework) -> Dict[str, Any]: """Assess compliance for a specific framework""" framework_assessment = { "framework": framework.value, "compliant": True, "compliance_score": 1.0, "requirements_met": {}, "violations": [] } # Framework-specific compliance checks if framework == ComplianceFramework.GDPR: # GDPR compliance checks gdpr_checks = { "data_lineage_documented": bool(model_record.data_lineage), "consent_mechanism": "explicit_consent" in model_record.data_lineage, "right_to_explanation": bool(model_record.validation_results.get("explainability")), "data_minimization": "data_minimization_applied" in model_record.data_lineage } framework_assessment["requirements_met"] = gdpr_checks compliance_score = sum(gdpr_checks.values()) / len(gdpr_checks) framework_assessment["compliance_score"] = compliance_score framework_assessment["compliant"] = compliance_score >= 0.8 elif framework == ComplianceFramework.SOC2: # SOC2 compliance checks soc2_checks = { "security_controls": bool(model_record.safety_assessment), "availability_monitoring": "uptime_monitoring" in model_record.validation_results, "processing_integrity": bool(model_record.validation_results), "confidentiality": "data_encryption" in model_record.data_lineage, "privacy": bool(model_record.bias_assessment) } framework_assessment["requirements_met"] = soc2_checks compliance_score = sum(soc2_checks.values()) / len(soc2_checks) framework_assessment["compliance_score"] = compliance_score framework_assessment["compliant"] = compliance_score >= 0.8 elif framework == ComplianceFramework.NIST: # NIST Cybersecurity Framework checks nist_checks = { "identify_assets": bool(model_record.data_lineage), "protect_controls": bool(model_record.safety_assessment), "detect_anomalies": "anomaly_detection" in model_record.validation_results, "respond_procedures": bool(model_record.audit_trail), "recover_capabilities": "backup_procedures" in model_record.data_lineage } framework_assessment["requirements_met"] = nist_checks compliance_score = sum(nist_checks.values()) / len(nist_checks) framework_assessment["compliance_score"] = compliance_score framework_assessment["compliant"] = compliance_score >= 0.8 return framework_assessment async def _check_governance_violations(self, model_record: ModelGovernanceRecord) -> List[Dict[str, Any]]: """Check for governance rule violations""" violations = [] # Create context for rule evaluation evaluation_context = { "model_status": model_record.status, "bias_assessment_completed": bool(model_record.bias_assessment), "safety_assessment_completed": bool(model_record.safety_assessment), "approval_required": self.config["governance_policies"]["model_approval_required"], "approved_by_count": len(model_record.approved_by) } for rule_id, rule in self.governance_rules.items(): if not rule.active: continue # Evaluate rule conditions rule_violated = self._evaluate_rule_conditions(rule.conditions, evaluation_context) if rule_violated: violation = { "rule_id": rule_id, "rule_name": rule.name, "severity": rule.severity.value, "description": rule.description, "suggested_actions": rule.actions } violations.append(violation) return violations def _evaluate_rule_conditions(self, conditions: List[str], context: Dict[str, Any]) -> bool: """Evaluate rule conditions against context""" try: for condition in conditions: # Simple condition evaluation (in production, use safe expression evaluator) if "==" in condition: var, value = condition.split("==") var = var.strip() value = value.strip().strip('"\'') context_value = context.get(var) if str(context_value) != value: continue elif ">" in condition: var, value = condition.split(">") var = var.strip() value = float(value.strip()) context_value = context.get(var, 0) if float(context_value) <= value: continue elif "<" in condition: var, value = condition.split("<") var = var.strip() value = float(value.strip()) context_value = context.get(var, 0) if float(context_value) >= value: continue # If we reach here, all conditions are met return True except Exception as e: self.logger.warning(f"Failed to evaluate rule conditions: {conditions}", error=str(e)) return False return False async def _generate_compliance_recommendations(self, model_record: ModelGovernanceRecord, assessment: Dict[str, Any]) -> List[str]: """Generate compliance improvement recommendations""" recommendations = [] # General recommendations based on compliance status if not assessment["overall_compliance"]: recommendations.append("Address identified compliance violations before deployment") # Framework-specific recommendations for framework, details in assessment["framework_compliance"].items(): if not details["compliant"]: if framework == "gdpr": recommendations.append("Implement explicit consent mechanism for data processing") recommendations.append("Add explainability features for right to explanation") elif framework == "soc2": recommendations.append("Implement comprehensive security controls") recommendations.append("Add availability monitoring capabilities") elif framework == "nist": recommendations.append("Document asset inventory and data lineage") recommendations.append("Implement anomaly detection capabilities") # Model-specific recommendations if not model_record.bias_assessment: recommendations.append("Complete bias assessment before production deployment") if not model_record.safety_assessment: recommendations.append("Conduct comprehensive safety assessment") if model_record.status == "production" and not model_record.approved_by: recommendations.append("Obtain required approvals from governance team") return recommendations async def create_compliance_report(self, framework: ComplianceFramework, time_period: Optional[Tuple[datetime, datetime]] = None) -> Dict[str, Any]: """Generate comprehensive compliance report""" if not time_period: end_date = datetime.now() start_date = end_date - timedelta(days=30) time_period = (start_date, end_date) report = { "report_id": f"compliance_report_{datetime.now().strftime('%Y%m%d_%H%M%S')}", "framework": framework.value, "generated_at": datetime.now().isoformat(), "time_period": { "start": time_period[0].isoformat(), "end": time_period[1].isoformat() }, "summary": {}, "model_compliance": {}, "violations": [], "recommendations": [] } # Assess all models in registry total_models = len(self.model_registry) compliant_models = 0 for model_id, model_record in self.model_registry.items(): assessment = await self._assess_framework_compliance(model_record, framework) report["model_compliance"][model_id] = assessment if assessment["compliant"]: compliant_models += 1 # Generate summary compliance_rate = compliant_models / total_models if total_models > 0 else 0 report["summary"] = { "total_models": total_models, "compliant_models": compliant_models, "compliance_rate": compliance_rate, "non_compliant_models": total_models - compliant_models } # Get violations for time period violations = await self._get_violations_for_period(time_period[0], time_period[1]) framework_violations = [ v for v in violations if framework in [ComplianceFramework(f) for f in self.governance_rules[v.rule_id].compliance_frameworks] ] report["violations"] = [asdict(v) for v in framework_violations] # Generate recommendations if compliance_rate < 0.8: report["recommendations"].append(f"Improve {framework.value} compliance rate (currently {compliance_rate:.1%})") if len(framework_violations) > 0: report["recommendations"].append("Address open compliance violations") self.logger.info(f"Generated {framework.value} compliance report", total_models=total_models, compliance_rate=compliance_rate) return report async def _get_violations_for_period(self, start_date: datetime, end_date: datetime) -> List[ComplianceViolation]: """Get compliance violations for time period""" try: conn = sqlite3.connect(self.db_path) cursor = conn.cursor() cursor.execute(""" SELECT * FROM compliance_violations WHERE timestamp BETWEEN ? AND ? ORDER BY timestamp DESC """, (start_date.isoformat(), end_date.isoformat())) rows = cursor.fetchall() conn.close() violations = [] for row in rows: violation = ComplianceViolation( violation_id=row[0], rule_id=row[1], violation_type=row[2], severity=RiskLevel(row[3]), description=row[4], evidence=json.loads(row[5]), affected_systems=json.loads(row[6]), timestamp=datetime.fromisoformat(row[7]), status=row[8], assigned_to=row[9], resolution_notes=row[10], resolved_at=datetime.fromisoformat(row[11]) if row[11] else None ) violations.append(violation) return violations except Exception as e: self.logger.error("Failed to retrieve violations", error=str(e)) return [] async def _audit_log(self, event_type: str, resource_id: str, action: str, details: Dict[str, Any], user_id: Optional[str] = None, ip_address: Optional[str] = None, user_agent: Optional[str] = None): """Create audit log entry""" try: conn = sqlite3.connect(self.db_path) cursor = conn.cursor() cursor.execute(""" INSERT INTO audit_logs (timestamp, event_type, user_id, resource_id, action, details, ip_address, user_agent) VALUES (?, ?, ?, ?, ?, ?, ?, ?) """, ( datetime.now().isoformat(), event_type, user_id, resource_id, action, json.dumps(details), ip_address, user_agent )) conn.commit() conn.close() except Exception as e: self.logger.error("Failed to create audit log", error=str(e)) async def _update_model_record(self, model_record: ModelGovernanceRecord): """Update model record in database""" try: conn = sqlite3.connect(self.db_path) cursor = conn.cursor() cursor.execute(""" UPDATE model_governance SET last_updated = ?, status = ?, compliance_status = ?, audit_trail = ? WHERE model_id = ? """, ( datetime.now().isoformat(), model_record.status, json.dumps(model_record.compliance_status), json.dumps(model_record.audit_trail), model_record.model_id )) conn.commit() conn.close() except Exception as e: self.logger.error(f"Failed to update model record: {model_record.model_id}", error=str(e)) def get_governance_dashboard_data(self) -> Dict[str, Any]: """Get data for governance dashboard""" total_models = len(self.model_registry) compliant_models = sum( 1 for model in self.model_registry.values() if all(model.compliance_status.values()) ) # Recent violations recent_violations = [ v for v in self.compliance_violations if v.timestamp >= datetime.now() - timedelta(days=7) ] # Compliance by framework framework_compliance = {} for framework in ComplianceFramework: framework_compliant = sum( 1 for model in self.model_registry.values() if model.compliance_status.get(framework.value, False) ) framework_compliance[framework.value] = { "compliant": framework_compliant, "total": total_models, "rate": framework_compliant / total_models if total_models > 0 else 0 } return { "overall_compliance": { "total_models": total_models, "compliant_models": compliant_models, "compliance_rate": compliant_models / total_models if total_models > 0 else 0 }, "framework_compliance": framework_compliance, "recent_violations": len(recent_violations), "governance_rules": len(self.governance_rules), "last_updated": datetime.now().isoformat() } # Factory function def create_enterprise_governance_manager(**kwargs) -> EnterpriseGovernanceManager: """Create enterprise governance manager with configuration""" return EnterpriseGovernanceManager(**kwargs) # Example usage if __name__ == "__main__": async def main(): # Initialize governance manager governance = EnterpriseGovernanceManager() # Register a model model_record = await governance.register_model( model_id="cyber_llm_v1", model_name="Cyber-LLM", version="1.0.0", metadata={ "training_metrics": {"accuracy": 0.95, "safety_score": 0.89}, "bias_assessment": {"demographic_parity": 0.02}, "data_lineage": {"explicit_consent": True} } ) # Assess compliance compliance = await governance.assess_model_compliance("cyber_llm_v1") print(f"Model compliance: {compliance['overall_compliance']}") # Generate GDPR report gdpr_report = await governance.create_compliance_report(ComplianceFramework.GDPR) print(f"GDPR compliance rate: {gdpr_report['summary']['compliance_rate']:.1%}") # Get dashboard data dashboard = governance.get_governance_dashboard_data() print(f"Overall compliance rate: {dashboard['overall_compliance']['compliance_rate']:.1%}") asyncio.run(main())