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المهن ذات الصلة SOC
استنادا إلى تصنيف SOC المهني
name safety-architecture version 1.0.0 description Framework for designing safeguards in autonomous systems including kill switches,
resource limits, anomaly detection, and human-in-the-loop patterns.
author QuantQuiver AI R&D license MIT category workflow tags ["safety","autonomous-systems","kill-switch","monitoring","risk-management","circuit-breaker","failsafe"] dependencies {"skills":[],"python":">=3.9","packages":["pyyaml"],"tools":["code_execution","bash"]} triggers ["safety architecture","kill switch","autonomous safeguards","circuit breaker","failsafe design","human in the loop","anomaly detection"]
Safety Architecture Framework
Purpose
A framework for designing safeguards in autonomous systems including kill switches, resource limits, anomaly detection, and human-in-the-loop patterns. Ensures autonomous systems fail safely and maintain human oversight.
Problem Space:
Autonomous systems can cause runaway damage if unchecked
Default behavior during failures often unsafe
Human oversight mechanisms afterthoughts
Resource exhaustion can cascade to other systems
Solution Approach:
Defense-in-depth safety layers
Fail-safe defaults
Mandatory human checkpoints
Resource isolation and limits
Comprehensive anomaly detection
When to Use
Designing any autonomous system
Systems that control resources (money, compute, data)
AI agents with tool access
Automated trading/scheduling systems
Any system requiring regulatory compliance
Production systems with business-critical operations
When NOT to Use
Simple scripts with no autonomous decision-making
Read-only analysis tools
Systems with no resource impact
Prototype/experimental code (but consider adding before production)
Core Instructions
Safety Layer Architecture
┌─────────────────────────────────────────────────────────────────┐
│ SAFETY LAYER ARCHITECTURE │
├─────────────────────────────────────────────────────────────────┤
│ │
│ Layer 5: Human Oversight │
│ ┌───────────────────────────────────────────────────────────┐ │
│ │ • Manual approval gates for critical actions │ │
│ │ • Alert escalation with response requirements │ │
│ │ • Audit logging with human review │ │
│ └───────────────────────────────────────────────────────────┘ │
│ │ │
│ Layer 4: Business Logic Guards │
│ ┌───────────────────────────────────────────────────────────┐ │
│ │ • Domain-specific validation rules │ │
│ │ • Value limits and thresholds │ │
│ │ • Timing and rate constraints │ │
│ └───────────────────────────────────────────────────────────┘ │
│ │ │
│ Layer 3: Anomaly Detection │
│ ┌───────────────────────────────────────────────────────────┐ │
│ │ • Statistical outlier detection │ │
│ │ • Behavioral drift monitoring │ │
│ │ • Pattern deviation alerts │ │
│ └───────────────────────────────────────────────────────────┘ │
│ │ │
│ Layer 2: Circuit Breakers │
│ ┌───────────────────────────────────────────────────────────┐ │
│ │ • Error rate thresholds │ │
│ │ • Consecutive failure limits │ │
│ │ • Automatic recovery with backoff │ │
│ └───────────────────────────────────────────────────────────┘ │
│ │ │
│ Layer 1: Resource Limits (Hard Stops) │
│ ┌───────────────────────────────────────────────────────────┐ │
│ │ • Memory limits │ │
│ │ • CPU/time limits │ │
│ │ • Cost/budget caps │ │
│ │ • Action count limits │ │
│ └───────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘
Standard Safety Components
1. Kill Switch Patterns from datetime import datetime, timedelta
from enum import Enum
import threading
import signal
import sys
class KillSwitchState (Enum ):
ACTIVE = "active"
PAUSED = "paused"
KILLED = "killed"
class KillSwitch :
"""
Global kill switch for autonomous system.
Features:
- Manual activation (API/CLI)
- Automatic activation on anomaly
- Graceful shutdown with cleanup
- State persistence for recovery
"""
def __init__ (self, cleanup_callback=None , timeout_seconds=30 ):
self .state = KillSwitchState.ACTIVE
self .cleanup_callback = cleanup_callback
self .timeout_seconds = timeout_seconds
self .activation_reason = None
self .activation_time = None
self ._lock = threading.Lock()
signal.signal(signal.SIGINT, self ._signal_handler)
signal.signal(signal.SIGTERM, self ._signal_handler)
def _signal_handler (self, signum, frame ):
"""Handle OS signals for graceful shutdown."""
self .activate(f"Received signal {signum} " )
def activate (self, reason: str ):
"""
Activate kill switch - stops all autonomous operations.
Args:
reason: Why the kill switch was activated
"""
with self ._lock:
if self .state == KillSwitchState.KILLED:
return
self .state = KillSwitchState.KILLED
self .activation_reason = reason
self .activation_time = datetime.now()
print (f"[KILL SWITCH ACTIVATED] {reason} " )
if self .cleanup_callback:
cleanup_thread = threading.Thread(
target=self .cleanup_callback
)
cleanup_thread.start()
cleanup_thread.join(timeout=self .timeout_seconds)
if cleanup_thread.is_alive():
print ("[KILL SWITCH] Cleanup timeout - forcing exit" )
def pause (self, reason: str ):
"""Pause operations without full shutdown."""
with self ._lock:
if self .state == KillSwitchState.ACTIVE:
self .state = KillSwitchState.PAUSED
self .activation_reason = reason
print (f"[SYSTEM PAUSED] {reason} " )
def resume (self ):
"""Resume from paused state."""
with self ._lock:
if self .state == KillSwitchState.PAUSED:
self .state = KillSwitchState.ACTIVE
self .activation_reason = None
print ("[SYSTEM RESUMED]" )
def check (self ) -> bool :
"""Check if operations should continue."""
return self .state == KillSwitchState.ACTIVE
@property
def is_active (self ) -> bool :
return self .state == KillSwitchState.ACTIVE
@property
def is_paused (self ) -> bool :
return self .state == KillSwitchState.PAUSED
@property
def is_killed (self ) -> bool :
return self .state == KillSwitchState.KILLED
2. Circuit Breaker Pattern from dataclasses import dataclass
from datetime import datetime, timedelta
from enum import Enum
import threading
class CircuitState (Enum ):
CLOSED = "closed"
OPEN = "open"
HALF_OPEN = "half_open"
@dataclass
class CircuitBreakerConfig :
failure_threshold: int = 5
success_threshold: int = 3
timeout_seconds: int = 60
half_open_max_calls: int = 3
class CircuitBreaker :
"""
Circuit breaker for protecting against cascading failures.
States:
- CLOSED: Normal operation, tracking failures
- OPEN: Failing, rejecting all calls
- HALF_OPEN: Testing if service recovered
"""
def __init__ (self, name: str , config: CircuitBreakerConfig = None ):
self .name = name
self .config = config or CircuitBreakerConfig()
self .state = CircuitState.CLOSED
self .failure_count = 0
self .success_count = 0
self .last_failure_time = None
self .half_open_calls = 0
self ._lock = threading.Lock()
def can_execute (self ) -> bool :
"""Check if call should be allowed."""
with self ._lock:
if self .state == CircuitState.CLOSED:
return True
if self .state == CircuitState.OPEN:
if self ._timeout_elapsed():
self ._transition_to_half_open()
return True
return False
if self .state == CircuitState.HALF_OPEN:
if self .half_open_calls < self .config.half_open_max_calls:
self .half_open_calls += 1
return True
return False
return False
def record_success (self ):
"""Record successful call."""
with self ._lock:
if self .state == CircuitState.HALF_OPEN:
self .success_count += 1
if self .success_count >= self .config.success_threshold:
self ._transition_to_closed()
elif self .state == CircuitState.CLOSED:
self .failure_count = 0
def record_failure (self ):
"""Record failed call."""
with self ._lock:
self .last_failure_time = datetime.now()
if self .state == CircuitState.HALF_OPEN:
self ._transition_to_open()
elif self .state == CircuitState.CLOSED:
self .failure_count += 1
if self .failure_count >= self .config.failure_threshold:
self ._transition_to_open()
def _timeout_elapsed (self ) -> bool :
if not self .last_failure_time:
return True
elapsed = datetime.now() - self .last_failure_time
return elapsed.total_seconds() >= self .config.timeout_seconds
def _transition_to_open (self ):
self .state = CircuitState.OPEN
print (f"[CIRCUIT BREAKER] {self.name} : OPEN (failures: {self.failure_count} )" )
def _transition_to_half_open (self ):
self .state = CircuitState.HALF_OPEN
self .half_open_calls = 0
self .success_count = 0
print (f"[CIRCUIT BREAKER] {self.name} : HALF_OPEN (testing recovery)" )
def _transition_to_closed (self ):
self .state = CircuitState.CLOSED
self .failure_count = 0
self .success_count = 0
print (f"[CIRCUIT BREAKER] {self.name} : CLOSED (recovered)" )
def __call__ (self, func ):
"""Decorator for wrapping functions with circuit breaker."""
def wrapper (*args, **kwargs ):
if not self .can_execute():
raise CircuitOpenError(f"Circuit {self.name} is open" )
try :
result = func(*args, **kwargs)
self .record_success()
return result
except Exception as e:
self .record_failure()
raise
return wrapper
class CircuitOpenError (Exception ):
pass
3. Resource Limiter from dataclasses import dataclass
from datetime import datetime, timedelta
from typing import Optional , Dict , Any
import threading
@dataclass
class ResourceLimits :
"""Configuration for resource limits."""
max_actions_per_hour: int = 1000
max_value_per_action: float = 10000.0
max_total_value_per_hour: float = 100000.0
max_api_calls_per_minute: int = 60
max_memory_mb: int = 1024
max_execution_time_seconds: int = 300
class ResourceLimiter :
"""
Tracks and enforces resource usage limits.
Prevents runaway consumption of:
- API calls
- Financial value
- Compute resources
- Time
"""
def __init__ (self, limits: ResourceLimits = None ):
self .limits = limits or ResourceLimits()
self .action_count = 0
self .total_value = 0.0
self .api_calls = []
self .start_time = datetime.now()
self .hour_start = datetime.now()
self ._lock = threading.Lock()
def check_action (self, value: float = 0.0 ) -> tuple [bool , str ]:
"""
Check if action is within limits.
Returns:
(allowed, reason) tuple
"""
with self ._lock:
self ._cleanup_old_records()
elapsed = (datetime.now() - self .start_time).total_seconds()
if elapsed > self .limits.max_execution_time_seconds:
return False , f"Max execution time exceeded ({elapsed:.0 f} s)"
if self .action_count >= self .limits.max_actions_per_hour:
return False , f"Max actions per hour exceeded ({self.action_count} )"
if value > self .limits.max_value_per_action:
return False , f"Action value ${value:.2 f} exceeds max ${self.limits.max_value_per_action:.2 f} "
if self .total_value + value > self .limits.max_total_value_per_hour:
return False , f"Total value would exceed limit (${self.total_value + value:.2 f} )"
return True , "OK"
def record_action (self, value: float = 0.0 ):
"""Record an action and its value."""
with self ._lock:
self .action_count += 1
self .total_value += value
def check_api_call (self ) -> tuple [bool , str ]:
"""Check if API call is within rate limit."""
with self ._lock:
now = datetime.now()
minute_ago = now - timedelta(minutes=1 )
self .api_calls = [t for t in self .api_calls if t > minute_ago]
if len (self .api_calls) >= self .limits.max_api_calls_per_minute:
return False , f"API rate limit exceeded ({len (self.api_calls)} /min)"
return True , "OK"
def record_api_call (self ):
"""Record an API call."""
with self ._lock:
self .api_calls.append(datetime.now())
def _cleanup_old_records (self ):
"""Reset hourly counters if hour elapsed."""
now = datetime.now()
if (now - self .hour_start).total_seconds() >= 3600 :
self .action_count = 0
self .total_value = 0.0
self .hour_start = now
def get_usage_report (self ) -> Dict [str , Any ]:
"""Get current resource usage."""
with self ._lock:
return {
"actions_this_hour" : self .action_count,
"actions_limit" : self .limits.max_actions_per_hour,
"value_this_hour" : self .total_value,
"value_limit" : self .limits.max_total_value_per_hour,
"api_calls_last_minute" : len (self .api_calls),
"api_limit" : self .limits.max_api_calls_per_minute,
"execution_seconds" : (datetime.now() - self .start_time).total_seconds(),
"execution_limit" : self .limits.max_execution_time_seconds,
}
4. Anomaly Detector from dataclasses import dataclass
from collections import deque
from typing import Optional , List
import statistics
import math
@dataclass
class AnomalyConfig :
window_size: int = 100
z_score_threshold: float = 3.0
min_samples: int = 10
consecutive_anomalies_alert: int = 3
class AnomalyDetector :
"""
Statistical anomaly detection for continuous metrics.
Uses Z-score method with rolling statistics.
"""
def __init__ (self, name: str , config: AnomalyConfig = None ):
self .name = name
self .config = config or AnomalyConfig()
self .values = deque(maxlen=self .config.window_size)
self .consecutive_anomalies = 0
def check (self, value: float ) -> tuple [bool , Optional [str ]]:
"""
Check if value is anomalous.
Returns:
(is_anomaly, reason) tuple
"""
if len (self .values) < self .config.min_samples:
self .values.append(value)
return False , None
mean = statistics.mean(self .values)
stdev = statistics.stdev(self .values)
if stdev == 0 :
self .values.append(value)
return False , None
z_score = abs ((value - mean) / stdev)
self .values.append(value)
if z_score > self .config.z_score_threshold:
self .consecutive_anomalies += 1
reason = f"Z-score {z_score:.2 f} > threshold {self.config.z_score_threshold} "
if self .consecutive_anomalies >= self .config.consecutive_anomalies_alert:
reason += f" (ALERT: {self.consecutive_anomalies} consecutive anomalies)"
return True , reason
else :
self .consecutive_anomalies = 0
return False , None
@property
def should_alert (self ) -> bool :
"""Check if anomaly pattern warrants alert."""
return self .consecutive_anomalies >= self .config.consecutive_anomalies_alert
5. Human-in-the-Loop Gate from dataclasses import dataclass
from datetime import datetime, timedelta
from enum import Enum
from typing import Optional , Callable
import uuid
class ApprovalStatus (Enum ):
PENDING = "pending"
APPROVED = "approved"
REJECTED = "rejected"
EXPIRED = "expired"
@dataclass
class ApprovalRequest :
id : str
action_type: str
description: str
value: float
context: dict
created_at: datetime
expires_at: datetime
status: ApprovalStatus = ApprovalStatus.PENDING
reviewer: Optional [str ] = None
reviewed_at: Optional [datetime] = None
review_notes: Optional [str ] = None
class HumanApprovalGate :
"""
Requires human approval for critical actions.
Features:
- Configurable approval thresholds
- Timeout handling
- Audit trail
- Notification hooks
"""
def __init__ (
self,
approval_timeout_minutes: int = 60 ,
notify_callback: Callable = None ,
auto_approve_below: float = 0.0
):
self .timeout_minutes = approval_timeout_minutes
self .notify_callback = notify_callback
self .auto_approve_below = auto_approve_below
self .pending_approvals: dict [str , ApprovalRequest] = {}
def request_approval (
self,
action_type: str ,
description: str ,
value: float ,
context: dict = None
) -> ApprovalRequest:
"""
Create approval request for critical action.
Returns:
ApprovalRequest object to track
"""
if value <= self .auto_approve_below:
request = ApprovalRequest(
id =str (uuid.uuid4()),
action_type=action_type,
description=description,
value=value,
context=context or {},
created_at=datetime.now(),
expires_at=datetime.now(),
status=ApprovalStatus.APPROVED,
reviewer="auto" ,
reviewed_at=datetime.now(),
review_notes="Auto-approved (below threshold)"
)
return request
request = ApprovalRequest(
id =str (uuid.uuid4()),
action_type=action_type,
description=description,
value=value,
context=context or {},
created_at=datetime.now(),
expires_at=datetime.now() + timedelta(minutes=self .timeout_minutes)
)
self .pending_approvals[request.id ] = request
if self .notify_callback:
self .notify_callback(request)
print (f"[APPROVAL REQUIRED] {request.id } : {description} (${value:.2 f} )" )
return request
def approve (
self,
request_id: str ,
reviewer: str ,
notes: str = None
) -> bool :
"""Approve a pending request."""
if request_id not in self .pending_approvals:
return False
request = self .pending_approvals[request_id]
if request.status != ApprovalStatus.PENDING:
return False
if datetime.now() > request.expires_at:
request.status = ApprovalStatus.EXPIRED
return False
request.status = ApprovalStatus.APPROVED
request.reviewer = reviewer
request.reviewed_at = datetime.now()
request.review_notes = notes
print (f"[APPROVED] {request_id} by {reviewer} " )
return True
def reject (
self,
request_id: str ,
reviewer: str ,
notes: str = None
) -> bool :
"""Reject a pending request."""
if request_id not in self .pending_approvals:
return False
request = self .pending_approvals[request_id]
if request.status != ApprovalStatus.PENDING:
return False
request.status = ApprovalStatus.REJECTED
request.reviewer = reviewer
request.reviewed_at = datetime.now()
request.review_notes = notes
print (f"[REJECTED] {request_id} by {reviewer} : {notes} " )
return True
def check_status (self, request_id: str ) -> ApprovalStatus:
"""Check approval status."""
if request_id not in self .pending_approvals:
return None
request = self .pending_approvals[request_id]
if request.status == ApprovalStatus.PENDING:
if datetime.now() > request.expires_at:
request.status = ApprovalStatus.EXPIRED
return request.status
Decision Framework When to Require Human Approval:
Actions above value threshold
First-time or unusual actions
Actions affecting external systems
Any irreversible action
Actions during anomaly state
Circuit Breaker vs Kill Switch:
Aspect Circuit Breaker Kill Switch Scope Single service/endpoint Entire system Trigger Automatic (errors) Manual or critical anomaly Recovery Automatic with backoff Manual restart required Use Case Service resilience Emergency stop
Templates
Complete Safety-Wrapped System class SafeAutonomousSystem :
"""
Template for autonomous system with full safety architecture.
"""
def __init__ (self, config: dict ):
self .resource_limiter = ResourceLimiter(ResourceLimits(
max_actions_per_hour=config.get("max_actions" , 1000 ),
max_value_per_action=config.get("max_value" , 10000 ),
max_total_value_per_hour=config.get("max_total" , 100000 )
))
self .circuit_breakers = {
"api" : CircuitBreaker("api" , CircuitBreakerConfig(
failure_threshold=5 ,
timeout_seconds=60
)),
"database" : CircuitBreaker("database" , CircuitBreakerConfig(
failure_threshold=3 ,
timeout_seconds=120
))
}
self .anomaly_detectors = {
"value" : AnomalyDetector("value" , AnomalyConfig(z_score_threshold=3.0 )),
"frequency" : AnomalyDetector("frequency" , AnomalyConfig(z_score_threshold=2.5 ))
}
self .approval_gate = HumanApprovalGate(
approval_timeout_minutes=60 ,
auto_approve_below=100.0
)
self .kill_switch = KillSwitch(cleanup_callback=self ._cleanup)
def execute_action (self, action: dict ) -> dict :
"""
Execute action through all safety layers.
"""
if not self .kill_switch.check():
return {"error" : "System is stopped" , "reason" : self .kill_switch.activation_reason}
value = action.get("value" , 0 )
allowed, reason = self .resource_limiter.check_action(value)
if not allowed:
return {"error" : "Resource limit exceeded" , "reason" : reason}
is_anomaly, anomaly_reason = self .anomaly_detectors["value" ].check(value)
if is_anomaly and self .anomaly_detectors["value" ].should_alert:
self .kill_switch.pause(f"Anomaly detected: {anomaly_reason} " )
return {"error" : "Anomaly detected - paused" , "reason" : anomaly_reason}
if not self .circuit_breakers["api" ].can_execute():
return {"error" : "Circuit open" , "service" : "api" }
if value > 1000 :
request = self .approval_gate.request_approval(
action_type=action.get("type" , "unknown" ),
description=action.get("description" , "" ),
value=value,
context=action
)
if request.status != ApprovalStatus.APPROVED:
return {"error" : "Approval required" , "request_id" : request.id }
try :
result = self ._do_action(action)
self .resource_limiter.record_action(value)
self .circuit_breakers["api" ].record_success()
return {"success" : True , "result" : result}
except Exception as e:
self .circuit_breakers["api" ].record_failure()
return {"error" : str (e)}
def _do_action (self, action: dict ):
"""Actual action implementation."""
pass
def _cleanup (self ):
"""Cleanup on kill switch activation."""
print ("Running cleanup..." )
Examples
Example 1: Trading System Safety Input : "Add safety controls to my automated trading system"
Output : Implementation with:
Position size limits per trade
Daily loss limits with auto-stop
Anomaly detection on trade frequency
Human approval for large trades
Kill switch for market anomalies
Example 2: AI Agent Safeguards Input : "Add safeguards to my autonomous AI agent"
Output : Implementation with:
API call rate limiting
Cost accumulation limits
Circuit breakers for external services
Human approval for destructive actions
Emergency stop capability
Validation Checklist Before deploying autonomous system:
Related Resources
Skill: repository-auditor - Security review of safety code
Skill: cicd-pipeline-generator - CI with safety tests
Pattern: Circuit Breaker (Martin Fowler)
Pattern: Bulkhead (Resilience patterns)
Changelog
1.0.0 (January 2026)
Initial release
Kill switch implementation
Circuit breaker pattern
Resource limiter
Anomaly detection
Human-in-the-loop gates
