# WIA-SEC-018: Vulnerability Assessment
## Phases 2, 3, and 4 - Advanced Implementation

**Standard ID:** WIA-SEC-018
**Category:** Security (SEC)
**Version:** 1.0.0
**Status:** Active
**Last Updated:** 2025-12-25

---

## Phase 2: Advanced Vulnerability Detection

### 2.1 Machine Learning-Based Vulnerability Detection

#### AI-Powered Anomaly Detection

```python
class MLVulnerabilityDetector:
    """
    Machine learning-based vulnerability detection system
    using anomaly detection and pattern recognition
    """

    def __init__(self):
        self.model = self.load_pretrained_model()
        self.feature_extractor = FeatureExtractor()

    def analyze_code_patterns(self, code_sample):
        """
        Analyze code for potential vulnerabilities using ML
        """
        features = self.feature_extractor.extract(code_sample)

        predictions = self.model.predict(features)

        return {
            'vulnerabilities': self.interpret_predictions(predictions),
            'confidence': predictions.confidence_scores,
            'patterns': self.identify_patterns(features),
            'recommendations': self.generate_recommendations(predictions)
        }

    def detect_zero_day_candidates(self, execution_traces):
        """
        Identify potential zero-day vulnerabilities through
        behavioral analysis
        """
        anomalies = []

        for trace in execution_traces:
            anomaly_score = self.calculate_anomaly_score(trace)

            if anomaly_score > self.threshold:
                anomalies.append({
                    'trace': trace,
                    'score': anomaly_score,
                    'indicators': self.extract_indicators(trace),
                    'severity_estimate': self.estimate_severity(trace)
                })

        return sorted(anomalies, key=lambda x: x['score'], reverse=True)

    def continuous_learning(self, new_vulnerabilities):
        """
        Update model with newly discovered vulnerabilities
        """
        features = self.extract_features_batch(new_vulnerabilities)
        self.model.incremental_fit(features)
        self.save_model_checkpoint()
```

#### Behavioral Analysis Engine

```javascript
class BehavioralAnalysisEngine {
  constructor() {
    this.baselineProfiles = new Map();
    this.anomalyDetector = new AnomalyDetector();
  }

  async analyzeApplicationBehavior(appId, runtime Data) {
    // Establish baseline behavior
    const baseline = await this.getOrCreateBaseline(appId);

    // Compare current behavior against baseline
    const deviations = this.detectDeviations(runtimeData, baseline);

    // Classify deviations as potential vulnerabilities
    const vulnerabilities = deviations
      .filter(d => d.severity > this.threshold)
      .map(d => this.classifyDeviation(d));

    return {
      baselineCompliance: this.calculateComplianceScore(deviations),
      suspiciousBehaviors: vulnerabilities,
      recommendations: this.generateRecommendations(vulnerabilities)
    };
  }

  detectDeviations(current, baseline) {
    return {
      memoryUsage: this.compareMetric(current.memory, baseline.memory),
      networkPatterns: this.compareNetworkBehavior(current.network, baseline.network),
      fileSystemAccess: this.compareFileAccess(current.fs, baseline.fs),
      privilegeEscalation: this.detectPrivilegeChanges(current, baseline),
      dataExfiltration: this.detectExfiltrationPatterns(current.network)
    };
  }
}
```

### 2.2 Advanced Scanning Techniques

#### Interactive Application Security Testing (IAST)

```yaml
iast_configuration:
  name: "Runtime Instrumentation Analysis"
  agents:
    - contrast-security
    - hdiv
    - seeker

  instrumentation:
    frameworks:
      - spring-boot
      - express
      - django
      - rails

    monitoring_points:
      - http_requests
      - database_queries
      - file_operations
      - authentication_events
      - authorization_checks

  vulnerability_detection:
    sql_injection:
      enabled: true
      confidence_threshold: 0.9
    xss:
      enabled: true
      context_aware: true
    command_injection:
      enabled: true
      shell_analysis: true
    path_traversal:
      enabled: true
      canonicalization: true

  reporting:
    realtime_alerts: true
    detailed_traces: true
    remediation_guidance: true
```

#### Container and Kubernetes Security Scanning

```yaml
container_security:
  name: "Container Vulnerability Assessment"
  scanners:
    - trivy
    - clair
    - anchore

  scan_targets:
    images:
      - base_images
      - application_images
      - runtime_containers

    registries:
      - docker_hub
      - gcr_io
      - ecr
      - private_registry

  vulnerability_checks:
    os_packages: true
    application_dependencies: true
    configuration_issues: true
    secrets_scanning: true
    malware_detection: true

  kubernetes:
    api_server_audit: true
    rbac_analysis: true
    network_policies: true
    pod_security_policies: true
    admission_controllers: true

  remediation:
    auto_rebuild: true
    base_image_updates: true
    dependency_patching: true
```

### 2.3 Exploit Prediction and Threat Intelligence

#### Exploit Prediction System

```python
class ExploitPredictionSystem:
    """
    Predict likelihood of exploit development for discovered vulnerabilities
    """

    def predict_exploit_likelihood(self, vulnerability):
        features = {
            'cvss_score': vulnerability.cvss.base_score,
            'attack_complexity': self.encode_complexity(vulnerability.cvss.attack_complexity),
            'privileges_required': self.encode_privileges(vulnerability.cvss.privileges_required),
            'public_disclosure': vulnerability.metadata.publication_date is not None,
            'vendor_response': self.analyze_vendor_response(vulnerability),
            'affected_product_popularity': self.get_product_popularity(vulnerability.affected_assets),
            'similar_exploits_exist': self.check_similar_exploits(vulnerability.cwe_id),
            'attacker_interest': self.measure_attacker_interest(vulnerability)
        }

        probability = self.ml_model.predict_proba([features])[0][1]

        return {
            'exploit_probability': probability,
            'estimated_time_to_exploit': self.estimate_tte(probability, features),
            'predicted_exploit_maturity': self.predict_maturity(probability),
            'recommended_priority_boost': self.calculate_priority_boost(probability)
        }

    def integrate_threat_intelligence(self, vulnerability):
        """
        Enrich vulnerability with threat intelligence
        """
        threat_intel = {
            'exploit_kits': self.check_exploit_kits(vulnerability.cve_id),
            'dark_web_mentions': self.scan_dark_web(vulnerability),
            'attacker_discussions': self.monitor_underground_forums(vulnerability),
            'active_campaigns': self.correlate_with_campaigns(vulnerability),
            'attribution': self.identify_threat_actors(vulnerability)
        }

        return threat_intel
```

---

## Phase 3: Enterprise-Scale Vulnerability Management

### 3.1 Multi-Cloud Vulnerability Assessment

#### Cloud Security Posture Management (CSPM)

```javascript
class MultiCloudVulnerabilityManager {
  constructor() {
    this.providers = {
      aws: new AWSVulnerabilityScanner(),
      azure: new AzureVulnerabilityScanner(),
      gcp: new GCPVulnerabilityScanner()
    };
  }

  async assessCloudInfrastructure() {
    const assessments = await Promise.all([
      this.assessAWS(),
      this.assessAzure(),
      this.assessGCP()
    ]);

    return this.consolidateFindings(assessments);
  }

  async assessAWS() {
    return {
      // EC2 instance vulnerabilities
      compute: await this.providers.aws.scanEC2Instances(),

      // S3 bucket misconfigurations
      storage: await this.providers.aws.scanS3Security(),

      // IAM policy issues
      identity: await this.providers.aws.scanIAMPolicies(),

      // Security group misconfigurations
      network: await this.providers.aws.scanSecurityGroups(),

      // Lambda function vulnerabilities
      serverless: await this.providers.aws.scanLambdaFunctions(),

      // RDS database security
      databases: await this.providers.aws.scanRDSSecurity(),

      // EKS cluster security
      kubernetes: await this.providers.aws.scanEKSClusters()
    };
  }

  consolidateFindings(assessments) {
    const allVulnerabilities = assessments.flatMap(a => a.vulnerabilities);

    return {
      summary: this.generateSummary(allVulnerabilities),
      byProvider: this.groupByProvider(allVulnerabilities),
      byService: this.groupByService(allVulnerabilities),
      crossCloudRisks: this.identifyCrossCloudRisks(allVulnerabilities),
      recommendations: this.generateCloudRecommendations(allVulnerabilities)
    };
  }
}
```

### 3.2 Supply Chain Security

#### Software Bill of Materials (SBOM) Analysis

```typescript
interface SBOM {
  bomFormat: 'CycloneDX' | 'SPDX';
  version: string;
  components: Component[];
  dependencies: Dependency[];
  vulnerabilities: VulnerabilityReference[];
}

class SupplyChainSecurityAnalyzer {
  async analyzeSBOM(sbom: SBOM): Promise<SupplyChainAnalysis> {
    // Analyze all components in SBOM
    const componentAnalysis = await Promise.all(
      sbom.components.map(c => this.analyzeComponent(c))
    );

    // Map dependencies and identify transitive vulnerabilities
    const dependencyTree = this.buildDependencyTree(sbom);
    const transitiveVulns = this.findTransitiveVulnerabilities(dependencyTree);

    // Check for known malicious packages
    const malwareCheck = await this.scanForMalware(sbom.components);

    // Analyze license compliance risks
    const licenseRisks = this.analyzeLicenseCompliance(sbom);

    // Check for outdated dependencies
    const outdatedDeps = this.identifyOutdatedDependencies(sbom);

    return {
      totalComponents: sbom.components.length,
      vulnerableComponents: componentAnalysis.filter(c => c.vulnerabilities.length > 0),
      transitiveVulnerabilities: transitiveVulns,
      malwareDetected: malwareCheck.threats,
      licenseRisks: licenseRisks,
      outdatedDependencies: outdatedDeps,
      riskScore: this.calculateSupplyChainRisk({
        componentAnalysis,
        transitiveVulns,
        malwareCheck,
        licenseRisks
      }),
      recommendations: this.generateSupplyChainRecommendations()
    };
  }

  async analyzeComponent(component: Component): Promise<ComponentAnalysis> {
    // Check component against multiple vulnerability databases
    const vulnerabilities = await Promise.all([
      this.checkNVD(component),
      this.checkGitHubAdvisories(component),
      this.checkOSSIndex(component),
      this.checkSnykDB(component)
    ]);

    // Check component integrity
    const integrityCheck = await this.verifyComponentIntegrity(component);

    // Analyze component maintainer reputation
    const reputationScore = await this.analyzeMainta inerReputation(component);

    return {
      component: component,
      vulnerabilities: vulnerabilities.flat(),
      integrityVerified: integrityCheck.verified,
      maintainerReputation: reputationScore,
      lastUpdate: component.version.timestamp,
      recommendedAction: this.determineAction(vulnerabilities, integrityCheck)
    };
  }
}
```

### 3.3 Vulnerability Remediation Automation

#### Automated Patch Management

```python
class AutomatedRemediationEngine:
    """
    Automated vulnerability remediation with safety controls
    """

    def __init__(self):
        self.patch_manager = PatchManager()
        self.testing_framework = AutomatedTesting()
        self.rollback_manager = RollbackManager()

    async def remediate_vulnerability(self, vulnerability):
        """
        Automatically remediate vulnerability with testing and rollback
        """
        # Step 1: Identify remediation strategy
        strategy = self.select_remediation_strategy(vulnerability)

        # Step 2: Create remediation plan
        plan = self.create_remediation_plan(vulnerability, strategy)

        # Step 3: Execute in staging environment first
        staging_result = await self.execute_in_staging(plan)

        if not staging_result.success:
            return self.escalate_to_manual(vulnerability, staging_result)

        # Step 4: Run automated tests
        test_results = await self.testing_framework.run_security_tests(
            vulnerability,
            staging_result.environment
        )

        if not test_results.all_passed:
            return self.escalate_to_manual(vulnerability, test_results)

        # Step 5: Create production rollout plan
        rollout_plan = self.create_rollout_plan(plan, test_results)

        # Step 6: Execute gradual rollout with monitoring
        production_result = await self.gradual_rollout(
            rollout_plan,
            monitoring_enabled=True
        )

        # Step 7: Verify remediation
        verification = await self.verify_remediation(
            vulnerability,
            production_result
        )

        return {
            'vulnerability_id': vulnerability.id,
            'remediation_strategy': strategy,
            'staging_result': staging_result,
            'test_results': test_results,
            'production_result': production_result,
            'verification': verification,
            'rollback_available': True,
            'rollback_procedure': self.rollback_manager.get_procedure(plan)
        }

    def select_remediation_strategy(self, vulnerability):
        """
        Select optimal remediation strategy based on vulnerability type
        """
        strategies = {
            'dependency_update': self.can_auto_update_dependency(vulnerability),
            'configuration_fix': self.can_auto_fix_config(vulnerability),
            'code_patch': self.can_auto_patch_code(vulnerability),
            'waf_rule': self.can_deploy_waf_rule(vulnerability),
            'manual_required': False
        }

        # Select highest confidence strategy
        available_strategies = {k: v for k, v in strategies.items()
                                if v and k != 'manual_required'}

        if not available_strategies:
            strategies['manual_required'] = True
            return 'manual'

        return max(available_strategies.keys(),
                   key=lambda k: self.get_strategy_confidence(k, vulnerability))

    async def gradual_rollout(self, plan, monitoring_enabled=True):
        """
        Gradually roll out remediation with canary deployment
        """
        stages = [
            {'name': 'canary', 'percentage': 5, 'duration': '1h'},
            {'name': 'beta', 'percentage': 25, 'duration': '4h'},
            {'name': 'production', 'percentage': 100, 'duration': '24h'}
        ]

        for stage in stages:
            # Deploy to percentage of fleet
            deployment = await self.deploy_to_percentage(
                plan,
                stage['percentage']
            )

            # Monitor for issues
            if monitoring_enabled:
                monitoring_result = await self.monitor_deployment(
                    deployment,
                    duration=stage['duration']
                )

                if monitoring_result.has_issues:
                    # Automatic rollback on issues
                    await self.rollback_manager.rollback(deployment)
                    return {
                        'success': False,
                        'stage_failed': stage['name'],
                        'issues': monitoring_result.issues,
                        'rollback_completed': True
                    }

        return {
            'success': True,
            'fully_deployed': True,
            'monitoring_results': 'all_clear'
        }
```

---

## Phase 4: Continuous Vulnerability Intelligence

### 4.1 Real-time Threat Intelligence Integration

#### Threat Intelligence Platform Integration

```typescript
class ThreatIntelligencePlatform {
  private feeds: ThreatFeed[];
  private enrichmentServices: EnrichmentService[];

  async enrichVulnerability(vulnerability: Vulnerability): Promise<EnrichedVulnerability> {
    const enrichments = await Promise.all([
      this.getExploitIntelligence(vulnerability),
      this.getAttackPatterns(vulnerability),
      this.getThreatActorActivity(vulnerability),
      this.getIncidentReports(vulnerability),
      this.getIoCsRelated(vulnerability)
    ]);

    return {
      ...vulnerability,
      threatIntelligence: {
        exploitAvailability: enrichments[0],
        knownAttackPatterns: enrichments[1],
        threatActorInterest: enrichments[2],
        relatedIncidents: enrichments[3],
        indicatorsOfCompromise: enrichments[4],
        riskScore: this.calculateThreatScore(enrichments),
        recommendations: this.generateThreatBasedRecommendations(enrichments)
      }
    };
  }

  async monitorDarkWeb(vulnerability: Vulnerability): Promise<DarkWebIntelligence> {
    // Monitor dark web forums and marketplaces for vulnerability mentions
    const mentions = await this.darkWebScanner.search({
      cveId: vulnerability.cveId,
      keywords: [vulnerability.title, ...vulnerability.keywords],
      timeRange: '30d'
    });

    return {
      totalMentions: mentions.length,
      exploitListings: mentions.filter(m => m.type === 'exploit_sale'),
      discussions: mentions.filter(m => m.type === 'discussion'),
      tradingActivity: this.analyzeTradingActivity(mentions),
      priceRange: this.extractPriceRange(mentions),
      threatLevel: this.assessThreatLevel(mentions)
    };
  }

  async correlatWithIncidents(vulnerability: Vulnerability): Promise<IncidentCorrelation[]> {
    // Correlate vulnerability with known security incidents
    const incidents = await this.incidentDatabase.search({
      cveId: vulnerability.cveId,
      timeRange: 'all'
    });

    return incidents.map(incident => ({
      incidentId: incident.id,
      organization: incident.organization,
      impact: incident.impact,
      attackVector: incident.attackVector,
      timeline: incident.timeline,
      lessonsLearned: incident.lessonsLearned,
      similarities: this.calculateSimilarity(vulnerability, incident)
    }));
  }
}
```

### 4.2 Vulnerability Lifecycle Management

#### Complete Vulnerability Lifecycle

```javascript
class VulnerabilityLifecycleManager {
  constructor() {
    this.states = [
      'DISCOVERED',
      'VALIDATED',
      'ANALYZED',
      'PRIORITIZED',
      'ASSIGNED',
      'IN_REMEDIATION',
      'FIXED',
      'VERIFIED',
      'CLOSED',
      'REOPENED',
      'ACCEPTED_RISK',
      'FALSE_POSITIVE'
    ];

    this.workflows = new WorkflowEngine();
    this.notifications = new NotificationService();
    this.sla = new SLAManager();
  }

  async transitionState(vulnerabilityId, newState, metadata) {
    const vulnerability = await this.getVulnerability(vulnerabilityId);

    // Validate state transition
    if (!this.isValidTransition(vulnerability.state, newState)) {
      throw new Error(`Invalid state transition: ${vulnerability.state} -> ${newState}`);
    }

    // Execute pre-transition hooks
    await this.executePreTransitionHooks(vulnerability, newState);

    // Update vulnerability state
    vulnerability.state = newState;
    vulnerability.stateHistory.push({
      from: vulnerability.state,
      to: newState,
      timestamp: new Date(),
      metadata: metadata
    });

    // Execute post-transition actions
    await this.executePostTransitionActions(vulnerability, newState);

    // Update SLA tracking
    await this.sla.updateTracking(vulnerability);

    // Send notifications
    await this.notifications.notifyStateChange(vulnerability, newState);

    return vulnerability;
  }

  async executePostTransitionActions(vulnerability, newState) {
    const actions = {
      'DISCOVERED': [
        () => this.createInitialAssessment(vulnerability),
        () => this.checkCVEDatabases(vulnerability)
      ],
      'VALIDATED': [
        () => this.calculateCVSS(vulnerability),
        () => this.assessRisk(vulnerability),
        () => this.checkExploitAvailability(vulnerability)
      ],
      'PRIORITIZED': [
        () => this.assignOwner(vulnerability),
        () => this.createRemediationTicket(vulnerability),
        () => this.setSLA(vulnerability)
      ],
      'FIXED': [
        () => this.scheduleVerification(vulnerability),
        () => this.notifySecurityTeam(vulnerability)
      ],
      'VERIFIED': [
        () => this.updateMetrics(vulnerability),
        () => this.generateReport(vulnerability),
        () => this.closeVulnerability(vulnerability)
      ]
    };

    const stateActions = actions[newState] || [];
    await Promise.all(stateActions.map(action => action()));
  }

  async trackSLA(vulnerability) {
    const slaConfig = this.getSLAConfig(vulnerability.priority);
    const timeline = {
      discovered: vulnerability.discoveryDate,
      responseDeadline: this.calculateDeadline(
        vulnerability.discoveryDate,
        slaConfig.responseTime
      ),
      remediationDeadline: this.calculateDeadline(
        vulnerability.discoveryDate,
        slaConfig.remediationTime
      ),
      verificationDeadline: this.calculateDeadline(
        vulnerability.fixedDate,
        slaConfig.verificationTime
      )
    };

    // Check SLA violations
    const now = new Date();
    const violations = [];

    if (vulnerability.state === 'DISCOVERED' &&
        now > timeline.responseDeadline) {
      violations.push('RESPONSE_SLA_VIOLATED');
    }

    if (!['FIXED', 'VERIFIED', 'CLOSED'].includes(vulnerability.state) &&
        now > timeline.remediationDeadline) {
      violations.push('REMEDIATION_SLA_VIOLATED');
    }

    if (violations.length > 0) {
      await this.escalate(vulnerability, violations);
    }

    return {
      timeline,
      violations,
      compliance: violations.length === 0
    };
  }
}
```

### 4.3 Advanced Reporting and Analytics

#### Executive Dashboard

```python
class VulnerabilityAnalyticsDashboard:
    """
    Advanced analytics and reporting for vulnerability management
    """

    def generate_executive_summary(self, time_period='30d'):
        """
        Generate executive-level vulnerability summary
        """
        vulnerabilities = self.get_vulnerabilities(time_period)

        return {
            'overview': {
                'total_vulnerabilities': len(vulnerabilities),
                'critical': len([v for v in vulnerabilities if v.severity == 'CRITICAL']),
                'high': len([v for v in vulnerabilities if v.severity == 'HIGH']),
                'medium': len([v for v in vulnerabilities if v.severity == 'MEDIUM']),
                'low': len([v for v in vulnerabilities if v.severity == 'LOW']),
                'remediated': len([v for v in vulnerabilities if v.state == 'CLOSED']),
                'open': len([v for v in vulnerabilities if v.state not in ['CLOSED', 'FALSE_POSITIVE']])
            },
            'trends': {
                'discovery_rate': self.calculate_discovery_rate(vulnerabilities),
                'remediation_rate': self.calculate_remediation_rate(vulnerabilities),
                'mean_time_to_remediate': self.calculate_mttr(vulnerabilities),
                'sla_compliance': self.calculate_sla_compliance(vulnerabilities)
            },
            'risk_metrics': {
                'overall_risk_score': self.calculate_overall_risk(vulnerabilities),
                'high_risk_assets': self.identify_high_risk_assets(vulnerabilities),
                'emerging_threats': self.identify_emerging_threats(vulnerabilities),
                'attack_surface': self.calculate_attack_surface(vulnerabilities)
            },
            'compliance': {
                'iso27001_compliance': self.check_iso27001_compliance(),
                'soc2_compliance': self.check_soc2_compliance(),
                'findings': self.get_compliance_findings()
            },
            'recommendations': self.generate_executive_recommendations(vulnerabilities)
        }

    def calculate_vulnerability_metrics(self):
        """
        Calculate comprehensive vulnerability metrics
        """
        return {
            'mttr_by_severity': {
                'CRITICAL': self.calculate_mttr_by_severity('CRITICAL'),
                'HIGH': self.calculate_mttr_by_severity('HIGH'),
                'MEDIUM': self.calculate_mttr_by_severity('MEDIUM'),
                'LOW': self.calculate_mttr_by_severity('LOW')
            },
            'vulnerability_density': {
                'per_1000_loc': self.calculate_vuln_density_per_loc(),
                'per_asset': self.calculate_vuln_density_per_asset(),
                'per_team': self.calculate_vuln_density_per_team()
            },
            'remediation_effectiveness': {
                'first_time_fix_rate': self.calculate_first_time_fix_rate(),
                'reopen_rate': self.calculate_reopen_rate(),
                'false_positive_rate': self.calculate_false_positive_rate()
            },
            'security_posture': {
                'score': self.calculate_security_posture_score(),
                'trend': self.calculate_security_trend(),
                'peer_comparison': self.compare_with_peers()
            }
        }

    def generate_heat_map(self, vulnerabilities):
        """
        Generate vulnerability heat map by asset and severity
        """
        heat_map = {}

        for vuln in vulnerabilities:
            for asset in vuln.affected_assets:
                if asset.id not in heat_map:
                    heat_map[asset.id] = {
                        'asset_name': asset.name,
                        'CRITICAL': 0,
                        'HIGH': 0,
                        'MEDIUM': 0,
                        'LOW': 0
                    }

                heat_map[asset.id][vuln.severity] += 1

        # Calculate risk scores for each asset
        for asset_id, counts in heat_map.items():
            heat_map[asset_id]['risk_score'] = (
                counts['CRITICAL'] * 10 +
                counts['HIGH'] * 7 +
                counts['MEDIUM'] * 4 +
                counts['LOW'] * 1
            )

        return sorted(
            heat_map.values(),
            key=lambda x: x['risk_score'],
            reverse=True
        )
```

### 4.4 Integration with Security Ecosystem

#### SIEM Integration

```typescript
class SIEMIntegration {
  async sendToSplunk(vulnerability: Vulnerability): Promise<void> {
    const event = {
      sourcetype: 'wia:vulnerability',
      event: {
        vulnerability_id: vulnerability.id,
        cve_id: vulnerability.cveId,
        severity: vulnerability.severity,
        cvss_score: vulnerability.cvss.baseScore,
        affected_assets: vulnerability.affectedAssets.map(a => a.id),
        state: vulnerability.state,
        discovery_date: vulnerability.discoveryDate,
        remediation_deadline: vulnerability.remediationDeadline,
        risk_score: vulnerability.riskScore
      }
    };

    await this.splunkClient.sendEvent(event);
  }

  async sendToQRadar(vulnerability: Vulnerability): Promise<void> {
    const offense = {
      offense_type: 'Vulnerability',
      description: `${vulnerability.severity} vulnerability: ${vulnerability.title}`,
      severity: this.mapSeverityToQRadar(vulnerability.severity),
      credibility: this.calculateCredibility(vulnerability),
      relevance: this.calculateRelevance(vulnerability),
      categories: [vulnerability.category],
      source_address_ids: vulnerability.affectedAssets.map(a => a.ipAddress)
    };

    await this.qradarClient.createOffense(offense);
  }
}
```

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**Document Version:** 1.0.0
**Last Updated:** 2025-12-25
**Next Review:** 2026-03-25

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弘益人間 (홍익인간) - Benefit All Humanity
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