AWS Cloud Security Monitoring & Incident Response Platform

ACTIVE
Platform Status: Monitoring 58 AWS accounts across 4 regions. Last incident: 2 hours ago (Low severity).

Project Overview

This enterprise security platform provides comprehensive threat detection, automated incident response, and compliance monitoring for multi-account AWS environments. The solution implements the AWS Well-Architected Framework with emphasis on the Security Pillar.

58
AWS Accounts
2.3m
Mean Time to Detect
4.7m
Mean Time to Respond
98.5%
Compliance Score

Architecture Design

Multi-Layer Security Architecture

Layer 1: Data Collection
  • CT AWS CloudTrail Enabled
  • VPC VPC Flow Logs Enabled
  • GD GuardDuty Enabled
  • SH Security Hub Enabled
Layer 2: Processing & Analysis
  • λ AWS Lambda 28 Functions
  • EB EventBridge 15 Rules
  • SF Step Functions 8 Workflows
  • SQS SQS Queues 5 Queues
Layer 3: Storage & Analytics
  • S3 Amazon S3 3 Buckets
  • OS OpenSearch 2.5 TB
  • CW CloudWatch Logs 15 Log Groups
  • ATH Athena Configured

Cross-Account Architecture

The platform uses AWS Organizations with Service Control Policies (SCPs) for centralized security governance. Each member account forwards security findings to a central security account for aggregation and analysis.

Account Type Count Purpose Monthly Cost
Security Tooling 1 Central security monitoring and management $1,850
Production 24 Business applications and services $420 (avg)
Development 18 Development and testing environments $180 (avg)
Sandbox 15 Experimental and POC environments $75 (avg)

Implementation Details

Infrastructure as Code (IaC)

The entire platform is deployed using AWS Cloud Development Kit (CDK) with TypeScript. The infrastructure is version-controlled and deployed through CI/CD pipelines.

typescript
SecurityMonitoringStack.ts
// Main CDK Stack Definition export class SecurityMonitoringStack extends cdk.Stack { constructor(scope: cdk.Construct, id: string, props?: cdk.StackProps) { super(scope, id, props); // Create central Security Hub const securityHub = new aws_securityhub.CfnHub(this, 'SecurityHub', { enableDefaultStandards: false }); // Enable GuardDuty in all regions const guardDutyMaster = new aws_guardduty.CfnDetector(this, 'GuardDutyMaster', { enable: true, findingPublishingFrequency: 'FIFTEEN_MINUTES' }); // Create centralized logging bucket with Object Lock const logBucket = new s3.Bucket(this, 'SecurityLogsBucket', { encryption: s3.BucketEncryption.S3_MANAGED, versioned: true, objectLockEnabled: true, objectLockConfiguration: { objectLockEnabled: 'Enabled', rule: { defaultRetention: { mode: 'GOVERNANCE', days: 365 } } }, lifecycleRules: [{ transitions: [{ storageClass: s3.StorageClass.GLACIER, transitionAfter: cdk.Duration.days(90) }] }] }); // Lambda function for automated remediation const remediationFunction = new lambda.Function(this, 'RemediationHandler', { runtime: lambda.Runtime.PYTHON_3_9, handler: 'remediation.handler', code: lambda.Code.fromAsset('lambda/remediation'), timeout: cdk.Duration.seconds(300), memorySize: 1024, environment: { SECURITY_HUB_REGION: this.region, LOG_BUCKET: logBucket.bucketName } }); // EventBridge rule for Security Hub findings new events.Rule(this, 'HighSeverityRule', { eventPattern: { source: ['aws.securityhub'], detailType: ['Security Hub Findings - Imported'], detail: { findings: { Severity: { Label: [{ 'equals-ignore-case': 'HIGH' }] } } } }, targets: [new targets.LambdaFunction(remediationFunction)] });

Automated Response Playbooks

The platform implements 15 automated response playbooks for common security incidents. Each playbook is documented with detailed runbooks and escalation procedures.

Playbook ID Incident Type Automation Level Response Time Success Rate
PB-001 Unauthorized API Access Full Automation 2.1 minutes 99.8%
PB-002 Cryptojacking Detection Full Automation 3.4 minutes 98.7%
PB-003 S3 Bucket Policy Violation Semi-Automated 5.2 minutes 97.3%
PB-004 IAM Policy Drift Full Automation 1.8 minutes 99.5%
PB-005 Network Scanning Detected Semi-Automated 4.7 minutes 96.8%

Machine Learning Integration

Custom machine learning models are deployed using Amazon SageMaker to analyze security findings and reduce false positives. The models are trained on historical security data and updated monthly.

ML Model Performance: 68% reduction in false positive rate, 92% accuracy in threat classification, models retrained every 30 days with new data.

Security Metrics & KPIs

Key Performance Indicators

99.99%
Platform Uptime
2.3m
Mean Time to Detect
4.7m
Mean Time to Respond
2.1%
False Positive Rate

Compliance Metrics

Framework Control Coverage Compliance Score Last Assessment Status
CIS AWS Foundations 100% 98.7% 2024-03-15 Compliant
NIST CSF 95% 96.2% 2024-03-10 Compliant
PCI DSS v4.0 88% 94.1% 2024-03-05 Partial
HIPAA 92% 97.3% 2024-03-12 Compliant
GDPR 85% 93.8% 2024-03-08 Partial

Threat Detection Statistics

Threat Category Detections (30 days) Automated Responses Manual Interventions False Positives
Unauthorized Access 142 138 4 3
Cryptojacking 28 28 0 1
Policy Violations 356 321 35 12
Network Attacks 87 76 11 8
Data Exfiltration 15 12 3 2

Cost Analysis & Optimization

Monthly Cost Breakdown

Service Cost (Monthly) Percentage Optimization Status Recommendations
GuardDuty $1,250 32% Optimized Consolidated member accounts
OpenSearch $980 25% Review Needed Consider moving cold data to S3
CloudTrail $420 11% Optimized Selective event logging enabled
S3 Storage $385 10% Optimized Lifecycle policies in place
Lambda $310 8% Optimized Provisioned concurrency optimized
Security Hub $285 7% Optimized Custom standards only
Other Services $270 7% Review Needed Monitor Config rule evaluations

Cost Optimization Strategies

  • Data Retention Policies: Security logs are moved to S3 Glacier after 90 days, reducing OpenSearch costs by 40%
  • Selective Monitoring: GuardDuty only monitors production and critical development accounts
  • Lambda Optimization: Provisioned concurrency optimized based on usage patterns, reducing cold starts by 85%
  • S3 Intelligent Tiering: Automated movement of infrequently accessed security data
  • CloudTrail Event Selectors: Only log security-relevant API calls
ROI Calculation: The platform has prevented an estimated $2.8M in potential breach costs over 12 months, representing a 12:1 return on investment.

API Reference & Integration

REST API Endpoints

The platform exposes a RESTful API for integration with external systems and custom dashboards. All endpoints require IAM authentication.

http
API Endpoints
# Get security metrics GET /api/v1/metrics Authorization: AWS4-HMAC-SHA256 Credential=... Response: { "mttd": "2.3", "mttr": "4.7", "compliance_score": 98.5, "incidents_last_24h": 12, "false_positive_rate": 2.1 } # Trigger manual remediation POST /api/v1/remediate Authorization: AWS4-HMAC-SHA256 Credential=... Body: { "incident_id": "inc-2024-03-15-001", "playbook": "PB-001", "resource_arn": "arn:aws:ec2:us-east-1:123456789012:instance/i-0abcdef1234567890", "severity": "HIGH" } Response: { "remediation_id": "rem-2024-03-15-001", "status": "IN_PROGRESS", "estimated_completion": "2024-03-15T14:30:00Z" } # Get compliance report GET /api/v1/compliance/{framework} Authorization: AWS4-HMAC-SHA256 Credential=... Response: { "framework": "CIS", "assessment_date": "2024-03-15", "score": 98.7, "failed_controls": [ { "control_id": "CIS-1.1", "description": "Avoid use of root account", "status": "FAILED", "remediation": "Enable IAM user with MFA" } ] }

Event Schema

The platform emits events to EventBridge for integration with other AWS services. Below is the schema for security findings:

json
Event Schema
{ "version": "1.0", "id": "security-finding-event", "detail-type": "Security Finding", "source": "com.security.platform", "account": "123456789012", "time": "2024-03-15T10:30:00Z", "region": "us-east-1", "resources": [ "arn:aws:ec2:us-east-1:123456789012:instance/i-0abcdef1234567890" ], "detail": { "finding_id": "sec-2024-03-15-001", "severity": "HIGH", "confidence": 95, "title": "Unauthorized API Access Detected", "description": "Root account API call from unusual IP address", "category": "UnauthorizedAccess", "detection_source": "GuardDuty", "resource_type": "AWS::EC2::Instance", "resource_arn": "arn:aws:ec2:us-east-1:123456789012:instance/i-0abcdef1234567890", "first_seen": "2024-03-15T10:28:00Z", "last_seen": "2024-03-15T10:29:00Z", "remediation": { "playbook": "PB-001", "automated": true, "status": "PENDING" }, "evidence": { "source_ip": "203.0.113.25", "user_agent": "AWS CLI", "api_call": "TerminateInstances", "aws_region": "us-east-1" } } }

Integration Examples

  • Slack Integration: Real-time alerts to security channel with actionable buttons
  • Jira Integration: Automatic ticket creation for manual review items
  • Splunk Integration: Forwarding enriched security events to SIEM
  • PagerDuty Integration: On-call escalation for critical incidents
  • Custom Dashboards: Power BI/Tableau integration for executive reporting

Technical Specifications

Performance Requirements

Metric Target Actual SLA
Event Processing Latency < 60 seconds 42 seconds 99.9%
API Response Time < 200ms 145ms 99.5%
Data Retention 365 days 365 days 100%
Concurrent Users 50+ 32 (avg) N/A
Data Processing Volume 10 TB/month 8.4 TB/month 95%

Deployment Regions

  • Primary: us-east-1 (N. Virginia) - Full deployment
  • Secondary: us-west-2 (Oregon) - DR deployment
  • Monitoring: eu-west-1 (Ireland) - European compliance
  • Backup: ap-southeast-1 (Singapore) - Asian compliance

Security & Compliance Features

  • End-to-end encryption (TLS 1.3 for transit, AES-256 for rest)
  • IAM roles with least privilege principle
  • VPC endpoints for all AWS services
  • Automatic key rotation every 90 days
  • Audit trails for all administrative actions
  • Regular penetration testing (quarterly)
  • Automated vulnerability scanning