Enterprise-grade security architecture for Aurelis GitHub Models integration
This document outlines the comprehensive security model implemented in Aurelis, covering authentication, authorization, data protection, compliance, and threat mitigation strategies for safe AI model interactions.
Aurelis implements a defense-in-depth security model with multiple layers of protection:
┌─────────────────────────────────────────────────────────────┐
│ Application Layer │
│ ├── Input Validation & Sanitization │
│ ├── Business Logic Security │
│ ├── Session Management │
│ └── Output Encoding │
├─────────────────────────────────────────────────────────────┤
│ Authentication Layer │
│ ├── Token Validation │
│ ├── Multi-Factor Authentication │
│ ├── Session Security │
│ └── Identity Verification │
├─────────────────────────────────────────────────────────────┤
│ Authorization Layer │
│ ├── Role-Based Access Control (RBAC) │
│ ├── Resource-Level Permissions │
│ ├── API Rate Limiting │
│ └── Usage Quotas │
├─────────────────────────────────────────────────────────────┤
│ Transport Layer │
│ ├── TLS 1.3 Encryption │
│ ├── Certificate Pinning │
│ ├── Request/Response Integrity │
│ └── Man-in-the-Middle Protection │
├─────────────────────────────────────────────────────────────┤
│ Infrastructure Layer │
│ ├── Network Segmentation │
│ ├── Firewall Protection │
│ ├── DDoS Mitigation │
│ └── Intrusion Detection │
└─────────────────────────────────────────────────────────────┘
Aurelis adheres to multiple security and compliance frameworks:
class SecureTokenManager:
"""Enterprise-grade GitHub token management."""
def __init__(self):
self.encryption_key = self._derive_encryption_key()
self.token_store = SecureTokenStore()
self.audit_logger = get_audit_logger()
def store_token(self, token: str, user_context: Dict[str, Any]) -> str:
"""Securely store GitHub token with encryption."""
# Validate token format and permissions
if not self._validate_token_format(token):
raise SecurityError("Invalid token format")
# Encrypt token before storage
encrypted_token = self._encrypt_token(token)
# Store with metadata
token_id = self._generate_token_id()
storage_record = {
"token_id": token_id,
"encrypted_token": encrypted_token,
"created_at": datetime.utcnow(),
"user_id": user_context.get("user_id"),
"organization": user_context.get("organization"),
"permissions": self._extract_token_permissions(token),
"last_used": None,
"usage_count": 0
}
self.token_store.store(token_id, storage_record)
# Audit log
self.audit_logger.log_security_event(
event_type="token_stored",
severity="info",
description="GitHub token securely stored",
context={"token_id": token_id, "user_id": user_context.get("user_id")}
)
return token_id
def retrieve_token(self, token_id: str, user_context: Dict[str, Any]) -> str:
"""Securely retrieve and decrypt GitHub token."""
# Verify user authorization
if not self._authorize_token_access(token_id, user_context):
raise SecurityError("Unauthorized token access attempt")
record = self.token_store.retrieve(token_id)
if not record:
raise SecurityError("Token not found")
# Decrypt token
decrypted_token = self._decrypt_token(record["encrypted_token"])
# Update usage tracking
self._update_token_usage(token_id)
# Audit log
self.audit_logger.log_security_event(
event_type="token_retrieved",
severity="info",
description="GitHub token accessed",
context={"token_id": token_id, "user_id": user_context.get("user_id")}
)
return decrypted_token
def rotate_token(self, token_id: str, new_token: str, user_context: Dict[str, Any]):
"""Rotate GitHub token with secure transition."""
# Validate new token
if not self._validate_token_format(new_token):
raise SecurityError("Invalid new token format")
# Store new token
new_token_id = self.store_token(new_token, user_context)
# Mark old token for deprecation
self._deprecate_token(token_id, new_token_id)
# Audit log
self.audit_logger.log_security_event(
event_type="token_rotated",
severity="info",
description="GitHub token rotated",
context={
"old_token_id": token_id,
"new_token_id": new_token_id,
"user_id": user_context.get("user_id")
}
)
return new_token_id
class TokenValidator:
"""Validate GitHub tokens and their permissions."""
def __init__(self):
self.required_scopes = {
"read:user", # Basic user information
"read:org" # Organization membership (if applicable)
}
self.github_api = GitHubAPIClient()
async def validate_token(self, token: str) -> TokenValidationResult:
"""Comprehensive token validation."""
validation_result = TokenValidationResult()
try:
# 1. Format validation
if not self._validate_token_format(token):
validation_result.add_error("Invalid token format")
return validation_result
# 2. API connectivity test
user_info = await self._test_api_connectivity(token)
if not user_info:
validation_result.add_error("Token authentication failed")
return validation_result
# 3. Scope validation
token_scopes = await self._get_token_scopes(token)
missing_scopes = self.required_scopes - set(token_scopes)
if missing_scopes:
validation_result.add_warning(f"Missing scopes: {missing_scopes}")
# 4. Rate limit check
rate_limit_info = await self._check_rate_limits(token)
validation_result.rate_limit_info = rate_limit_info
# 5. Model access verification
model_access = await self._verify_model_access(token)
if not model_access:
validation_result.add_error("No access to GitHub Models")
return validation_result
validation_result.mark_valid()
validation_result.user_info = user_info
validation_result.token_scopes = token_scopes
except Exception as e:
validation_result.add_error(f"Validation error: {str(e)}")
return validation_result
async def _verify_model_access(self, token: str) -> bool:
"""Verify token has access to GitHub Models."""
headers = {"Authorization": f"Bearer {token}"}
try:
async with aiohttp.ClientSession() as session:
async with session.get(
"https://models.inference.ai.azure.com/models",
headers=headers,
timeout=aiohttp.ClientTimeout(total=10)
) as response:
return response.status == 200
except Exception:
return False
class MFAManager:
"""Multi-factor authentication for enhanced security."""
def __init__(self):
self.totp_manager = TOTPManager()
self.backup_codes = BackupCodeManager()
def setup_mfa(self, user_id: str) -> MFASetupResult:
"""Set up MFA for user account."""
# Generate TOTP secret
totp_secret = self.totp_manager.generate_secret()
# Generate backup codes
backup_codes = self.backup_codes.generate_codes(user_id, count=10)
# Store encrypted MFA data
mfa_data = {
"user_id": user_id,
"totp_secret": self._encrypt_secret(totp_secret),
"backup_codes": [self._hash_backup_code(code) for code in backup_codes],
"enabled": False, # Not enabled until first successful verification
"created_at": datetime.utcnow()
}
self._store_mfa_data(user_id, mfa_data)
return MFASetupResult(
qr_code=self.totp_manager.generate_qr_code(totp_secret, user_id),
backup_codes=backup_codes,
secret=totp_secret
)
def verify_mfa(self, user_id: str, code: str) -> bool:
"""Verify MFA code."""
mfa_data = self._get_mfa_data(user_id)
if not mfa_data:
return False
# Try TOTP verification
totp_secret = self._decrypt_secret(mfa_data["totp_secret"])
if self.totp_manager.verify_code(totp_secret, code):
self._record_successful_mfa(user_id, "totp")
return True
# Try backup code verification
code_hash = self._hash_backup_code(code)
if code_hash in mfa_data["backup_codes"]:
# Remove used backup code
self._remove_backup_code(user_id, code_hash)
self._record_successful_mfa(user_id, "backup_code")
return True
# Record failed attempt
self._record_failed_mfa(user_id)
return False
class DataClassificationManager:
"""Classify and handle data based on sensitivity levels."""
def __init__(self):
self.classification_rules = {
"public": {
"encryption_required": False,
"audit_level": "basic",
"retention_days": 365
},
"internal": {
"encryption_required": True,
"audit_level": "standard",
"retention_days": 90
},
"confidential": {
"encryption_required": True,
"audit_level": "detailed",
"retention_days": 30
},
"restricted": {
"encryption_required": True,
"audit_level": "comprehensive",
"retention_days": 7
}
}
def classify_data(self, data: Any, context: Dict[str, Any]) -> DataClassification:
"""Classify data based on content and context."""
classification = DataClassification()
# Analyze content for sensitive patterns
if isinstance(data, str):
sensitivity_score = self._analyze_content_sensitivity(data)
classification.sensitivity_score = sensitivity_score
if sensitivity_score >= 0.8:
classification.level = "restricted"
elif sensitivity_score >= 0.6:
classification.level = "confidential"
elif sensitivity_score >= 0.3:
classification.level = "internal"
else:
classification.level = "public"
# Consider context
if context.get("contains_pii"):
classification.level = max(classification.level, "confidential")
if context.get("regulatory_data"):
classification.level = "restricted"
# Apply classification rules
rules = self.classification_rules[classification.level]
classification.encryption_required = rules["encryption_required"]
classification.audit_level = rules["audit_level"]
classification.retention_days = rules["retention_days"]
return classification
def _analyze_content_sensitivity(self, content: str) -> float:
"""Analyze content for sensitive information."""
sensitive_patterns = [
(r'\b\d{3}-\d{2}-\d{4}\b', 0.9), # SSN
(r'\b\d{4}[- ]?\d{4}[- ]?\d{4}[- ]?\d{4}\b', 0.8), # Credit card
(r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b', 0.3), # Email
(r'\b(?:password|secret|key|token)\s*[:=]\s*\S+', 0.9), # Credentials
(r'\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b', 0.2), # IP address
]
max_score = 0.0
for pattern, score in sensitive_patterns:
if re.search(pattern, content, re.IGNORECASE):
max_score = max(max_score, score)
return max_score
class EncryptionManager:
"""Manage encryption for data at rest and in transit."""
def __init__(self):
self.master_key = self._get_master_key()
self.aes_cipher = AESCipher(self.master_key)
self.rsa_manager = RSAKeyManager()
def encrypt_sensitive_data(self, data: bytes, classification: DataClassification) -> EncryptedData:
"""Encrypt data based on classification level."""
if not classification.encryption_required:
return EncryptedData(data=data, encrypted=False)
# Generate data encryption key (DEK)
dek = self._generate_dek()
# Encrypt data with DEK
encrypted_data = self.aes_cipher.encrypt(data, dek)
# Encrypt DEK with master key (envelope encryption)
encrypted_dek = self.aes_cipher.encrypt(dek, self.master_key)
return EncryptedData(
data=encrypted_data,
encrypted_key=encrypted_dek,
algorithm="AES-256-GCM",
key_version=self._get_key_version(),
encrypted=True
)
def decrypt_sensitive_data(self, encrypted_data: EncryptedData) -> bytes:
"""Decrypt data using envelope encryption."""
if not encrypted_data.encrypted:
return encrypted_data.data
# Decrypt DEK with master key
dek = self.aes_cipher.decrypt(encrypted_data.encrypted_key, self.master_key)
# Decrypt data with DEK
decrypted_data = self.aes_cipher.decrypt(encrypted_data.data, dek)
# Securely clear DEK from memory
self._secure_clear(dek)
return decrypted_data
def setup_tls_configuration(self) -> TLSConfig:
"""Configure TLS for secure communication."""
return TLSConfig(
min_version="TLSv1.3",
cipher_suites=[
"TLS_AES_256_GCM_SHA384",
"TLS_CHACHA20_POLY1305_SHA256",
"TLS_AES_128_GCM_SHA256"
],
certificate_pinning=True,
hsts_enabled=True,
ocsp_stapling=True
)
class SecureAPIClient:
"""Secure API client with comprehensive protection."""
def __init__(self):
self.session = None
self.rate_limiter = RateLimiter()
self.request_signer = RequestSigner()
async def create_secure_session(self) -> aiohttp.ClientSession:
"""Create secure HTTP session with protection."""
# TLS configuration
ssl_context = ssl.create_default_context()
ssl_context.minimum_version = ssl.TLSVersion.TLSv1_3
ssl_context.set_ciphers('ECDHE+AESGCM:ECDHE+CHACHA20:DHE+AESGCM:DHE+CHACHA20:!aNULL:!MD5:!DSS')
# Certificate pinning
ssl_context.check_hostname = True
ssl_context.verify_mode = ssl.CERT_REQUIRED
# Create connector with security settings
connector = aiohttp.TCPConnector(
ssl=ssl_context,
limit=20, # Limit concurrent connections
limit_per_host=5,
ttl_dns_cache=300,
use_dns_cache=True,
keepalive_timeout=30,
enable_cleanup_closed=True
)
# Security headers
headers = {
"User-Agent": "Aurelis/2.0.0 Security-Enhanced",
"Accept": "application/json",
"Accept-Encoding": "gzip, deflate",
"X-Content-Type-Options": "nosniff",
"X-Frame-Options": "DENY",
"X-XSS-Protection": "1; mode=block",
"Strict-Transport-Security": "max-age=31536000; includeSubDomains"
}
# Timeout configuration
timeout = aiohttp.ClientTimeout(
total=60,
connect=10,
sock_read=45
)
session = aiohttp.ClientSession(
connector=connector,
timeout=timeout,
headers=headers,
trace_configs=[self._create_trace_config()]
)
return session
async def secure_request(
self,
method: str,
url: str,
data: Optional[Dict[str, Any]] = None,
headers: Optional[Dict[str, str]] = None
) -> aiohttp.ClientResponse:
"""Make secure API request with protection."""
# Rate limiting
await self.rate_limiter.acquire()
# Request preparation
prepared_headers = self._prepare_security_headers(headers or {})
# Request signing
if data:
signature = self.request_signer.sign_request(method, url, data)
prepared_headers["X-Request-Signature"] = signature
# Input validation
self._validate_request_input(url, data)
session = await self.create_secure_session()
try:
async with session.request(
method=method,
url=url,
json=data,
headers=prepared_headers
) as response:
# Response validation
await self._validate_response(response)
return response
finally:
await session.close()
class RequestValidator:
"""Validate API requests and responses for security."""
def __init__(self):
self.content_limits = {
"max_prompt_length": 50000,
"max_system_prompt_length": 10000,
"max_metadata_size": 1024
}
self.dangerous_patterns = [
r'<script\b[^<]*(?:(?!<\/script>)<[^<]*)*<\/script>', # Script injection
r'javascript:', # JavaScript URLs
r'data:text\/html', # Data URLs
r'vbscript:', # VBScript URLs
r'\bon\w+\s*=', # Event handlers
]
def validate_model_request(self, request: ModelRequest) -> ValidationResult:
"""Validate model request for security issues."""
result = ValidationResult()
# Length validation
if len(request.prompt) > self.content_limits["max_prompt_length"]:
result.add_error("Prompt exceeds maximum length")
if request.system_prompt and len(request.system_prompt) > self.content_limits["max_system_prompt_length"]:
result.add_error("System prompt exceeds maximum length")
# Content validation
if self._contains_dangerous_content(request.prompt):
result.add_error("Prompt contains potentially dangerous content")
if request.system_prompt and self._contains_dangerous_content(request.system_prompt):
result.add_error("System prompt contains potentially dangerous content")
# Metadata validation
if request.metadata:
metadata_size = len(json.dumps(request.metadata))
if metadata_size > self.content_limits["max_metadata_size"]:
result.add_error("Metadata exceeds maximum size")
# Parameter validation
if request.temperature < 0 or request.temperature > 2:
result.add_error("Temperature out of valid range")
if request.max_tokens is not None and (request.max_tokens < 1 or request.max_tokens > 100000):
result.add_error("max_tokens out of valid range")
return result
def _contains_dangerous_content(self, content: str) -> bool:
"""Check for dangerous content patterns."""
for pattern in self.dangerous_patterns:
if re.search(pattern, content, re.IGNORECASE):
return True
return False
class RBACManager:
"""Role-based access control for Aurelis."""
def __init__(self):
self.roles = {
"viewer": {
"permissions": ["models.view", "health.check"],
"model_access": ["gpt-4o-mini"],
"daily_token_limit": 1000,
"features": ["basic_generation"]
},
"developer": {
"permissions": ["models.view", "models.use", "analysis.run"],
"model_access": ["gpt-4o-mini", "codestral-2501", "cohere-command-r"],
"daily_token_limit": 10000,
"features": ["generation", "analysis", "documentation"]
},
"senior_developer": {
"permissions": ["models.view", "models.use", "analysis.run", "optimization.use"],
"model_access": ["all"],
"daily_token_limit": 25000,
"features": ["generation", "analysis", "documentation", "optimization"]
},
"architect": {
"permissions": ["models.view", "models.use", "analysis.run", "optimization.use", "admin.config"],
"model_access": ["all"],
"daily_token_limit": 50000,
"features": ["all"]
},
"admin": {
"permissions": ["*"],
"model_access": ["all"],
"daily_token_limit": 100000,
"features": ["all"]
}
}
self.user_roles = {}
self.session_manager = SessionManager()
def assign_role(self, user_id: str, role: str, assigned_by: str) -> bool:
"""Assign role to user."""
if role not in self.roles:
raise SecurityError(f"Invalid role: {role}")
# Check if assigner has permission
if not self._can_assign_role(assigned_by, role):
raise SecurityError("Insufficient permissions to assign role")
self.user_roles[user_id] = {
"role": role,
"assigned_by": assigned_by,
"assigned_at": datetime.utcnow(),
"active": True
}
# Audit log
self._log_role_assignment(user_id, role, assigned_by)
return True
def check_permission(self, user_id: str, permission: str) -> bool:
"""Check if user has specific permission."""
user_role_data = self.user_roles.get(user_id)
if not user_role_data or not user_role_data["active"]:
return False
role = user_role_data["role"]
role_permissions = self.roles[role]["permissions"]
# Check for wildcard permission
if "*" in role_permissions:
return True
# Check exact permission
if permission in role_permissions:
return True
# Check permission hierarchy
return self._check_permission_hierarchy(permission, role_permissions)
def check_model_access(self, user_id: str, model_type: str) -> bool:
"""Check if user can access specific model."""
user_role_data = self.user_roles.get(user_id)
if not user_role_data or not user_role_data["active"]:
return False
role = user_role_data["role"]
model_access = self.roles[role]["model_access"]
return "all" in model_access or model_type in model_access
def get_token_limit(self, user_id: str) -> int:
"""Get daily token limit for user."""
user_role_data = self.user_roles.get(user_id)
if not user_role_data or not user_role_data["active"]:
return 0
role = user_role_data["role"]
return self.roles[role]["daily_token_limit"]
class AdvancedRateLimiter:
"""Advanced rate limiting with multiple strategies."""
def __init__(self):
self.redis_client = redis.Redis()
self.rate_limits = {
"per_second": 10,
"per_minute": 100,
"per_hour": 1000,
"per_day": 10000
}
self.burst_limits = {
"burst_size": 20,
"burst_window": 10 # seconds
}
async def check_rate_limit(
self,
identifier: str,
endpoint: str,
user_role: str = "developer"
) -> RateLimitResult:
"""Check rate limits with multiple time windows."""
current_time = time.time()
result = RateLimitResult()
# Adjust limits based on user role
limits = self._get_role_based_limits(user_role)
# Check each time window
for window, limit in limits.items():
window_key = f"rate_limit:{identifier}:{endpoint}:{window}"
window_seconds = self._get_window_seconds(window)
# Get current count
current_count = await self._get_window_count(window_key, window_seconds)
if current_count >= limit:
result.allowed = False
result.limit_exceeded = window
result.reset_time = current_time + window_seconds
result.retry_after = window_seconds
break
# Update rate limit info
result.limits[window] = {
"limit": limit,
"remaining": limit - current_count,
"reset_time": current_time + window_seconds
}
# Check burst limit
if result.allowed:
burst_allowed = await self._check_burst_limit(identifier, endpoint)
if not burst_allowed:
result.allowed = False
result.limit_exceeded = "burst"
result.retry_after = self.burst_limits["burst_window"]
# Record request if allowed
if result.allowed:
await self._record_request(identifier, endpoint)
return result
def _get_role_based_limits(self, role: str) -> Dict[str, int]:
"""Get rate limits based on user role."""
role_multipliers = {
"viewer": 0.1,
"developer": 1.0,
"senior_developer": 2.0,
"architect": 5.0,
"admin": 10.0
}
multiplier = role_multipliers.get(role, 1.0)
return {
window: int(limit * multiplier)
for window, limit in self.rate_limits.items()
}
class ComplianceAuditLogger:
"""Compliance-focused audit logging system."""
def __init__(self):
self.audit_handlers = {
"file": FileAuditHandler(),
"syslog": SyslogAuditHandler(),
"database": DatabaseAuditHandler(),
"siem": SIEMAuditHandler()
}
self.compliance_modes = {
"sox": SOXComplianceMode(),
"hipaa": HIPAAComplianceMode(),
"gdpr": GDPRComplianceMode(),
"pci": PCIComplianceMode()
}
def log_security_event(
self,
event_type: str,
severity: str,
description: str,
user_id: Optional[str] = None,
source_ip: Optional[str] = None,
context: Optional[Dict[str, Any]] = None
):
"""Log security event with compliance requirements."""
# Create comprehensive audit record
audit_record = {
"timestamp": datetime.utcnow().isoformat(),
"event_id": self._generate_event_id(),
"event_type": event_type,
"category": "security",
"severity": severity,
"description": description,
"user_id": user_id,
"source_ip": source_ip,
"session_id": self._get_session_id(),
"correlation_id": self._get_correlation_id(),
"context": self._sanitize_context(context or {}),
"system": "aurelis",
"version": "2.0.0"
}
# Add compliance-specific fields
for mode_name, mode in self.compliance_modes.items():
if mode.is_enabled():
audit_record.update(mode.get_compliance_fields(audit_record))
# Send to all configured handlers
for handler_name, handler in self.audit_handlers.items():
if handler.is_enabled():
try:
handler.log_event(audit_record)
except Exception as e:
# Log handler failure but don't block operation
self._log_handler_failure(handler_name, str(e))
def log_model_request(
self,
request_id: str,
model_type: str,
task_type: str,
user_id: str,
input_size: int,
output_size: int,
token_usage: Dict[str, int],
success: bool,
error_message: Optional[str] = None
):
"""Log model request with usage tracking."""
audit_record = {
"timestamp": datetime.utcnow().isoformat(),
"event_id": self._generate_event_id(),
"event_type": "model_request",
"category": "usage",
"request_id": request_id,
"model_type": model_type,
"task_type": task_type,
"user_id": user_id,
"input_size": input_size,
"output_size": output_size,
"token_usage": token_usage,
"success": success,
"error_message": error_message,
"session_id": self._get_session_id(),
"correlation_id": self._get_correlation_id()
}
# Calculate cost estimation
audit_record["estimated_cost"] = self._calculate_cost(model_type, token_usage)
# Add data classification
audit_record["data_classification"] = self._classify_request_data(audit_record)
# Send to audit handlers
for handler in self.audit_handlers.values():
if handler.is_enabled():
handler.log_event(audit_record)
class GDPRComplianceManager:
"""GDPR compliance management for personal data."""
def __init__(self):
self.data_processor = PersonalDataProcessor()
self.consent_manager = ConsentManager()
self.retention_manager = DataRetentionManager()
def process_personal_data(
self,
data: str,
user_id: str,
processing_purpose: str,
legal_basis: str
) -> ProcessingResult:
"""Process personal data with GDPR compliance."""
# Check consent
if legal_basis == "consent":
consent = self.consent_manager.check_consent(user_id, processing_purpose)
if not consent.is_valid():
raise GDPRError("Valid consent not found")
# Detect personal data
personal_data_detected = self.data_processor.detect_personal_data(data)
if personal_data_detected:
# Apply data minimization
minimized_data = self.data_processor.minimize_data(data, processing_purpose)
# Apply pseudonymization if required
if self._requires_pseudonymization(processing_purpose):
processed_data = self.data_processor.pseudonymize(minimized_data, user_id)
else:
processed_data = minimized_data
# Record processing activity
self._record_processing_activity(
user_id=user_id,
purpose=processing_purpose,
legal_basis=legal_basis,
data_categories=personal_data_detected.categories,
retention_period=self._get_retention_period(processing_purpose)
)
return ProcessingResult(
data=processed_data,
personal_data_detected=True,
processing_recorded=True
)
return ProcessingResult(
data=data,
personal_data_detected=False,
processing_recorded=False
)
def handle_data_subject_request(
self,
request_type: str,
user_id: str,
verification_token: str
) -> DataSubjectResponse:
"""Handle GDPR data subject requests."""
# Verify request
if not self._verify_data_subject_identity(user_id, verification_token):
raise GDPRError("Identity verification failed")
if request_type == "access":
return self._handle_access_request(user_id)
elif request_type == "rectification":
return self._handle_rectification_request(user_id)
elif request_type == "erasure":
return self._handle_erasure_request(user_id)
elif request_type == "portability":
return self._handle_portability_request(user_id)
elif request_type == "restriction":
return self._handle_restriction_request(user_id)
else:
raise GDPRError(f"Unsupported request type: {request_type}")
def _handle_erasure_request(self, user_id: str) -> DataSubjectResponse:
"""Handle right to erasure (right to be forgotten)."""
# Check if erasure is permitted
if not self._can_erase_data(user_id):
return DataSubjectResponse(
success=False,
message="Erasure not permitted due to legal obligations"
)
# Perform erasure across all systems
erasure_results = []
# Erase from primary database
db_result = self._erase_from_database(user_id)
erasure_results.append(db_result)
# Erase from cache systems
cache_result = self._erase_from_cache(user_id)
erasure_results.append(cache_result)
# Erase from backup systems
backup_result = self._erase_from_backups(user_id)
erasure_results.append(backup_result)
# Erase from audit logs (where permitted)
audit_result = self._erase_from_audit_logs(user_id)
erasure_results.append(audit_result)
all_successful = all(result.success for result in erasure_results)
return DataSubjectResponse(
success=all_successful,
message="Data erasure completed" if all_successful else "Partial erasure completed",
details=erasure_results
)
class DDoSProtectionManager:
"""DDoS protection and attack mitigation."""
def __init__(self):
self.request_tracker = RequestTracker()
self.anomaly_detector = AnomalyDetector()
self.response_generator = ThreatResponseGenerator()
async def analyze_request(
self,
request: aiohttp.web.Request
) -> ThreatAnalysisResult:
"""Analyze incoming request for DDoS patterns."""
client_ip = self._get_client_ip(request)
user_agent = request.headers.get("User-Agent", "")
analysis = ThreatAnalysisResult()
# Rate analysis
request_rate = await self.request_tracker.get_request_rate(client_ip)
if request_rate > self._get_rate_threshold():
analysis.threat_level = "high"
analysis.threat_type = "rate_based_ddos"
analysis.confidence = 0.9
# Pattern analysis
pattern_anomaly = self.anomaly_detector.detect_request_pattern_anomaly(
client_ip, request.method, request.path_qs
)
if pattern_anomaly.is_anomalous:
analysis.threat_level = max(analysis.threat_level, "medium")
analysis.threat_type = "pattern_based_attack"
analysis.confidence = max(analysis.confidence, pattern_anomaly.confidence)
# User agent analysis
ua_analysis = self._analyze_user_agent(user_agent)
if ua_analysis.is_suspicious:
analysis.threat_level = max(analysis.threat_level, "low")
analysis.threat_type = "automated_attack"
analysis.confidence = max(analysis.confidence, ua_analysis.confidence)
# Geographic analysis
geo_analysis = await self._analyze_geographic_patterns(client_ip)
if geo_analysis.is_suspicious:
analysis.threat_level = max(analysis.threat_level, "medium")
analysis.threat_type = "geographic_anomaly"
analysis.confidence = max(analysis.confidence, geo_analysis.confidence)
return analysis
async def apply_protection_measures(
self,
analysis: ThreatAnalysisResult,
client_ip: str
) -> ProtectionResponse:
"""Apply appropriate protection measures based on threat analysis."""
if analysis.threat_level == "high":
# Immediate blocking
await self._block_ip(client_ip, duration=3600) # 1 hour
return ProtectionResponse(
action="block",
duration=3600,
reason=f"High threat detected: {analysis.threat_type}"
)
elif analysis.threat_level == "medium":
# Rate limiting
await self._apply_strict_rate_limit(client_ip)
return ProtectionResponse(
action="rate_limit",
limit="1_per_second",
reason=f"Medium threat detected: {analysis.threat_type}"
)
elif analysis.threat_level == "low":
# Monitoring
await self._increase_monitoring(client_ip)
return ProtectionResponse(
action="monitor",
reason=f"Low threat detected: {analysis.threat_type}"
)
return ProtectionResponse(action="allow")
class InputSanitizer:
"""Comprehensive input validation and sanitization."""
def __init__(self):
self.sql_injection_patterns = [
r'(\%27)|(\')|(\-\-)|(\%23)|(#)',
r'((\%3D)|(=))[^\n]*((\%27)|(\')|(\-\-)|(\%3B)|(;))',
r'\w*((\%27)|(\'))((\%6F)|o|(\%4F))((\%72)|r|(\%52))',
r'((\%27)|(\'))union',
]
self.xss_patterns = [
r'<script\b[^<]*(?:(?!<\/script>)<[^<]*)*<\/script>',
r'javascript:',
r'on\w+\s*=',
r'<iframe\b[^<]*(?:(?!<\/iframe>)<[^<]*)*<\/iframe>',
]
self.command_injection_patterns = [
r'[;&|`\$\(\)]',
r'(\.\./)+',
r'/etc/passwd',
r'/bin/sh',
]
def sanitize_model_request(self, request: ModelRequest) -> ModelRequest:
"""Sanitize model request input."""
# Sanitize prompt
sanitized_prompt = self._sanitize_text_input(request.prompt)
# Sanitize system prompt
sanitized_system_prompt = None
if request.system_prompt:
sanitized_system_prompt = self._sanitize_text_input(request.system_prompt)
# Sanitize metadata
sanitized_metadata = None
if request.metadata:
sanitized_metadata = self._sanitize_metadata(request.metadata)
# Validate parameters
self._validate_parameters(request)
return ModelRequest(
prompt=sanitized_prompt,
model_type=request.model_type,
task_type=request.task_type,
system_prompt=sanitized_system_prompt,
temperature=request.temperature,
max_tokens=request.max_tokens,
metadata=sanitized_metadata
)
def _sanitize_text_input(self, text: str) -> str:
"""Sanitize text input for security threats."""
# Check for SQL injection
for pattern in self.sql_injection_patterns:
if re.search(pattern, text, re.IGNORECASE):
raise SecurityError("Potential SQL injection detected")
# Check for XSS
for pattern in self.xss_patterns:
if re.search(pattern, text, re.IGNORECASE):
raise SecurityError("Potential XSS attack detected")
# Check for command injection
for pattern in self.command_injection_patterns:
if re.search(pattern, text):
raise SecurityError("Potential command injection detected")
# HTML encoding for special characters
sanitized = html.escape(text)
# URL decoding to prevent double encoding attacks
sanitized = urllib.parse.unquote(sanitized)
# Remove null bytes
sanitized = sanitized.replace('\x00', '')
return sanitized
class KeyManagementSystem:
"""Enterprise key management system."""
def __init__(self):
self.hsm_client = HSMClient() # Hardware Security Module
self.key_store = SecureKeyStore()
self.key_rotation_manager = KeyRotationManager()
def create_master_key(self, key_purpose: str) -> str:
"""Create new master key in HSM."""
key_spec = {
"key_usage": ["encrypt", "decrypt"],
"key_size": 256,
"algorithm": "AES",
"purpose": key_purpose,
"rotation_period": 90 # days
}
# Generate key in HSM
key_id = self.hsm_client.generate_key(key_spec)
# Store key metadata
key_metadata = {
"key_id": key_id,
"purpose": key_purpose,
"created_at": datetime.utcnow(),
"algorithm": "AES-256",
"status": "active",
"rotation_schedule": self._calculate_rotation_schedule(90)
}
self.key_store.store_metadata(key_id, key_metadata)
# Audit log
self._log_key_creation(key_id, key_purpose)
return key_id
def rotate_key(self, old_key_id: str) -> str:
"""Rotate encryption key."""
old_key_metadata = self.key_store.get_metadata(old_key_id)
if not old_key_metadata:
raise KeyManagementError("Key not found")
# Create new key
new_key_id = self.create_master_key(old_key_metadata["purpose"])
# Re-encrypt data with new key
self.key_rotation_manager.re_encrypt_data(old_key_id, new_key_id)
# Mark old key as deprecated
old_key_metadata["status"] = "deprecated"
old_key_metadata["deprecated_at"] = datetime.utcnow()
old_key_metadata["replaced_by"] = new_key_id
self.key_store.update_metadata(old_key_id, old_key_metadata)
# Schedule old key destruction
self._schedule_key_destruction(old_key_id, days=30)
# Audit log
self._log_key_rotation(old_key_id, new_key_id)
return new_key_id
def encrypt_with_envelope(self, data: bytes, purpose: str) -> EnvelopeEncryptionResult:
"""Encrypt data using envelope encryption."""
# Get or create master key
master_key_id = self._get_master_key_for_purpose(purpose)
# Generate data encryption key (DEK)
dek = self._generate_dek()
# Encrypt data with DEK
encrypted_data = self._encrypt_data(data, dek)
# Encrypt DEK with master key
encrypted_dek = self.hsm_client.encrypt(dek, master_key_id)
# Clear DEK from memory
self._secure_clear(dek)
return EnvelopeEncryptionResult(
encrypted_data=encrypted_data,
encrypted_dek=encrypted_dek,
master_key_id=master_key_id,
algorithm="AES-256-GCM"
)
class SecurityIncidentResponseManager:
"""Automated security incident response system."""
def __init__(self):
self.alert_manager = AlertManager()
self.response_playbooks = ResponsePlaybookManager()
self.forensics_collector = ForensicsCollector()
async def handle_security_incident(
self,
incident_type: str,
severity: str,
context: Dict[str, Any]
) -> IncidentResponse:
"""Handle security incident with automated response."""
# Create incident record
incident_id = self._create_incident_record(incident_type, severity, context)
# Get appropriate response playbook
playbook = self.response_playbooks.get_playbook(incident_type, severity)
response = IncidentResponse(incident_id=incident_id)
try:
# Execute immediate response steps
immediate_actions = await self._execute_immediate_response(playbook, context)
response.immediate_actions = immediate_actions
# Collect forensic evidence
if playbook.requires_forensics:
forensic_data = await self.forensics_collector.collect_evidence(context)
response.forensic_data = forensic_data
# Execute containment measures
containment_actions = await self._execute_containment(playbook, context)
response.containment_actions = containment_actions
# Notify stakeholders
notifications = await self._send_notifications(incident_type, severity, context)
response.notifications = notifications
# Schedule follow-up actions
follow_up_tasks = self._schedule_follow_up(playbook, incident_id)
response.follow_up_tasks = follow_up_tasks
response.status = "handled"
except Exception as e:
response.status = "failed"
response.error = str(e)
# Escalate on failure
await self._escalate_incident(incident_id, str(e))
# Update incident record
self._update_incident_record(incident_id, response)
return response
async def _execute_immediate_response(
self,
playbook: ResponsePlaybook,
context: Dict[str, Any]
) -> List[ResponseAction]:
"""Execute immediate response actions."""
actions = []
for step in playbook.immediate_steps:
try:
if step.action_type == "block_ip":
await self._block_ip_address(step.parameters["ip"])
actions.append(ResponseAction("block_ip", "success", step.parameters))
elif step.action_type == "disable_user":
await self._disable_user_account(step.parameters["user_id"])
actions.append(ResponseAction("disable_user", "success", step.parameters))
elif step.action_type == "revoke_tokens":
await self._revoke_user_tokens(step.parameters["user_id"])
actions.append(ResponseAction("revoke_tokens", "success", step.parameters))
elif step.action_type == "increase_monitoring":
await self._increase_monitoring_level(step.parameters)
actions.append(ResponseAction("increase_monitoring", "success", step.parameters))
except Exception as e:
actions.append(ResponseAction(step.action_type, "failed", {"error": str(e)}))
return actions
class SecurityMonitoringSystem:
"""Real-time security monitoring and alerting."""
def __init__(self):
self.event_processor = SecurityEventProcessor()
self.anomaly_detector = SecurityAnomalyDetector()
self.alert_manager = SecurityAlertManager()
self.dashboard = SecurityDashboard()
async def process_security_event(self, event: SecurityEvent):
"""Process security event for threats and anomalies."""
# Enrich event with context
enriched_event = await self._enrich_security_event(event)
# Analyze for known threat patterns
threat_analysis = await self.event_processor.analyze_threat_patterns(enriched_event)
if threat_analysis.threat_detected:
await self._handle_threat_detection(enriched_event, threat_analysis)
# Analyze for anomalies
anomaly_analysis = await self.anomaly_detector.detect_anomalies(enriched_event)
if anomaly_analysis.anomaly_detected:
await self._handle_anomaly_detection(enriched_event, anomaly_analysis)
# Update security metrics
await self._update_security_metrics(enriched_event)
# Update dashboard
await self.dashboard.update_real_time_data(enriched_event)
async def _enrich_security_event(self, event: SecurityEvent) -> EnrichedSecurityEvent:
"""Enrich security event with additional context."""
enriched = EnrichedSecurityEvent(event)
# Add geographic information
if event.source_ip:
geo_info = await self._get_geographic_info(event.source_ip)
enriched.geographic_info = geo_info
# Add threat intelligence
threat_intel = await self._get_threat_intelligence(event)
enriched.threat_intelligence = threat_intel
# Add user context
if event.user_id:
user_context = await self._get_user_context(event.user_id)
enriched.user_context = user_context
# Add historical context
historical_context = await self._get_historical_context(event)
enriched.historical_context = historical_context
return enriched
def generate_security_report(self, time_period: str) -> SecurityReport:
"""Generate comprehensive security report."""
report = SecurityReport(period=time_period)
# Security metrics
report.metrics = self._calculate_security_metrics(time_period)
# Threat summary
report.threats = self._summarize_threats(time_period)
# Vulnerability assessment
report.vulnerabilities = self._assess_vulnerabilities()
# Compliance status
report.compliance = self._check_compliance_status()
# Recommendations
report.recommendations = self._generate_security_recommendations()
return report
Last Updated: December 2024
Version: 2.0.0
Security Classification: Internal Use
Author: Gamecooler19 (Lead Developer at Kanopus)
Aurelis - Where AI meets enterprise code development