๐ Citizen Intelligence Agency โ Future Security Architecture
๐ฎ Advanced Security Capabilities Roadmap
๐ฏ Zero Trust, AI-Augmented, and Quantum-Resistant Security Vision
**๐ Document Owner:** CEO | **๐ Version:** 1.0 | **๐
Last Updated:** 2025-09-18 (UTC)
**๐ Review Cycle:** Quarterly | **โฐ Next Review:** 2025-12-18
---
## ๐ฏ Purpose
This document outlines the future security architecture vision for the Citizen Intelligence Agency platform, describing advanced security capabilities leveraging cutting-edge AWS security services, zero trust principles, and AI-driven security operations to protect political intelligence data.
## ๐ Table of Contents
- [Executive Overview](#-executive-overview)
- [Security Architecture Framework](#-security-architecture-framework)
- [AWS Well-Architected Framework Integration](#-aws-well-architected-framework-integration)
- [Network & DNS Security](#-network--dns-security)
- [Route 53 DNS Firewall](#route-53-dns-firewall)
- [VPC IP Address Management (IPAM)](#vpc-ip-address-management-ipam)
- [AWS Network Firewall](#aws-network-firewall)
- [Identity & Access Security](#-identity--access-security)
- [AWS Verified Access](#aws-verified-access)
- [Zero Trust Implementation](#zero-trust-implementation)
- [IAM Identity Center Integration](#iam-identity-center-integration)
- [Data & Secrets Protection](#-data--secrets-protection)
- [AWS KMS & Quantum-Resistant Cryptography](#aws-kms--quantum-resistant-cryptography)
- [Secrets Manager Enhanced Rotation](#secrets-manager-enhanced-rotation)
- [Data Loss Prevention](#data-loss-prevention)
- [Compliance & Governance](#-compliance--governance)
- [AWS Audit Manager](#aws-audit-manager)
- [Security Hub Integration](#security-hub-integration)
- [Automated Compliance Controls](#automated-compliance-controls)
- [AI-Augmented Security](#-ai-augmented-security)
- [AWS Bedrock for Security](#aws-bedrock-for-security)
- [Security Lake Integration](#security-lake-integration)
- [Intelligent Threat Detection](#intelligent-threat-detection)
- [Security Operations](#-security-operations)
- [Security Intelligence Platform](#security-intelligence-platform)
- [Automated Incident Response](#automated-incident-response)
- [Security Metrics & Reporting](#security-metrics--reporting)
- [Conclusion](#-conclusion)
## ๐ Executive Overview
The Citizen Intelligence Agency has implemented a comprehensive security architecture that leverages advanced AWS security services, zero trust principles, and AI-driven security operations. This vision document describes our current security posture and capabilities that protect the platform's sensitive political data and analytics.
Our security architecture is built around six core pillars that work together to provide defense-in-depth protection:
```mermaid
graph LR
classDef pillar fill:#2b6cb0,stroke:#1a4971,stroke-width:2px,color:white,font-weight:bold
A[CIA Security
Architecture]
A --> B[Network & DNS
Security]
A --> C[Identity & Access
Management]
A --> D[Data & Secrets
Protection]
A --> E[Compliance &
Governance]
A --> F[AI-Augmented
Security]
A --> G[Security
Operations]
class B,C,D,E,F,G pillar
style A fill:#1a365d,stroke:#1a4971,stroke-width:3px,color:white,font-weight:bold
```
## ๐๏ธ Security Architecture Framework
Our security architecture implements defense-in-depth through multiple coordinated layers of security controls:
```mermaid
flowchart TD
subgraph "Defense-in-Depth Implementation"
A[Data Layer] -->|Protects| B[Application Layer]
B -->|Protects| C[Compute Layer]
C -->|Protects| D[Network Layer]
D -->|Protects| E[Perimeter Layer]
E -->|Protects| F[Identity Layer]
G[Zero Trust Model] -->|Enforces| A
G -->|Enforces| B
G -->|Enforces| C
G -->|Enforces| D
G -->|Enforces| E
G -->|Enforces| F
H[Security Intelligence] -->|Monitors| A
H -->|Monitors| B
H -->|Monitors| C
H -->|Monitors| D
H -->|Monitors| E
H -->|Monitors| F
end
%% Styling
classDef data fill:#d1c4e9,stroke:#673ab7,stroke-width:2px,color:#311b92
classDef app fill:#bbdefb,stroke:#1976d2,stroke-width:2px,color:#1a237e
classDef compute fill:#c8e6c9,stroke:#388e3c,stroke-width:2px,color:#1b5e20
classDef network fill:#fff9c4,stroke:#fbc02d,stroke-width:2px,color:#e65100
classDef perimeter fill:#ffccbc,stroke:#ff5722,stroke-width:2px,color:#bf360c
classDef identity fill:#b39ddb,stroke:#512da8,stroke-width:2px,color:#311b92
classDef zerotrust fill:#f48fb1,stroke:#d81b60,stroke-width:2px,color:#880e4f,font-weight:bold
classDef intel fill:#90caf9,stroke:#1565c0,stroke-width:2px,color:#0d47a1,font-weight:bold
class A data
class B app
class C compute
class D network
class E perimeter
class F identity
class G zerotrust
class H intel
```
## ๐๏ธ AWS Well-Architected Framework Integration
Our security architecture is fully aligned with the AWS Well-Architected Framework, with security controls implemented across all six pillars:
```mermaid
flowchart TD
subgraph "Well-Architected Security Integration"
A[AWS Well-Architected
Framework] --> B[Security Pillar]
A --> C[Operational Excellence
Pillar]
A --> D[Reliability
Pillar]
A --> E[Performance Efficiency
Pillar]
A --> F[Cost Optimization
Pillar]
A --> G[Sustainability
Pillar]
B --> H[Identity & Access
Management]
B --> I[Detection
Controls]
B --> J[Infrastructure
Protection]
B --> K[Data
Protection]
B --> L[Incident
Response]
M[Well-Architected
Review Process] --> N[Quarterly Security
Assessment]
N --> O[Improvement
Roadmap]
O --> P[Implementation
Plan]
end
%% Styling
classDef waf fill:#0953a0,stroke:#0a2e52,stroke-width:2px,color:white,font-weight:bold
classDef pillar fill:#1e88e5,stroke:#0c47a1,stroke-width:2px,color:white,font-weight:bold
classDef secpillar fill:#d32f2f,stroke:#b71c1c,stroke-width:2px,color:white,font-weight:bold
classDef control fill:#7cb342,stroke:#558b2f,stroke-width:2px,color:white
classDef process fill:#ffb74d,stroke:#f57c00,stroke-width:2px,color:#e65100
class A waf
class B secpillar
class C,D,E,F,G pillar
class H,I,J,K,L control
class M,N,O,P process
```
### Well-Architected Implementation
We maintain a rigorous Well-Architected review process focused on security excellence:
1. **Security Pillar Excellence**
- ๐ **SEC 1:** How do you securely operate your workload?
- *Implementation:* Comprehensive IAM policies with least privilege, MFA, and centralized logging
- ๐ **SEC 2:** How do you manage identities for people and machines?
- *Implementation:* AWS IAM Identity Center with attribute-based access control and temporary credentials
- ๐ **SEC 3:** How do you manage permissions for people and machines?
- *Implementation:* Granular permission sets with JIT access and service control policies
- ๐ **SEC 4:** How do you detect and investigate security events?
- *Implementation:* Security Lake with Bedrock-powered analytics and automated incident response
- ๐ **SEC 5:** How do you protect your network resources?
- *Implementation:* Multi-layered defense with DNS Firewall, Network Firewall, and micro-segmentation
- ๐ **SEC 6:** How do you protect your compute resources?
- *Implementation:* Immutable infrastructure, runtime protection, and automated patching
- ๐ **SEC 7:** How do you classify your data?
- *Implementation:* Political data classification system with automated discovery and tagging
- ๐ **SEC 8:** How do you protect your data at rest?
- *Implementation:* KMS encryption with quantum-resistant algorithms for sensitive political data
- ๐ **SEC 9:** How do you protect your data in transit?
- *Implementation:* TLS 1.3 enforcement with certificate monitoring and rotation
- ๐ **SEC 10:** How do you anticipate, respond to, and recover from incidents?
- *Implementation:* Automated incident playbooks with ML-enhanced investigation capabilities
2. **Cross-Pillar Security Integration**
- ๐ **Operational Excellence:** Security automation pipelines with immutable infrastructure
- โก **Reliability:** Security controls designed for high availability and fault tolerance
- ๐ **Performance Efficiency:** Security services optimized for minimal performance impact
- ๐ฐ **Cost Optimization:** Security controls with efficient resource utilization
- ๐ฑ **Sustainability:** Energy-efficient security architecture minimizing carbon footprint
3. **Well-Architected Review Process**
- ๐ **Quarterly Assessment:** Regular evaluation against Well-Architected Framework
- ๐ **Continuous Improvement:** Prioritized roadmap for security enhancements
- ๐ **Workload Review:** Detailed analysis of each security component
- ๐ **Security Findings:** Tracked and remediated via Security Hub
## ๐ Network & DNS Security
Our multi-layered network security strategy forms the foundation of our defense system, protecting our infrastructure from the edge to the core.
### Route 53 DNS Firewall
Route 53 DNS Firewall provides DNS-level protection against data exfiltration attempts and connections to malicious domains:
```mermaid
flowchart LR
subgraph "DNS Security Layer"
direction TB
A[User DNS Request] --> B[Route 53 DNS Firewall]
B --> C{Rule Evaluation}
C -->|Block Rule Match| D[Block & Log]
C -->|Allow Rule Match| E[Resolve Domain]
C -->|Monitor Rule Match| F[Allow & Log]
G[Threat Intelligence Feeds] -->|Update Rules| B
end
%% Styling
classDef request fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef firewall fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef decision fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef action fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
classDef intel fill:#c4b5fd,stroke:#5b21b6,stroke-width:2px,color:#4c1d95
class A request
class B firewall
class C decision
class D,E,F action
class G intel
```
#### Key DNS Firewall Implementation
- ๐ **Advanced Rule Groups**: Custom rules blocking malicious domains and DNS tunneling techniques
- ๐ **Threat Intelligence Integration**: Real-time updates from threat feeds focused on political security
- ๐ **DNS Analytics Pipeline**: Integration with Security Lake for advanced pattern analysis
- ๐ก๏ธ **Domain Protection**: Custom rules protecting Swedish political domain infrastructure
- ๐ **Monitoring Dashboard**: Real-time visualization of DNS security metrics
### VPC IP Address Management (IPAM)
Our VPC IPAM implementation provides centralized management of IP address allocation across our multi-account environment:
```mermaid
flowchart TD
subgraph "VPC IPAM Architecture"
A[AWS Organizations
Multi-Account] --> B[IPAM
Central Management]
B --> C[Global IP Pool]
C --> D[EU-North-1
Regional Pool]
C --> E[EU-West-1
Regional Pool]
D --> F[Production VPCs]
D --> G[Development VPCs]
F --> H[Security Groups
& NACLs]
B --> I[IP Monitoring
& Compliance]
end
%% Styling
classDef org fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef ipam fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef pool fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef vpc fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
classDef security fill:#c4b5fd,stroke:#5b21b6,stroke-width:2px,color:#4c1d95
class A org
class B,I ipam
class C,D,E pool
class F,G vpc
class H security
```
#### IPAM Security Benefits
- ๐ **IP Security Observability**: Complete visibility into all network resources
- ๐ **Security Boundary Enforcement**: IP allocation aligned with security zones
- ๐ซ **Overlap Prevention**: Automatic detection of security-risky CIDR overlaps
- ๐ **Resource Tagging**: Enhanced tracking for security and compliance
- ๐ **Centralized Management**: Single pane of glass for all network addresses
### AWS Network Firewall
Our AWS Network Firewall implementation provides advanced traffic inspection and filtering:
```mermaid
flowchart TD
subgraph "Network Firewall Deployment"
A[Internet Traffic] --> B[AWS Shield]
B --> C[Network Firewall]
C -->|Stateful Rules| D[Deep Packet Inspection]
C -->|Stateless Rules| E[Header Filtering]
D & E --> F[Application Load Balancer]
F --> G[Private Subnets]
end
%% Styling
classDef internet fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef protection fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef inspection fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef internal fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
class A internet
class B,C protection
class D,E inspection
class F,G internal
```
#### Network Firewall Capabilities
- ๐ **Advanced Protocol Analysis**: Inspects traffic for politically-targeted attacks
- ๐ก๏ธ **Suricata Rules Integration**: Custom rule sets for Swedish political context
- ๐ **Centralized Deployment**: Protection across all application environments
- ๐ **Traffic Intelligence**: Behavioral analysis of network patterns
- ๐ **Security Lake Integration**: Real-time logging for advanced analytics
## ๐ Identity & Access Security
Our identity-centric security model implements zero trust principles where identity becomes the primary security perimeter.
### AWS Verified Access
AWS Verified Access provides context-aware access decisions without requiring a VPN:
```mermaid
flowchart TD
subgraph "Verified Access Implementation"
A[User Access Request] --> B[AWS Verified Access]
B --> C{Context Evaluation}
C -->|Identity| D[IAM Identity Center]
C -->|Device Posture| E[Device Trust]
C -->|Location| F[Geo-Risk Assessment]
D & E & F --> G{Access Decision}
G -->|Grant| H[Least Privilege Access]
G -->|Deny| I[Access Denied & Logged]
end
%% Styling
classDef user fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef access fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef context fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef decision fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
class A user
class B,G access
class C,D,E,F context
class H,I decision
```
#### Verified Access Implementation
- ๐ **Contextual Access Control**: Access decisions based on comprehensive context
- ๐ก๏ธ **Continuous Verification**: Ongoing evaluation throughout user sessions
- ๐ฑ **Device Trust Integration**: Verification of device security posture
- ๐ **Location Intelligence**: Risk-based filtering for geolocation context
- ๐ **Real-time Adaptation**: Dynamic permission adjustments based on risk
### Zero Trust Implementation
Our zero trust architecture eliminates implicit trust and continuously validates every access request:
```mermaid
graph LR
subgraph "Zero Trust Security Model"
A[Identity Verification] -->|Verify| B[Device Verification]
B -->|Verify| C[Network Verification]
C -->|Verify| D[Resource Access]
E[Continuous Monitoring] -->|Analyze| F[Behavior Analytics]
F -->|Inform| G[Dynamic Trust Calculation]
G -->|Adjust| D
end
%% Styling
classDef verify fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef access fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef monitor fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b,font-weight:bold
class A,B,C verify
class D access
class E,F,G monitor
```
#### Zero Trust Key Components
- ๐ **Identity as Primary Perimeter**: All access decisions start with identity verification
- ๐ซ **Least Privilege Enforcement**: Minimal access rights by default
- ๐ **Micro-Segmentation**: Fine-grained isolation for sensitive political data
- ๐ **Just-in-Time Access**: Temporary, purpose-based permission grants
- ๐ก๏ธ **Explicit Trust Verification**: All trust is earned through verification
### IAM Identity Center Integration
Our IAM Identity Center implementation provides centralized identity governance:
```mermaid
flowchart LR
subgraph "Identity Center Implementation"
A[Identity Sources] --> B[IAM Identity Center]
A -->|Corporate Directory| B
A -->|SAML Providers| B
B --> C[Permission Sets]
C --> D[AWS Account Access]
C --> E[Application Access]
F[Attribute-Based Access] --> G[Dynamic Permissions]
G --> C
end
%% Styling
classDef source fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef identity fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef permission fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef access fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
class A source
class B identity
class C,F,G permission
class D,E access
```
#### Identity Center Features
- ๐ **Single Sign-On**: Unified authentication across AWS accounts and applications
- ๐ค **Advanced User Management**: Centralized control of user lifecycle
- ๐ **Fine-grained Permissions**: Precise access control based on job functions
- ๐ **Attribute-Based Access Control**: Dynamic permissions based on user attributes
- ๐ **Access Reporting**: Comprehensive visibility into identity access patterns
## ๐พ Data & Secrets Protection
Our data protection strategy ensures that sensitive political information is secured throughout its lifecycle.
### AWS KMS & Quantum-Resistant Cryptography
Our encryption strategy leverages AWS KMS with quantum-resistant algorithms:
```mermaid
flowchart TD
subgraph "Quantum-Safe Encryption"
A[Data Classification] --> B[Encryption Requirements]
B --> C[AWS KMS]
C --> D[Symmetric Keys]
C --> E[Asymmetric Keys]
D --> F[Post-Quantum
Hybrid Mode]
E --> G[Post-Quantum
Signatures]
F & G --> H[Quantum-Safe
Encryption]
end
%% Styling
classDef data fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef kms fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef keys fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef quantum fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b,font-weight:bold
class A,B data
class C kms
class D,E keys
class F,G,H quantum
```
#### Quantum-Resistant Implementation
- ๐ **Risk-Based Encryption**: Strongest protection for political analysis data
- ๐ **Cryptographic Agility**: Framework for algorithm transitions
- ๐ **Hybrid Approach**: Combining classical and post-quantum algorithms
- ๐๏ธ **Automated Key Rotation**: Scheduled rotation of encryption keys
- ๐ก๏ธ **Long-term Protection**: Securing data against future quantum threats
### Secrets Manager Enhanced Rotation
Our secrets management strategy automates credential rotation with zero downtime:
```mermaid
flowchart LR
subgraph "Secrets Rotation Strategy"
A[AWS Secrets Manager] --> B[Database Credentials]
A --> C[API Keys]
A --> D[Service Accounts]
E[Lambda Rotator] --> F{Rotation Schedule}
F -->|Trigger| G[Automated Rotation]
G --> H[Create New Secret]
H --> I[Update Service]
I --> J[Test New Secret]
J --> K[Finalize Rotation]
end
%% Styling
classDef secrets fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef creds fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef rotation fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef process fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
class A secrets
class B,C,D creds
class E,F,G rotation
class H,I,J,K process
```
#### Secrets Management Features
- ๐ **Automated Rotation**: Continuous cycling of sensitive credentials
- ๐ **Secure Distribution**: Just-in-time delivery of secrets to services
- ๐ **Comprehensive Audit**: Complete history of secret access and changes
- ๐ **Encryption by Default**: KMS integration for key-level protection
- ๐ **Service Integration**: Native integration with RDS, Lambda, and other services
### Data Loss Prevention
Our DLP strategy prevents unauthorized exfiltration of sensitive political data:
```mermaid
flowchart TD
subgraph "Data Loss Prevention"
A[Content Classification] --> B[Sensitive Data Discovery]
B --> C[DLP Policy Engine]
C --> D[Monitoring Points]
D --> E[Network Traffic]
D --> F[Data Storage]
D --> G[User Actions]
E & F & G --> H{Policy Enforcement}
H -->|Block| I[Prevent Data Leakage]
H -->|Alert| J[Security Notification]
H -->|Log| K[Audit Trail]
end
%% Styling
classDef data fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef engine fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef monitor fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef action fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
class A,B data
class C engine
class D,E,F,G monitor
class H,I,J,K action
```
#### DLP Implementation
- ๐ **Political Data Classification**: Identification of sensitive political information
- ๐ซ **Exfiltration Prevention**: Blocking unauthorized data transfers
- ๐ **User Behavior Monitoring**: Tracking access to sensitive data
- ๐ **Continuous Scanning**: Real-time analysis of data movements
- ๐ **Comprehensive Logging**: Complete audit trail of data access
## ๐ Compliance & Governance
Our compliance framework ensures adherence to regulatory requirements while enabling business agility.
### AWS Audit Manager
AWS Audit Manager automates evidence collection and compliance reporting:
```mermaid
flowchart TD
subgraph "Audit Manager Framework"
A[Compliance Requirements] --> B[AWS Audit Manager]
B --> C[Custom Frameworks]
C --> D[GDPR Framework]
C --> E[ISO 27001 Framework]
C --> F[Political Data Framework]
B --> G[Evidence Collection]
G --> H[Automated Collection]
G --> I[Manual Collection]
H & I --> J[Evidence Repository]
J --> K[Assessment Reports]
end
%% Styling
classDef compliance fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef audit fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef framework fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef evidence fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
classDef report fill:#c4b5fd,stroke:#5b21b6,stroke-width:2px,color:#4c1d95
class A compliance
class B audit
class C,D,E,F framework
class G,H,I,J evidence
class K report
```
#### Custom Political Data Framework
Our custom AWS Audit Manager framework includes specialized controls for political data:
1. **Political Data Governance**
- PD.1: Political data classification policy
- PD.2: Political data handling procedures
- PD.3: Political data access review
- PD.4: Political data retention controls
2. **Political Source Protection**
- PS.1: Anonymous source protection mechanisms
- PS.2: Source identity segregation
- PS.3: Source metadata protection
3. **Political Analysis Controls**
- PA.1: Analysis methodology documentation
- PA.2: Analysis bias prevention
- PA.3: Analysis conclusions validation
- PA.4: Political influence safeguards
4. **Political Data Publication**
- PP.1: Pre-publication security review
- PP.2: Attribution verification
- PP.3: Public interest assessment
- PP.4: Data de-identification validation
### Security Hub Integration
Security Hub provides a comprehensive view of our security posture:
```mermaid
flowchart LR
subgraph "Security Hub Integration"
A[AWS Security Hub] --> B[Security Standards]
B --> C[AWS Foundational
Security Best Practices]
B --> D[CIS AWS
Foundations]
B --> E[Custom Political
Data Standards]
A --> F[Security Findings]
F --> G[GuardDuty]
F --> H[Inspector]
F --> I[IAM Access Analyzer]
F --> J[Integrated Response]
J --> K[EventBridge Rules]
K --> L[Automated Remediation]
end
%% Styling
classDef hub fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef standards fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef findings fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef response fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
class A hub
class B,C,D,E standards
class F,G,H,I findings
class J,K,L response
```
#### Security Hub Capabilities
- ๐ **Centralized Dashboard**: Single pane of glass for security posture
- ๐ **Automated Checks**: Continuous evaluation against security standards
- ๐ **Finding Aggregation**: Consolidated view of security issues
- ๐จ **Prioritized Alerts**: Risk-based ranking of security findings
- ๐ค **Automated Remediation**: Event-driven response to security findings
### Automated Compliance Controls
Our automated compliance controls ensure continuous adherence to requirements:
```mermaid
flowchart TD
subgraph "Automated Compliance"
A[Compliance Requirements] --> B[Policy as Code]
B --> C[AWS Config Rules]
B --> D[CloudFormation Guard]
B --> E[IAM Access Analyzer]
C & D & E --> F[Continuous Verification]
F -->|Non-Compliant| G[Automated Remediation]
F -->|Compliant| H[Compliance Evidence]
G --> I[EventBridge Rules]
I --> J[Lambda Remediations]
H --> K[Audit Manager]
end
%% Styling
classDef req fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef code fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef tools fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef verify fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
classDef remediate fill:#c4b5fd,stroke:#5b21b6,stroke-width:2px,color:#4c1d95
class A req
class B code
class C,D,E tools
class F,H verify
class G,I,J,K remediate
```
#### Automated Controls Features
- ๐ **Continuous Compliance**: Real-time evaluation of security posture
- ๐ **Policy as Code**: Infrastructure and security policies defined as code
- ๐ค **Automated Remediation**: Self-healing for compliance violations
- ๐ **Compliance Metrics**: Real-time visibility into compliance status
- ๐ **Evidence Collection**: Automated gathering of compliance evidence
## ๐ง AI-Augmented Security
Our AI-augmented security capabilities leverage machine learning to enhance threat detection and response.
### AWS Bedrock for Security
AWS Bedrock provides AI capabilities for security analysis:
```mermaid
flowchart TD
subgraph "Bedrock Security Integration"
A[Security Data] --> B[AWS Bedrock]
B --> C[Security Use Cases]
C --> D[Threat Intelligence
Analysis]
C --> E[Security Log
Investigation]
C --> F[Policy Generation
& Analysis]
G[Foundation Models] --> H[Claude Security]
G --> I[Titan Security]
G --> J[Custom Security
Fine-tuning]
H & I & J --> C
end
%% Styling
classDef data fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef bedrock fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef usecase fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef models fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
class A data
class B bedrock
class C,D,E,F usecase
class G,H,I,J models
```
#### Bedrock Security Features
- ๐ง **Political Context Understanding**: Models fine-tuned for political security domain
- ๐ **Pattern Recognition**: Identification of novel political threats
- ๐ **Natural Language Security**: Security policy analysis and generation
- ๐ **Continuous Learning**: Adaptation to evolving political threats
- ๐ค **Security Assistant**: AI-powered support for security analysts
### Security Lake Integration
Security Lake provides a foundation for AI-driven security analytics:
```mermaid
flowchart LR
subgraph "Security Lake Implementation"
A[Security Data Sources] --> B[AWS Security Lake]
A -->|CloudTrail| B
A -->|VPC Flow Logs| B
A -->|Route 53 Logs| B
A -->|WAF Logs| B
B --> C[Normalized OCSF Format]
C --> D[Security Analytics]
D --> E[Political Data Access
Analytics]
D --> F[User Behavior
Analytics]
D --> G[Threat Hunting]
end
%% Styling
classDef sources fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef lake fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef format fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef analytics fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
class A sources
class B lake
class C format
class D,E,F,G analytics
```
#### Security Lake Implementation
- ๐ **Centralized Security Data**: Single repository for all security telemetry
- ๐ **OCSF Standardization**: Normalized data for consistent analysis
- ๐ **Advanced Query Capabilities**: Complex security pattern detection
- ๐ **Historical Analysis**: Long-term storage for trend analysis
- ๐ **Partner Integrations**: Connections to specialized security tools
### Intelligent Threat Detection
Our AI-driven threat detection capabilities identify sophisticated attacks:
```mermaid
flowchart TD
subgraph "AI Threat Detection"
A[Security Telemetry] --> B[ML Processing Pipeline]
B --> C[Detection Models]
C --> D[Anomaly Detection]
C --> E[Behavioral Analysis]
C --> F[Predictive Detection]
D & E & F --> G{Threat Assessment}
G -->|High Risk| H[Automated Response]
G -->|Medium Risk| I[Analyst Investigation]
G -->|Low Risk| J[Monitoring]
end
%% Styling
classDef data fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef ml fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef models fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef assess fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
classDef response fill:#c4b5fd,stroke:#5b21b6,stroke-width:2px,color:#4c1d95
class A data
class B ml
class C,D,E,F models
class G assess
class H,I,J response
```
#### AI Threat Detection Features
- ๐ง **Political Context Awareness**: Understanding of political data value and risks
- ๐ **Advanced Pattern Recognition**: Identification of sophisticated attack patterns
- ๐ **Behavioral Baselines**: Modeling of normal user interactions with political data
- ๐จ **Early Warning System**: Proactive detection of emerging threats
- ๐ **Adaptive Learning**: Continuous improvement from new threat data
## ๐จ Security Operations
Our security operations center provides continuous monitoring, detection, and response capabilities.
### Security Intelligence Platform
Our Security Intelligence Platform integrates telemetry from multiple sources:
```mermaid
flowchart TD
subgraph "Security Intelligence Platform"
A[Data Sources] --> B[Security Lake]
A -->|AWS Services| B
A -->|Applications| B
A -->|External Threat Intel| B
B --> C[Analytics Engine]
C --> D[Executive Dashboard]
C --> E[SOC Dashboard]
C --> F[Compliance Dashboard]
G[Query Interface] --> H[Natural Language Query]
H -->|AWS Bedrock| I[Security Insights]
end
%% Styling
classDef sources fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef lake fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef analytics fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef dashboards fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
classDef query fill:#c4b5fd,stroke:#5b21b6,stroke-width:2px,color:#4c1d95
class A sources
class B lake
class C analytics
class D,E,F dashboards
class G,H,I query
```
#### Intelligence Platform Features
- ๐ **Role-Based Dashboards**: Customized views for different stakeholders
- ๐ **Advanced Visualization**: Interactive exploration of security data
- ๐ **Trend Analysis**: Historical patterns and emerging threats
- ๐ฃ๏ธ **Natural Language Interface**: Accessible security insights through conversational queries
- ๐ **Real-time Updates**: Live monitoring of security posture
### Automated Incident Response
Our automated incident response system accelerates threat mitigation:
```mermaid
flowchart TD
subgraph "Incident Response Automation"
A[Security Finding] --> B{Severity Assessment}
B -->|Critical| C[Immediate Response]
B -->|High| D[Prioritized Response]
B -->|Medium/Low| E[Standard Response]
C & D & E --> F[Response Playbook]
F --> G[EventBridge Rule]
G --> H[Step Functions Workflow]
H --> I[Containment Actions]
H --> J[Investigation Steps]
H --> K[Remediation Steps]
L[Human Approval] -.->|If Required| H
end
%% Styling
classDef finding fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef assess fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef response fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef automation fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
classDef action fill:#c4b5fd,stroke:#5b21b6,stroke-width:2px,color:#4c1d95
class A finding
class B assess
class C,D,E,F response
class G,H automation
class I,J,K,L action
```
#### Incident Response Features
- ๐จ **Automated Triage**: Risk-based prioritization of security incidents
- ๐ค **Orchestrated Response**: Pre-defined playbooks for common threats
- ๐ **Human-in-the-Loop**: Approval workflows for critical actions
- ๐ **Comprehensive Documentation**: Automatic incident documentation
- ๐ **Response Metrics**: Tracking of mean time to detection and resolution
### Security Metrics & Reporting
Our security metrics framework provides insights into security effectiveness:
```mermaid
flowchart LR
subgraph "Security Metrics Framework"
A[Data Collection] --> B[Security Metrics]
B --> C[Operational Metrics]
C --> D[Mean Time to Detect]
C --> E[Mean Time to Respond]
B --> F[Risk Metrics]
F --> G[Vulnerability Exposure]
F --> H[Threat Landscape]
B --> I[Compliance Metrics]
I --> J[Control Effectiveness]
I --> K[Audit Findings]
L[Executive Reporting] --> M[Security Posture Score]
end
%% Styling
classDef data fill:#93c5fd,stroke:#1e40af,stroke-width:2px,color:#1e3a8a,font-weight:bold
classDef metrics fill:#f87171,stroke:#991b1b,stroke-width:2px,color:#7f1d1d,font-weight:bold
classDef ops fill:#fbbf24,stroke:#b45309,stroke-width:2px,color:#92400e,font-weight:bold
classDef risk fill:#a7f3d0,stroke:#047857,stroke-width:2px,color:#064e3b
classDef comply fill:#c4b5fd,stroke:#5b21b6,stroke-width:2px,color:#4c1d95
classDef exec fill:#e9d5ff,stroke:#7e22ce,stroke-width:2px,color:#581c87
class A data
class B metrics
class C,D,E ops
class F,G,H risk
class I,J,K comply
class L,M exec
```
#### Security Metrics Implementation
- ๐ **KPI Dashboard**: Real-time view of security key performance indicators
- ๐ **Trend Visualization**: Security posture evolution over time
- ๐ฏ **Benchmarking**: Comparison against industry security standards
- ๐ **Automated Reporting**: Scheduled security posture reports
- ๐ผ **Business Context**: Security metrics aligned with political intelligence objectives
## ๐ Conclusion
The Citizen Intelligence Agency's advanced security architecture leverages the latest AWS security services, zero trust principles, and AI capabilities to protect sensitive political intelligence data. Our comprehensive approach addresses security across all layersโfrom network protection with Route 53 DNS Firewall and AWS Network Firewall to identity-centric security with AWS Verified Access and IAM Identity Center.
By implementing AI-augmented security through AWS Bedrock and Security Lake, we've created an intelligent security ecosystem capable of detecting and responding to sophisticated threats targeting political data. Our quantum-resistant cryptography strategy ensures long-term protection of sensitive information, while our automated compliance framework with AWS Audit Manager provides continuous assurance of our security posture.
Our security architecture is fully aligned with the AWS Well-Architected Framework, integrating security best practices across all six pillars and maintaining rigorous quarterly reviews to ensure continuous improvement. This holistic approach not only protects our political intelligence platform but also enables reliability, operational excellence, performance efficiency, cost optimization, and sustainability.
This security architecture will continue to evolve in response to emerging threats and AWS service innovations, maintaining our position at the forefront of political intelligence security.
---
## ๐ Related Documents
- [๐ก๏ธ Security Architecture](SECURITY_ARCHITECTURE.md) - Current security implementation
- [๐ฏ Threat Model](THREAT_MODEL.md) - STRIDE/MITRE ATT&CK threat analysis
- [๐ฐ Financial Security Plan](FinancialSecurityPlan.md) - Security investment and costs
- [๐
End-of-Life Strategy](End-of-Life-Strategy.md) - Technology lifecycle management
- [โก CI/CD Workflows](WORKFLOWS.md) - Security automation and DevSecOps
- [๐ ISMS Compliance Mapping](ISMS_COMPLIANCE_MAPPING.md) - ISMS policy framework
---
**๐ Document Control:**
**โ
Approved by:** James Pether Sรถrling, CEO - Hack23 AB
**๐ค Distribution:** Public
**๐ท๏ธ Classification:** [](https://github.com/Hack23/ISMS-PUBLIC/blob/main/CLASSIFICATION.md#confidentiality-levels)
**๐
Effective Date:** 2025-09-18
**โฐ Next Review:** 2025-12-18
**๐ฏ Framework Compliance:** [](https://github.com/Hack23/ISMS-PUBLIC/blob/main/CLASSIFICATION.md) [](https://github.com/Hack23/ISMS-PUBLIC/blob/main/CLASSIFICATION.md) [](https://github.com/Hack23/ISMS-PUBLIC/blob/main/CLASSIFICATION.md) [](https://github.com/Hack23/ISMS-PUBLIC/blob/main/CLASSIFICATION.md)