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import asyncio
from datetime import datetime, timedelta
from typing import Any, Dict, List, Optional, Callable
from collections import defaultdict, deque
from fastmcp.utilities.logging import get_logger
logger = get_logger(__name__)
class PolicyMonitor:
"""Monitor for policy violations."""
def __init__(self, policy_engine=None):
"""Initialize the policy monitor.
Args:
policy_engine: Policy engine instance to monitor
"""
self.policy_engine = policy_engine
self.violation_history = deque(maxlen=1000) # Keep last 1000 violations
self.actor_violations = defaultdict(int) # Track violations per actor
async def __call__(self, action_context) -> Optional[Dict[str, Any]]:
"""Monitor an action for policy violations."""
try:
# Check for policy violations (works with or without policy engine)
violations = await self._check_policy_violations(action_context)
if violations:
# Record violation
violation_record = {
"type": "violation",
"severity": self._assess_violation_severity(violations),
"violations": violations,
"actor_id": action_context.actor_id,
"action_id": action_context.action_id,
"timestamp": datetime.utcnow().isoformat()
}
self.violation_history.append(violation_record)
self.actor_violations[action_context.actor_id] += 1
return violation_record
return None
except Exception as e:
logger.error(f"Policy monitor error: {e}")
return None
async def _check_policy_violations(self, action_context) -> List[Dict[str, Any]]:
"""Check for policy violations in an action."""
violations = []
try:
# Simulate policy checking
# In a real implementation, this would use the actual policy engine
# Check for suspicious patterns
if action_context.action_type == "admin_access" and action_context.actor_id.startswith("guest"):
violations.append({
"rule": "admin_access_restriction",
"message": "Guest user attempting admin access",
"severity": "high"
})
# Check for rate limiting
recent_violations = [v for v in self.violation_history
if v.get("actor_id") == action_context.actor_id
and datetime.fromisoformat(v["timestamp"]) > datetime.utcnow() - timedelta(minutes=5)]
if len(recent_violations) >= 3:
violations.append({
"rule": "rate_limit_exceeded",
"message": f"Actor {action_context.actor_id} has {len(recent_violations)} recent violations",
"severity": "medium"
})
# Check for resource access patterns
if action_context.resource_id and "sensitive" in action_context.resource_id.lower():
if not action_context.metadata.get("authorized"):
violations.append({
"rule": "unauthorized_sensitive_access",
"message": "Unauthorized access to sensitive resource",
"severity": "critical"
})
except Exception as e:
logger.error(f"Error checking policy violations: {e}")
return violations
def _assess_violation_severity(self, violations: List[Dict[str, Any]]) -> str:
"""Assess the overall severity of violations."""
if not violations:
return "low"
severities = [v.get("severity", "low") for v in violations]
if "critical" in severities:
return "critical"
elif "high" in severities:
return "high"
elif "medium" in severities:
return "medium"
else:
return "low"
def get_violation_stats(self) -> Dict[str, Any]:
"""Get violation statistics."""
return {
"total_violations": len(self.violation_history),
"actor_violations": dict(self.actor_violations),
"recent_violations": len([v for v in self.violation_history
if datetime.fromisoformat(v["timestamp"]) > datetime.utcnow() - timedelta(hours=1)])
}
class LedgerMonitor:
"""Monitor for ledger inconsistencies and anomalies."""
def __init__(self, ledger=None):
"""Initialize the ledger monitor.
Args:
ledger: Provenance ledger instance to monitor
"""
self.ledger = ledger
self.integrity_checks = deque(maxlen=100) # Keep last 100 integrity checks
async def __call__(self, action_context) -> Optional[Dict[str, Any]]:
"""Monitor ledger for inconsistencies."""
try:
if not self.ledger:
return None
# Check ledger integrity
integrity_issues = await self._check_ledger_integrity()
if integrity_issues:
# Record integrity issue
issue_record = {
"type": "anomaly",
"severity": self._assess_integrity_severity(integrity_issues),
"issues": integrity_issues,
"action_id": action_context.action_id,
"timestamp": datetime.utcnow().isoformat()
}
self.integrity_checks.append(issue_record)
return issue_record
return None
except Exception as e:
logger.error(f"Ledger monitor error: {e}")
return None
async def _check_ledger_integrity(self) -> List[Dict[str, Any]]:
"""Check ledger for integrity issues."""
issues = []
try:
# Check chain integrity
is_valid = self.ledger.verify_chain_integrity()
if not is_valid:
issues.append({
"type": "chain_integrity",
"message": "Ledger chain integrity verification failed",
"severity": "critical"
})
# Check for missing blocks
stats = self.ledger.get_ledger_statistics()
if stats.get("total_entries", 0) > 0 and stats.get("total_blocks", 0) == 0:
issues.append({
"type": "missing_blocks",
"message": "Entries exist but no blocks found",
"severity": "high"
})
# Check for unsealed blocks
# This would require additional ledger methods to check for unsealed blocks
except Exception as e:
logger.error(f"Error checking ledger integrity: {e}")
issues.append({
"type": "integrity_check_error",
"message": f"Error during integrity check: {str(e)}",
"severity": "medium"
})
return issues
def _assess_integrity_severity(self, issues: List[Dict[str, Any]]) -> str:
"""Assess the overall severity of integrity issues."""
if not issues:
return "low"
severities = [i.get("severity", "low") for i in issues]
if "critical" in severities:
return "critical"
elif "high" in severities:
return "high"
elif "medium" in severities:
return "medium"
else:
return "low"
def get_integrity_stats(self) -> Dict[str, Any]:
"""Get integrity check statistics."""
return {
"total_checks": len(self.integrity_checks),
"recent_issues": len([i for i in self.integrity_checks
if datetime.fromisoformat(i["timestamp"]) > datetime.utcnow() - timedelta(hours=1)])
}
class AnomalyDetector:
"""Detector for behavioral anomalies."""
def __init__(self):
"""Initialize the anomaly detector."""
self.actor_patterns = defaultdict(lambda: {
"action_counts": defaultdict(int),
"resource_access": defaultdict(int),
"session_times": deque(maxlen=100),
"last_seen": None
})
self.global_patterns = {
"action_frequency": defaultdict(int),
"resource_access": defaultdict(int),
"time_patterns": defaultdict(int)
}
async def __call__(self, action_context) -> Optional[Dict[str, Any]]:
"""Detect anomalies in an action."""
try:
# Update patterns
self._update_patterns(action_context)
# Detect anomalies
anomalies = await self._detect_anomalies(action_context)
if anomalies:
return {
"type": "anomaly",
"severity": self._assess_anomaly_severity(anomalies),
"anomalies": anomalies,
"actor_id": action_context.actor_id,
"action_id": action_context.action_id,
"timestamp": datetime.utcnow().isoformat()
}
return None
except Exception as e:
logger.error(f"Anomaly detector error: {e}")
return None
def _update_patterns(self, action_context):
"""Update behavioral patterns."""
actor_id = action_context.actor_id
actor_data = self.actor_patterns[actor_id]
# Update action counts
actor_data["action_counts"][action_context.action_type] += 1
self.global_patterns["action_frequency"][action_context.action_type] += 1
# Update resource access
if action_context.resource_id:
actor_data["resource_access"][action_context.resource_id] += 1
self.global_patterns["resource_access"][action_context.resource_id] += 1
# Update session times
actor_data["session_times"].append(action_context.timestamp)
actor_data["last_seen"] = action_context.timestamp
# Update time patterns
hour = action_context.timestamp.hour
self.global_patterns["time_patterns"][hour] += 1
async def _detect_anomalies(self, action_context) -> List[Dict[str, Any]]:
"""Detect anomalies in the action."""
anomalies = []
actor_id = action_context.actor_id
actor_data = self.actor_patterns[actor_id]
# Check for unusual action frequency
if len(actor_data["session_times"]) >= 10:
recent_actions = [t for t in actor_data["session_times"]
if t > datetime.utcnow() - timedelta(minutes=5)]
if len(recent_actions) > 20: # More than 20 actions in 5 minutes
anomalies.append({
"type": "high_frequency",
"message": f"Actor {actor_id} performing {len(recent_actions)} actions in 5 minutes",
"severity": "medium"
})
# Check for unusual time patterns
current_hour = action_context.timestamp.hour
if current_hour < 6 or current_hour > 22: # Unusual hours
if actor_data["action_counts"].get(action_context.action_type, 0) < 5: # New action type
anomalies.append({
"type": "unusual_timing",
"message": f"Actor {actor_id} performing {action_context.action_type} at unusual hour {current_hour}",
"severity": "low"
})
# Check for new resource access
if action_context.resource_id:
if actor_data["resource_access"].get(action_context.resource_id, 0) == 1:
# First time accessing this resource
anomalies.append({
"type": "new_resource_access",
"message": f"Actor {actor_id} accessing new resource {action_context.resource_id}",
"severity": "low"
})
# Check for privilege escalation patterns
if action_context.action_type in ["admin_access", "root_access", "privilege_escalation"]:
if actor_data["action_counts"].get(action_context.action_type, 0) == 1:
# First time performing privileged action
anomalies.append({
"type": "privilege_escalation",
"message": f"Actor {actor_id} attempting privileged action for first time",
"severity": "high"
})
return anomalies
def _assess_anomaly_severity(self, anomalies: List[Dict[str, Any]]) -> str:
"""Assess the overall severity of anomalies."""
if not anomalies:
return "low"
severities = [a.get("severity", "low") for a in anomalies]
if "high" in severities:
return "high"
elif "medium" in severities:
return "medium"
else:
return "low"
def get_anomaly_stats(self) -> Dict[str, Any]:
"""Get anomaly detection statistics."""
return {
"tracked_actors": len(self.actor_patterns),
"global_action_types": len(self.global_patterns["action_frequency"]),
"global_resources": len(self.global_patterns["resource_access"])
}
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