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"""
Enterprise Governance and AI Safety Framework for Cyber-LLM
Comprehensive model governance, regulatory compliance, and AI safety monitoring
Author: Muzan Sano <[email protected]>
"""
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())
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