Incident Response¶

Comprehensive incident response procedures for Anya Enterprise security events.

Overview¶

This document outlines the incident response process for security events in Anya Enterprise environments, including detection, containment, investigation, and recovery procedures.

Incident Classification¶

Severity Levels¶

Critical (P0)¶

Data breach with customer data exposed
System compromise affecting multiple customers
Ransomware or destructive attacks
Complete service outage
Response Time: 15 minutes
Escalation: CEO, CTO, Security Team Lead

High (P1)¶

Unauthorized access to sensitive systems
Malware detected on production systems
DDoS attacks affecting service availability
Security control failures
Response Time: 1 hour
Escalation: CTO, Security Team Lead, Engineering Manager

Medium (P2)¶

Suspicious activity detected
Minor security control failures
Failed security scans
Policy violations
Response Time: 4 hours
Escalation: Security Team, On-call Engineer

Low (P3)¶

Security awareness violations
Minor configuration issues
Documentation updates needed
Response Time: 24 hours
Escalation: Security Team

Response Process¶

Phase 1: Detection and Analysis¶

Detection Methods¶

interface SecurityAlert {
  id: string;
  timestamp: Date;
  severity: 'critical' | 'high' | 'medium' | 'low';
  source: string;
  event_type: string;
  description: string;
  affected_systems: string[];
  initial_indicators: string[];
}

class IncidentDetector {
  async analyzeSecurityEvent(event: SecurityEvent): Promise<SecurityAlert | null> {
    // Correlation with existing incidents
    const relatedIncidents = await this.findRelatedIncidents(event);

    // Pattern analysis
    const patterns = await this.analyzePatterns(event);

    // Threat intelligence lookup
    const threatIntel = await this.checkThreatIntelligence(event);

    if (this.isSecurityIncident(event, patterns, threatIntel)) {
      return this.createAlert(event, relatedIncidents);
    }

    return null;
  }
}

Initial Assessment¶

Verify the incident
Confirm the alert is legitimate
Eliminate false positives
Document initial findings
Assess scope and impact
Identify affected systems and data
Estimate business impact
Determine if incident is ongoing
Classify incident
Assign severity level
Categorize incident type
Estimate response resources needed

Phase 2: Containment¶

Short-term Containment¶

#!/bin/bash
# Emergency containment script

# Isolate affected systems
isolate_system() {
    local system_id=$1
    echo "Isolating system: $system_id"

    # Block network access
    iptables -A INPUT -s $system_id -j DROP
    iptables -A OUTPUT -d $system_id -j DROP

    # Disable user accounts if compromised
    disable_user_accounts $system_id

    # Snapshot system state for forensics
    create_forensic_snapshot $system_id
}

# Preserve evidence
preserve_evidence() {
    local incident_id=$1
    local evidence_dir="/var/incident-response/$incident_id"

    mkdir -p $evidence_dir

    # System logs
    cp /var/log/syslog $evidence_dir/
    cp /var/log/auth.log $evidence_dir/

    # Application logs
    cp /var/log/anya-enterprise/*.log $evidence_dir/

    # Network capture
    tcpdump -w $evidence_dir/network-capture.pcap &

    # Memory dump
    dd if=/dev/mem of=$evidence_dir/memory-dump.img
}

Long-term Containment¶

Apply security patches
Update firewall rules
Implement additional monitoring
Deploy additional security controls

Phase 3: Eradication¶

Remove Threats¶

import os
import subprocess
from typing import List

class ThreatEradicator:
    def __init__(self, incident_id: str):
        self.incident_id = incident_id
        self.cleanup_log = f"/var/log/cleanup-{incident_id}.log"

    def remove_malware(self, infected_files: List[str]) -> bool:
        """Remove identified malware files"""
        try:
            for file_path in infected_files:
                if os.path.exists(file_path):
                    # Backup before removal
                    backup_path = f"/var/incident-response/{self.incident_id}/malware-backup/"
                    os.makedirs(backup_path, exist_ok=True)
                    subprocess.run(['cp', file_path, backup_path])

                    # Remove malware
                    os.remove(file_path)
                    self.log_action(f"Removed malware: {file_path}")

            return True
        except Exception as e:
            self.log_action(f"Error removing malware: {str(e)}")
            return False

    def close_vulnerabilities(self, vulnerabilities: List[dict]) -> bool:
        """Close identified vulnerabilities"""
        for vuln in vulnerabilities:
            if vuln['type'] == 'weak_password':
                self.force_password_reset(vuln['users'])
            elif vuln['type'] == 'unpatched_system':
                self.apply_security_patches(vuln['systems'])
            elif vuln['type'] == 'misconfiguration':
                self.fix_configuration(vuln['config_files'])

        return True

    def log_action(self, message: str):
        with open(self.cleanup_log, 'a') as f:
            f.write(f"{datetime.now()}: {message}\n")

Phase 4: Recovery¶

System Restoration¶

Verify system integrity
Run integrity checks
Validate security controls
Test critical functions
Gradual restoration
Start with non-critical systems
Monitor for recurring issues
Progressively restore services
Enhanced monitoring
Deploy additional monitoring
Implement new detection rules
Increase logging verbosity

Recovery Checklist¶

[ ] All threats removed and vulnerabilities closed
[ ] Systems restored from clean backups
[ ] Security controls tested and verified
[ ] Enhanced monitoring deployed
[ ] User access validated
[ ] Business operations restored
[ ] Stakeholders notified of resolution

Phase 5: Lessons Learned¶

Post-Incident Review¶

interface PostIncidentReport {
  incident_id: string;
  summary: string;
  timeline: IncidentEvent[];
  root_cause: string;
  impact_assessment: {
    financial: number;
    reputation: string;
    operational: string;
    regulatory: string;
  };
  response_effectiveness: {
    detection_time: number;
    response_time: number;
    containment_time: number;
    recovery_time: number;
  };
  recommendations: Recommendation[];
  action_items: ActionItem[];
}

class PostIncidentAnalysis {
  async generateReport(incident_id: string): Promise<PostIncidentReport> {
    const incident = await this.getIncidentDetails(incident_id);
    const timeline = await this.buildTimeline(incident_id);
    const rootCause = await this.analyzeRootCause(incident);

    return {
      incident_id,
      summary: this.generateSummary(incident),
      timeline,
      root_cause: rootCause,
      impact_assessment: await this.assessImpact(incident),
      response_effectiveness: this.evaluateResponse(timeline),
      recommendations: await this.generateRecommendations(rootCause),
      action_items: await this.createActionItems(incident)
    };
  }
}

Communication Plan¶

Internal Communications¶

Incident Response Team¶

Security Team Lead: Overall incident coordination
IT Operations: System administration and recovery
Engineering: Application-specific expertise
Legal: Regulatory compliance and legal implications
PR/Communications: External communications
Executive: Strategic decisions and resource allocation

Communication Channels¶

Primary: Secure incident response chat room
Secondary: Encrypted email threads
Emergency: Direct phone calls
Documentation: Incident tracking system

External Communications¶

Customer Notifications¶

interface CustomerNotification {
  incident_id: string;
  notification_type: 'security_advisory' | 'data_breach' | 'service_disruption';
  affected_customers: string[];
  message: string;
  remediation_steps: string[];
  timeline: string;
  contact_info: string;
}

class CustomerCommunications {
  async notifyCustomers(incident: SecurityIncident): Promise<void> {
    if (this.requiresCustomerNotification(incident)) {
      const notification = this.createNotification(incident);

      // Send notifications based on severity
      if (incident.severity === 'critical') {
        await this.sendUrgentNotification(notification);
      } else {
        await this.sendStandardNotification(notification);
      }

      // Update status page
      await this.updateStatusPage(incident);
    }
  }
}

Regulatory Reporting¶

Data Protection Authorities: Within 72 hours for data breaches
Financial Regulators: For incidents affecting financial operations
Law Enforcement: For criminal activities
Industry Partners: For coordinated response

Tools and Resources¶

Incident Response Tools¶

Forensic Analysis¶

# Digital forensics toolkit
FORENSIC_TOOLS=(
    "volatility"     # Memory analysis
    "autopsy"        # Disk analysis
    "wireshark"      # Network analysis
    "osquery"        # System analysis
    "yara"           # Malware detection
)

# Install forensic tools
install_forensic_tools() {
    for tool in "${FORENSIC_TOOLS[@]}"; do
        if ! command -v $tool &> /dev/null; then
            echo "Installing $tool..."
            apt-get install -y $tool
        fi
    done
}

Automation Scripts¶

#!/usr/bin/env python3
"""
Incident Response Automation
"""

import asyncio
import logging
from datetime import datetime
from typing import Dict, List

class IncidentResponseAutomation:
    def __init__(self):
        self.logger = logging.getLogger(__name__)

    async def automate_initial_response(self, alert: SecurityAlert) -> Dict:
        """Automate initial incident response actions"""
        actions_taken = []

        try:
            # Automatic containment for high-severity incidents
            if alert.severity in ['critical', 'high']:
                await self.auto_contain_threat(alert)
                actions_taken.append('auto_containment')

            # Gather initial evidence
            evidence = await self.collect_initial_evidence(alert)
            actions_taken.append('evidence_collection')

            # Notify incident response team
            await self.notify_response_team(alert)
            actions_taken.append('team_notification')

            # Create incident ticket
            ticket_id = await self.create_incident_ticket(alert)
            actions_taken.append(f'ticket_created:{ticket_id}')

            return {
                'status': 'success',
                'actions_taken': actions_taken,
                'evidence_collected': len(evidence),
                'ticket_id': ticket_id
            }

        except Exception as e:
            self.logger.error(f"Automation failed: {str(e)}")
            return {
                'status': 'error',
                'error': str(e),
                'actions_taken': actions_taken
            }

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