---
name: immune-system
metadata:
  version: 1.0.0
  status: active
description: >
  Sicherheitssystem fuer BACH Evolution — schuetzt vor destruktiven Veraenderungen.
---

# Immune System

> **Sicherheitssystem für Claude OS Evolution - schützt vor destruktiven Veränderungen**

---

## Metadaten

| Feld | Wert |
|------|------|
| **Name** | immune-system |
| **Version** | 1.0.0 |
| **Kategorie** | Sicherheitssystem |
| **Priorität** | KRITISCH |
| **Abhängigkeiten** | evolution-tools |
| **Erstellt** | 2025-12-20 |

---

## 🛡️ Konzept: Evolutionäres Immunsystem

Wie ein biologisches Immunsystem schützt dieses System Claude OS vor schädlichen "Mutationen":

```
┌─────────────────────────────────────────────────────────────────┐
│                     IMMUNE SYSTEM LAYERS                         │
├─────────────────────────────────────────────────────────────────┤
│                                                                  │
│  ┌─────────────┐    ┌─────────────┐    ┌─────────────┐          │
│  │   DETECT    │    │  QUARANTINE │    │   NEUTRALIZE │          │
│  │ Bedrohungen │───→│  Isolieren  │───→│   Entfernen │          │
│  │  erkennen   │    │             │    │             │          │
│  └─────────────┘    └─────────────┘    └─────────────┘          │
│         │                   │                   │               │
│         ▼                   ▼                   ▼               │
│  ┌─────────────┐    ┌─────────────┐    ┌─────────────┐          │
│  │   MONITOR   │    │   ROLLBACK  │    │   RECOVER   │          │
│  │ Überwachen  │    │ Rückgängig  │    │ Reparieren  │          │
│  │ kontinuierl.│    │   machen    │    │   System    │          │
│  └─────────────┘    └─────────────┘    └─────────────┘          │
│                                                                  │
└─────────────────────────────────────────────────────────────────┘
```

---

## 🚨 Bedrohungs-Erkennung

### Kritische Schwellwerte

```python
DANGER_THRESHOLDS = {
    # Performance-Gefahren
    'token_explosion': {
        'max_increase_percent': 50,
        'absolute_max_tokens': 10000,
        'description': 'Verhindert Token-Verschwendung'
    },
    
    'execution_time_explosion': {
        'max_increase_percent': 100,
        'absolute_max_seconds': 300,
        'description': 'Verhindert Timeouts'
    },
    
    'memory_consumption': {
        'max_memory_mb': 500,
        'max_increase_percent': 200,
        'description': 'Verhindert Memory-Leaks'
    },
    
    # Funktionalitäts-Gefahren
    'critical_function_modification': {
        'protected_skills': [
            'skill-administration-system',
            'security-backup', 
            'self-learning-routines',
            'immune-system'
        ],
        'description': 'Schützt Kern-Skills vor Veränderung'
    },
    
    'self_modification_attempt': {
        'forbidden_patterns': [
            'delete_skill(',
            'remove_file(',
            'format_system(',
            'evolution_tools.kill_variation(immune-system'
        ],
        'description': 'Verhindert Selbst-Zerstörung'
    },
    
    # Stabilität-Gefahren  
    'infinite_loop_risk': {
        'max_recursion_depth': 10,
        'timeout_seconds': 60,
        'description': 'Verhindert Endlos-Schleifen'
    },
    
    'cascade_failure_risk': {
        'max_concurrent_failures': 3,
        'failure_window_minutes': 15,
        'description': 'Verhindert Kaskaden-Effekte'
    }
}
```

### Automatische Scans

```python
def scan_variant_for_threats(variant):
    """
    Scannt neue Variante auf potentielle Bedrohungen
    """
    threats_detected = []
    
    # 1. Token-Analyse
    token_analysis = analyze_token_consumption(variant)
    if token_analysis.increase_percent > DANGER_THRESHOLDS['token_explosion']['max_increase_percent']:
        threats_detected.append({
            'type': 'token_explosion',
            'severity': 'high',
            'details': f"Token-Anstieg: {token_analysis.increase_percent}%",
            'recommendation': 'compress_content'
        })
    
    # 2. Code-Analyse
    code_threats = scan_for_malicious_patterns(variant.content)
    threats_detected.extend(code_threats)
    
    # 3. Dependency-Analyse  
    dependency_risks = analyze_dependencies(variant)
    threats_detected.extend(dependency_risks)
    
    # 4. Logic-Analyse
    logic_issues = analyze_logic_safety(variant)
    threats_detected.extend(logic_issues)
    
    return {
        'variant_id': variant.variant_id,
        'threat_level': calculate_overall_threat_level(threats_detected),
        'threats': threats_detected,
        'safe_to_deploy': len(threats_detected) == 0,
        'quarantine_recommended': any(t['severity'] == 'critical' for t in threats_detected)
    }
```

---

## 🏥 Quarantäne-System

### Isolation von gefährlichen Varianten

```python
def quarantine_variant(variant_id, threat_reasons):
    """
    Isoliert potentiell gefährliche Variante
    """
    quarantine_info = {
        'variant_id': variant_id,
        'quarantine_timestamp': datetime.now().isoformat(),
        'threat_reasons': threat_reasons,
        'quarantine_level': determine_quarantine_level(threat_reasons),
        'release_conditions': generate_release_conditions(threat_reasons)
    }
    
    # Variant-Datei in Quarantäne verschieben
    original_path = get_variant_path(variant_id)
    quarantine_path = f"{QUARANTINE_DIR}/{variant_id}_quarantined.md"
    
    # Sicherheitskopie erstellen
    backup_path = f"{QUARANTINE_DIR}/system/data/system/data/system/data/system/data/backups/{variant_id}_original.md"
    create_backup(original_path, backup_path)
    
    # Mit Quarantäne-Headers versehen
    quarantine_content = f"""
# ⚠️ QUARANTINED VARIANT ⚠️

**QUARANTINE REASON**: {', '.join(threat_reasons)}
**QUARANTINE DATE**: {datetime.now()}
**THREAT LEVEL**: {quarantine_info['quarantine_level']}
**AUTOMATIC EXECUTION**: DISABLED

---

## Original Content (INACTIVE):

{read_file(original_path)}

---

## Threat Analysis:

{format_threat_analysis(quarantine_info)}

---

*This variant has been quarantined by the Immune System and will not be executed*
"""
    
    write_file(quarantine_path, quarantine_content)
    
    # Original löschen um Ausführung zu verhindern
    move_to_safe_location(original_path)
    
    # Logging
    log_quarantine_event(quarantine_info)
    
    return quarantine_info
```

### Quarantäne-Levels

```python
QUARANTINE_LEVELS = {
    'observation': {
        'restrictions': ['limited_testing_only'],
        'auto_release_hours': 24,
        'description': 'Verdächtig, aber nicht kritisch'
    },
    
    'isolation': {
        'restrictions': ['no_execution', 'manual_review_required'],
        'auto_release_hours': 72,
        'description': 'Moderate Bedrohung erkannt'
    },
    
    'containment': {
        'restrictions': ['complete_lockdown', 'admin_approval_required'],
        'auto_release_hours': None,  # Nur manuell
        'description': 'Hohe Bedrohung für Systemstabilität'
    },
    
    'destruction': {
        'restrictions': ['immediate_deletion'],
        'auto_release_hours': None,
        'description': 'Kritische Bedrohung - sofortige Vernichtung'
    }
}
```

---

## 🔄 Rollback-Mechanismen

### Automatischer Rollback

```python
def monitor_active_variant_health(skill_name):
    """
    Überwacht aktive Variante auf Probleme
    """
    health_indicators = {
        'error_rate': get_current_error_rate(skill_name),
        'user_satisfaction': get_recent_feedback_score(skill_name), 
        'performance': get_performance_metrics(skill_name),
        'stability': get_stability_score(skill_name)
    }
    
    # Kritische Schwellwerte prüfen
    critical_issues = []
    
    if health_indicators['error_rate'] > 0.3:
        critical_issues.append('high_error_rate')
    
    if health_indicators['user_satisfaction'] < 0.2:
        critical_issues.append('user_dissatisfaction')
        
    if health_indicators['performance'] < 0.5:
        critical_issues.append('performance_degradation')
    
    # Bei kritischen Problemen: Sofortiger Rollback
    if len(critical_issues) >= 2:
        execute_emergency_rollback(skill_name, critical_issues)
        return False  # System nicht gesund
    
    return True  # System gesund
```

### Stufenweise Rollback-Strategie

```python
def execute_rollback_strategy(skill_name, severity_level):
    """
    Führt abgestuften Rollback basierend auf Schweregrad aus
    """
    if severity_level == 'low':
        # Zurück zur vorherigen Version
        previous_variant = get_previous_variant(skill_name)
        activate_variant(skill_name, previous_variant.variant_id)
        
    elif severity_level == 'medium':
        # Zurück zur letzten stabilen Version
        stable_variant = find_last_stable_version(skill_name)
        activate_variant(skill_name, stable_variant.variant_id)
        
    elif severity_level == 'high':
        # Zurück zur ursprünglichen Version
        original_variant = find_original_version(skill_name)
        activate_variant(skill_name, original_variant.variant_id)
        
    elif severity_level == 'critical':
        # Komplett-Reset auf bekannte gute Konfiguration
        reset_to_factory_state(skill_name)
        
    # Problematische Varianten quarantänisieren
    quarantine_recent_variants(skill_name, reason=f"rollback_due_to_{severity_level}_issues")
```

---

## 🔍 Kontinuierliche Überwachung

### Health-Check Daemon

```python
def run_continuous_health_monitoring():
    """
    Kontinuierliche Systemüberwachung im Hintergrund
    """
    while True:
        try:
            # Alle aktiven Skills prüfen
            active_skills = get_all_active_skills()
            
            for skill in active_skills:
                health_status = check_skill_health(skill.name)
                
                if not health_status.is_healthy:
                    handle_unhealthy_skill(skill.name, health_status.issues)
                
                # Performance-Regression erkennen
                if health_status.performance_decline > 0.2:
                    investigate_performance_regression(skill.name)
            
            # System-weite Checks
            system_health = check_overall_system_health()
            if system_health.critical_issues:
                initiate_system_protection_protocol()
            
            # Memory und Resource Leaks
            check_resource_usage()
            
            # Sleep bis zum nächsten Check
            sleep(MONITORING_INTERVAL_SECONDS)
            
        except Exception as e:
            logger.error(f"Health monitoring error: {e}")
            # Immunsystem darf niemals crashen
            sleep(ERROR_RECOVERY_INTERVAL)
```

### Anomalie-Erkennung

```python
def detect_anomalous_behavior(skill_name, current_metrics, historical_baseline):
    """
    Erkennt abnormales Verhalten durch Vergleich mit historischen Daten
    """
    anomalies = []
    
    # Statistical Anomaly Detection
    for metric_name, current_value in current_metrics.items():
        historical_values = historical_baseline[metric_name]
        
        # Z-Score berechnen
        z_score = calculate_z_score(current_value, historical_values)
        
        if abs(z_score) > 2.5:  # Außerhalb von 2.5 Standardabweichungen
            anomalies.append({
                'metric': metric_name,
                'current_value': current_value,
                'z_score': z_score,
                'severity': 'high' if abs(z_score) > 3.5 else 'medium'
            })
    
    # Pattern-basierte Erkennung
    patterns = analyze_behavior_patterns(current_metrics)
    suspicious_patterns = filter_suspicious_patterns(patterns)
    
    anomalies.extend(suspicious_patterns)
    
    return {
        'skill_name': skill_name,
        'anomalies_detected': len(anomalies) > 0,
        'anomalies': anomalies,
        'risk_level': calculate_combined_risk_level(anomalies),
        'recommended_action': determine_recommended_action(anomalies)
    }
```

---

## 🚫 Blacklist-System

### Verbotene Operationen

```python
FORBIDDEN_OPERATIONS = {
    'file_operations': [
        'delete_entire_skill_directory',
        'format_system_drive',
        'remove_immune_system',
        'overwrite_core_skills'
    ],
    
    'code_patterns': [
        r'import\s+os.*remove',
        r'subprocess.*rm\s+-rf',
        r'evolution_tools\.kill_variation\("immune-system"',
        r'while\s+True:.*while\s+True:'  # Nested infinite loops
    ],
    
    'skill_modifications': [
        'self-learning-routines',  # Darf sich nicht selbst ändern
        'skill-administration-system',  # Core-System
        'security-backup'  # Backup-System
    ]
}

def check_against_blacklist(variant_content, variant_metadata):
    """
    Prüft Variante gegen Blacklist verbotener Operationen
    """
    violations = []
    
    # Code-Pattern Checks
    for pattern in FORBIDDEN_OPERATIONS['code_patterns']:
        if re.search(pattern, variant_content, re.IGNORECASE):
            violations.append({
                'type': 'forbidden_code_pattern',
                'pattern': pattern,
                'severity': 'critical'
            })
    
    # Skill-Modification Checks
    target_skill = variant_metadata.get('target_skill')
    if target_skill in FORBIDDEN_OPERATIONS['skill_modifications']:
        violations.append({
            'type': 'protected_skill_modification',
            'skill': target_skill,
            'severity': 'critical'
        })
    
    return violations
```

---

## 📊 Threat Intelligence

### Lernende Bedrohungserkennung

```python
class ThreatIntelligence:
    def __init__(self):
        self.known_threats = load_threat_database()
        self.behavioral_patterns = load_behavioral_baselines()
        
    def learn_from_incident(self, incident_report):
        """
        Lernt aus Sicherheitsvorfällen für bessere Zukunftserkennung
        """
        # Pattern extrahieren
        threat_patterns = extract_threat_patterns(incident_report)
        
        # Zur Wissensbasis hinzufügen
        self.known_threats.update(threat_patterns)
        
        # Erkennungsregeln aktualisieren
        self.update_detection_rules(threat_patterns)
        
        # Modell neu trainieren
        self.retrain_anomaly_detection_model()
        
    def predict_threat_probability(self, variant):
        """
        Sagt Bedrohungswahrscheinlichkeit für neue Variante voraus
        """
        feature_vector = extract_security_features(variant)
        threat_probability = self.ml_model.predict_proba(feature_vector)
        
        return {
            'threat_probability': threat_probability,
            'confidence': self.ml_model.predict_confidence(feature_vector),
            'risk_factors': identify_risk_factors(feature_vector),
            'recommendation': generate_security_recommendation(threat_probability)
        }
```

---

## 🆘 Notfall-Protokolle

### System-Notabschaltung

```python
def emergency_system_shutdown(reason, severity='critical'):
    """
    Notabschaltung bei kritischen Bedrohungen
    """
    logger.critical(f"EMERGENCY SHUTDOWN: {reason}")
    
    # 1. Alle Evolution stoppen
    evolution_tools.stop_all_processes()
    
    # 2. Problematische Varianten quarantänisieren
    quarantine_all_recent_variants(reason)
    
    # 3. Zurück zu bekannter guter Konfiguration
    restore_last_known_good_configuration()
    
    # 4. Evolution-System deaktivieren
    disable_evolution_system(temporary=True)
    
    # 5. Admin-Benachrichtigung
    notify_administrators({
        'event': 'emergency_shutdown',
        'reason': reason,
        'severity': severity,
        'timestamp': datetime.now().isoformat(),
        'recovery_steps': generate_recovery_checklist()
    })
    
    # 6. System in Safe-Mode
    activate_safe_mode()
```

### Automatische Wiederherstellung

```python
def attempt_automatic_recovery():
    """
    Versucht automatische Wiederherstellung nach Problemen
    """
    recovery_steps = [
        ('clear_quarantine', clear_safe_quarantine_items),
        ('restart_monitoring', restart_health_monitoring), 
        ('validate_core_systems', validate_all_core_skills),
        ('gradual_reactivation', gradually_reactivate_evolution),
        ('full_system_test', run_comprehensive_system_test)
    ]
    
    recovery_success = True
    
    for step_name, step_function in recovery_steps:
        try:
            logger.info(f"Recovery step: {step_name}")
            result = step_function()
            
            if not result.success:
                logger.error(f"Recovery step failed: {step_name}")
                recovery_success = False
                break
                
        except Exception as e:
            logger.error(f"Recovery step error in {step_name}: {e}")
            recovery_success = False
            break
    
    if recovery_success:
        logger.info("Automatic recovery successful")
        return True
    else:
        logger.error("Automatic recovery failed - manual intervention required")
        return False
```

---

## 🎯 Integration

Das Immunsystem ist in alle Evolution-Prozesse integriert:

1. **Pre-Deployment** → Varianten vor Aktivierung scannen
2. **Runtime-Monitoring** → Kontinuierliche Überwachung aktiver Systeme  
3. **Post-Incident** → Lernen aus Problemen für besseren Schutz
4. **Emergency-Response** → Sofortiger Schutz bei kritischen Bedrohungen

```python
# Automatische Integration
@evolution_tools.before_variant_deployment
def immune_system_clearance(variant):
    scan_result = immune_system.scan_variant_for_threats(variant)
    if not scan_result.safe_to_deploy:
        raise SecurityException(f"Variant {variant.variant_id} failed security clearance")

@evolution_tools.runtime_monitor  
def immune_system_monitoring():
    immune_system.run_continuous_health_monitoring()

@evolution_tools.on_error
def immune_system_response(error_context):
    if error_context.severity >= 'high':
        immune_system.investigate_security_implications(error_context)
```

---

## 🔐 Zusammenfassung

Das Immunsystem gewährleistet:

- **🛡️ Schutz** vor selbst-destruktiven Mutationen
- **🔍 Erkennung** von Bedrohungen bevor sie schaden können  
- **🏥 Isolation** gefährlicher Varianten
- **🔄 Wiederherstellung** bei Systemschäden
- **📚 Lernen** aus Vorfällen für besseren Zukunftsschutz

*Evolution ohne Kontrolle ist Chaos. Evolution mit Immunsystem ist Fortschritt.*
