FUTURE_SECURITY_ARCHITECTURE.md

May 31, 2026 · View on GitHub

🚀 Riksdagsmonitor — Future Security Architecture

🛡️ Evolution Roadmap: From Static Website to Advanced Intelligence Platform
🎯 Post-Quantum Ready · AI-Augmented Security · Zero-Trust Architecture

Document Version: 2.1
Last Updated: 2026-05-31
Classification: Public
Owner: Hack23 AB (Org.nr 5595347807)
Review Cycle: Quarterly

🎯 Executive Summary

This document outlines the future security architecture for Riksdagsmonitor over the next 3-11 years (2026-2037). The roadmap focuses on proactive security evolution rather than reactive patches, ensuring the web platform with interactive Chart.js/D3.js dashboards remains secure against emerging threats including post-quantum cryptography, AI-powered attacks, and advanced persistent threats.

Strategic Goals:

🔐 Post-Quantum Readiness - Cryptographic agility before quantum computers threaten current algorithms
🤖 AI-Augmented Security - Machine learning for threat detection and anomaly analysis
🛡️ Zero-Trust Architecture - Never trust, always verify, assume breach mentality
📊 Privacy-Preserving Analytics - Intelligence without surveillance
🌐 Decentralized Resilience - Distributed architecture for high availability

Current State Baseline
Threat Landscape Evolution
Future Security Domains
Implementation Roadmap
Technology Evolution
Compliance Evolution
Risk Management
Success Metrics
Security Investment & Budget Planning
Conclusion
References

📚 Architecture Documentation Map

The following table shows all 15 architecture documents maintained for Riksdagsmonitor. This document is highlighted.

Document	Focus	Description
ARCHITECTURE.md	Current	C4 system architecture model
DATA_MODEL.md	Current	Data structures and entities
FLOWCHART.md	Current	Business process flows
STATEDIAGRAM.md	Current	System state transitions
MINDMAP.md	Current	System conceptual map
SWOT.md	Current	Strategic analysis
SECURITY_ARCHITECTURE.md	Security	Current security controls
THREAT_MODEL.md	Security	STRIDE threat analysis
FUTURE_SECURITY_ARCHITECTURE.md	Security	Future security roadmap (this document)
FUTURE_ARCHITECTURE.md	Future	Architecture evolution roadmap
FUTURE_DATA_MODEL.md	Future	Enhanced data architecture
FUTURE_FLOWCHART.md	Future	Improved process workflows
FUTURE_STATEDIAGRAM.md	Future	Advanced state management
FUTURE_MINDMAP.md	Future	Capability expansion map
FUTURE_SWOT.md	Future	Future strategic opportunities

🔐 ISMS Policy Alignment

Policy Framework Integration

This document aligns with the following Hack23 ISMS policies from Hack23/ISMS-PUBLIC:

Policy	Relevance	Key Requirements
Information Security Policy	Primary	Security objectives, management commitment, risk appetite
Secure Development Policy	High	Secure coding standards, SAST/DAST, supply chain security
Access Control Policy	High	Least privilege, MFA, zero-trust principles
Risk Management Policy	High	Risk register, treatment plans, residual risk targets
Incident Response Policy	Medium	MTTR targets, escalation procedures, post-incident reviews
Cryptography Policy	High	Algorithm standards, key management, PQC migration
Supplier Security Policy	Medium	Third-party risk (Chart.js, D3.js, GitHub, AWS)
Business Continuity Policy	Medium	Dual deployment, RTO/RPO targets

Security Control Implementation Status

Control Domain	Current (2026)	Target (2028)	Target (2030)	Framework
Access Control	🟡 Partial	🟢 Full	🟢 Full	ISO 27001 A.9
Cryptography	🟡 Classical TLS 1.3	🟡 Hybrid PQC	🟢 Full PQC	ISO 27001 A.10
Physical Security	🟢 GitHub/AWS managed	🟢 Full	🟢 Full	ISO 27001 A.11
Operations Security	🟡 Partial	🟢 Full	🟢 Full	ISO 27001 A.12
Network Security	🟡 TLS/CDN only	🟡 WAF added	🟢 Full ZTA	ISO 27001 A.13
Supplier Relations	🟡 SRI/SBOM	🟢 Full SBOM	🟢 Full	ISO 27001 A.15
Incident Management	🟡 Documented	🟡 Automated	🟢 AI-assisted	ISO 27001 A.16
Compliance	🟡 Managed	🟡 Certified	🟢 ISO 27001 Cert	ISO 27001 A.18

Alignment with NIST CSF 2.0 Functions

Function	Current Maturity	2028 Target	2030 Target
GV — Govern	🟡 Level 2	🟢 Level 3	🟢 Level 4
ID — Identify	🟡 Level 2	🟢 Level 3	🟢 Level 4
PR — Protect	🟡 Level 2	🟢 Level 3	🟢 Level 4
DE — Detect	🔴 Level 1	🟡 Level 2	🟢 Level 3
RS — Respond	🟡 Level 2	🟢 Level 3	🟢 Level 4
RC — Recover	🟡 Level 2	🟢 Level 3	🟢 Level 4

1. �� Current State Baseline

1.1 Current Security Posture (2026 Q1)

graph TB
    subgraph "2026 Q1 Security Stack (Current)"
        L1[🌐 Network: TLS 1.3, HTTPS-only, AWS CloudFront + GitHub CDN]
        L2[🛡️ Application: HTML/CSS/JavaScript, Chart.js/D3.js dashboards]
        L3[🔑 Access: GitHub MFA, SSH keys, GPG signing, AWS OIDC]
        L4[📋 Integrity: Git history, Branch protection, SRI hashes]
        L5[🔍 Monitoring: Dependabot, CodeQL, Secret scanning]
        L6[🚨 Response: Documented procedures, Rollback capability, Dual deployment]
    end
    
    L1 --> L2
    L2 --> L3
    L3 --> L4
    L4 --> L5
    L5 --> L6
    
    style L1 fill:#4caf50,color:#000000
    style L2 fill:#4caf50,color:#000000
    style L3 fill:#ff9800,color:#000000
    style L4 fill:#ff9800,color:#000000
    style L5 fill:#2196f3,color:#ffffff
    style L6 fill:#f44336,color:#ffffff

Strengths:

✅ LOW residual risk (7.21/10.0)
✅ Zero high-priority vulnerabilities
✅ Dual deployment with automatic failover (AWS + GitHub Pages)
✅ Interactive dashboards with SRI hash validation
✅ Comprehensive ISMS documentation
✅ AWS OIDC authentication (no long-lived credentials)
✅ NEW (2026-02-18): SLSA Level 2+ Build Provenance attestations
✅ NEW (2026-02-18): SBOM generation in SPDX format
✅ NEW (2026-02-18): Documentation as code (API, coverage, E2E reports)

Limitations:

⚠️ CSP 'unsafe-inline' required for Chart.js/D3.js (future: nonce-based CSP)
⚠️ Client-side JavaScript increases attack surface (XSS risks)
⚠️ CDN dependency for Chart.js/D3.js (supply chain risk)
⚠️ No real-time threat intelligence integration
⚠️ Limited observability (no APM for client-side performance)

2. ⚠️ Threat Landscape Evolution

2.1 Emerging Threats (2026-2030)

graph TB
    subgraph "2026-2027: Near-Term Threats"
        T1[🤖 AI-Powered Phishing<br/>Deepfake social engineering]
        T2[🔐 Cryptographic Weakening<br/>Quantum computing advances]
        T3[⚡ Supply Chain Attacks<br/>Compromised CI/CD]
    end
    
    subgraph "2028-2029: Mid-Term Threats"
        T4[🧠 AI-Generated Exploits<br/>Automated vulnerability discovery]
        T5[🌐 DNS Hijacking 2.0<br/>Advanced BGP attacks]
        T6[📱 IoT Botnets<br/>Distributed attacks]
    end
    
    subgraph "2030+: Long-Term Threats"
        T7[💻 Quantum Decryption<br/>TLS 1.3 broken]
        T8[🤖 AGI Security Attacks<br/>Autonomous threat actors]
        T9[🌍 Nation-State APTs<br/>Advanced persistent threats]
    end
    
    T1 --> T4
    T2 --> T7
    T3 --> T6
    T4 --> T8
    T5 --> T9
    
    style T1 fill:#ff9800,color:#000000
    style T2 fill:#ff9800,color:#000000
    style T3 fill:#ff9800,color:#000000
    style T7 fill:#f44336,color:#ffffff
    style T8 fill:#f44336,color:#ffffff
    style T9 fill:#f44336,color:#ffffff

2.2 Regulatory Evolution

Framework	Current (2026)	Future (2028-2030)	Impact on Riksdagsmonitor
NIS2 Directive	Applicable	Stricter controls	Incident reporting <24h
EU Cyber Resilience Act	Proposed	Mandatory SBOM	Software supply chain transparency
AI Act	Draft	Enforced	AI system categorization if ML added
Post-Quantum Cryptography	NIST standards	Mandatory	Algorithm migration required
GDPR	Enforced	Enhanced	Privacy by design for any user data

3. 🏗️ Future Security Domains

3.1 Post-Quantum Cryptography (PQC)

Timeline: 2027 Q1 - Q4
Priority: 🔴 HIGH

graph LR
    Current[Current: TLS 1.3<br/>RSA 2048, ECDSA P-256] --> Hybrid[2027 Q2: Hybrid Mode<br/>Classical + PQC]
    Hybrid --> Full[2028 Q1: Full PQC<br/>CRYSTALS-Kyber, CRYSTALS-Dilithium]
    
    style Current fill:#90caf9,color:#000000
    style Hybrid fill:#ff9800,color:#000000
    style Full fill:#4caf50,color:#000000

Implementation Plan:

Phase 1: Assessment (2027 Q1)

Inventory all cryptographic dependencies
GitHub Pages TLS capabilities assessment
Browser compatibility matrix (PQC support)
Performance impact analysis

Phase 2: Hybrid Deployment (2027 Q2-Q3)

Configure hybrid TLS (classical + PQC)
Browser fallback mechanisms
Performance monitoring
User experience validation

Phase 3: Full PQC Migration (2028 Q1)

Deprecate classical-only connections
Full PQC enforcement for AWS CloudFront
Certificate management automation
Documentation updates

NIST PQC Standards:

Key Encapsulation: CRYSTALS-Kyber (KEM)
Digital Signatures: CRYSTALS-Dilithium, FALCON
Fallback: Classical algorithms during transition

AWS Integration:

CloudFront custom SSL certificate with PQC support
S3 presigned URLs with post-quantum signatures
Route 53 DNSSEC with PQC algorithms

Control Mapping:

ISO 27001: A.10.1.1 (Cryptographic controls)
NIST CSF 2.0: PR.DS-2 (Data in transit protected)
CIS Controls v8.1: 3.10 (Encrypt data in transit)

3.2 AI-Augmented Security

Timeline: 2026 Q3 - 2027 Q4
Priority: 🟡 MEDIUM

graph TB
    subgraph "AI Security Layers"
        A1[🤖 Anomaly Detection<br/>Traffic pattern analysis]
        A2[🔍 Threat Intelligence<br/>Real-time feed integration]
        A3[🛡️ Behavioral Analysis<br/>User interaction patterns]
        A4[📊 Predictive Security<br/>Vulnerability forecasting]
    end
    
    Data[Log Data] --> A1
    External[Threat Feeds] --> A2
    Analytics[User Analytics] --> A3
    SBOM[SBOM Data] --> A4
    
    A1 --> Alerts[Security Alerts]
    A2 --> Alerts
    A3 --> Alerts
    A4 --> Alerts
    
    style A1 fill:#2196f3,color:#ffffff
    style A2 fill:#2196f3,color:#ffffff
    style A3 fill:#2196f3,color:#ffffff
    style A4 fill:#2196f3,color:#ffffff

Capabilities:

1. Anomaly Detection (2026 Q4)

Traffic pattern analysis via AWS CloudWatch and CloudFront logs
Baseline establishment for normal behavior
Real-time alerting on deviations
Integration with GitHub Actions logs

2. Threat Intelligence (2027 Q1)

Integration with threat intelligence feeds (MISP, OTX)
Automated IOC matching against CloudFront access logs
Proactive blocking of known-bad actors via AWS WAF
Threat actor profiling

3. Behavioral Analysis (2027 Q2)

User interaction patterns (if analytics added)
Bot detection and mitigation via AWS WAF
Session anomaly detection
Privacy-preserving analytics (differential privacy)
Client-side dashboard performance monitoring

4. Predictive Security (2027 Q3)

Dependency vulnerability forecasting (Chart.js/D3.js)
Zero-day prediction models
Attack surface trend analysis (JavaScript attack surface)
Risk score predictions

Privacy Considerations:

✅ No PII collection
✅ Anonymized analytics only
✅ GDPR-compliant by design
✅ User opt-out mechanisms

Control Mapping:

ISO 27001: A.12.6 (Technical vulnerability management)
NIST CSF 2.0: DE.CM-1 (Network monitored)
CIS Controls v8.1: 13.1 (Security event alerting)

3.3 Zero-Trust Architecture

Timeline: 2027 Q1 - 2028 Q4
Priority: 🟢 LOW (Static website context)

Principles:

Never Trust, Always Verify - Even GitHub infrastructure
Assume Breach - Design for compromise scenarios
Least Privilege - Minimal permissions at all layers
Micro-Segmentation - Isolate components

Future Enhancements:

Contributor Access (2027 Q2)

Time-limited access tokens
Just-in-time privilege elevation
Continuous authentication verification
Behavior-based access policies

Infrastructure Verification (2027 Q4)

✅ IMPLEMENTED (2026-02-18): GitHub Actions attestations (SLSA Level 2+)
✅ IMPLEMENTED (2026-02-18): Build Provenance verification
Future Goal: SLSA Level 3 (hermetic builds, non-falsifiable provenance)
Binary authorization for deployments
Reproducible builds

Network Isolation (2028 Q2)

Content Security Policy Level 3 with nonces (remove 'unsafe-inline')
Subresource Integrity (SRI) for all external resources (Chart.js, D3.js)
CORS policy enforcement
DNS-over-HTTPS (DoH) via Route 53
AWS WAF integration with CloudFront

Control Mapping:

ISO 27001: A.13.1 (Network security management)
NIST CSF 2.0: PR.AC-5 (Network integrity protected)
CIS Controls v8.1: 13.6 (Deploy network-based IDS)

3.4 Advanced Monitoring & Observability

Timeline: 2026 Q4 - 2027 Q4
Priority: 🟡 MEDIUM

graph TB
    subgraph "Observability Stack Evolution"
        M1[Current: GitHub Actions<br/>Basic workflow monitoring]
        M2[2027 Q1: APM Integration<br/>Real-time performance tracking]
        M3[2027 Q3: SIEM Integration<br/>Security event correlation]
        M4[2028 Q1: Distributed Tracing<br/>End-to-end visibility]
    end
    
    M1 --> M2
    M2 --> M3
    M3 --> M4
    
    style M1 fill:#90caf9,color:#000000
    style M2 fill:#ff9800,color:#000000
    style M3 fill:#2196f3,color:#ffffff
    style M4 fill:#4caf50,color:#000000

Components:

1. Application Performance Monitoring (2027 Q1)

Real User Monitoring (RUM) for Chart.js/D3.js dashboards
Synthetic monitoring from global locations
Performance regression detection
Lighthouse CI integration
Client-side error tracking (Sentry or similar)

Metrics:

First Contentful Paint (FCP) < 1s
Time to Interactive (TTI) < 2s
Cumulative Layout Shift (CLS) < 0.05
Chart.js rendering performance < 500ms
Core Web Vitals monitoring

2. Security Information & Event Management (2027 Q3)

Centralized log aggregation (GitHub + AWS CloudFront + S3 access logs)
Real-time security event correlation
Automated incident response workflows
Compliance reporting automation

Integration:

Elastic Stack (ELK) or Splunk
GitHub audit log streaming
AWS CloudTrail and CloudWatch Logs
CloudFront access logs
Automated alerting to PagerDuty/Opsgenie

3. Distributed Tracing (2028 Q1)

OpenTelemetry instrumentation
Request flow visualization
Latency analysis
Dependency mapping

Control Mapping:

ISO 27001: A.12.4 (Logging and monitoring)
NIST CSF 2.0: DE.CM-1 (Network monitored)
CIS Controls v8.1: 8.2 (Collect audit logs)

3.5 🛰️ Intelligence-Integrity & Counter-AI Controls (OSINT/INTOP, to 2037)

Fielding the Political-Intelligence Capability Catalog (C1–C32) makes analytic integrity a first-class security property. The threats in FUTURE_THREAT_MODEL.md §Political-Intelligence Capability Threat Analysis (PI-T1…PI-T7) are countered here by integrity-by-construction: nothing reaches a published judgment without an evidence anchor, a provenance check, a neutrality gate and a human sign-off. These controls realize the catalog's assurance pillar (C26–C32).

3.5.1 Control set

#	Control	Counters	Mechanism (Horizon)
II-1 Evidence-anchor gate	Every analytic record must carry a graded `dok_id`/primary-source ref or it is rejected	PI-T1, PI-T3	CI hard-fail today (H1); runtime gate on fusion/estimative writes (H3)
II-2 Provenance & content credentials	C2PA-sign evidence; verify on cite; detect synthetic media	PI-T3	KMS-signed manifests, S3 Object Lock, deepfake detector, refuse-to-cite on failure (H3)
II-3 Prompt-injection & poisoning defense	Screen inputs to SAT/estimative agents; isolate untrusted document text	PI-T1, PI-T2	Bedrock Guardrails, input sanitization, retrieval allow-listing, tool-permission minimization (H3)
II-4 Party-symmetry / neutrality gate	Block asymmetric framing before publish	PI-T4	CI neutrality audit (H1→H2); longitudinal symmetry monitoring + dual-control override (H3)
II-5 Calibration-as-release-metric	Forecast products gated on rolling Brier; immutable, pre-registered questions	PI-T6	Append-only calibration ledger; release blocked on drift; independent resolution criteria (H2→H3)
II-6 I&W integrity	Protect tripwires from decoy flooding / warning suppression	PI-T5	Adaptive thresholds, redundant indicators, anomaly-on-anomaly, human triage (H3)
II-7 FIMI ethics gate	Aggregate-only, no citizen profiling, advisory-not-accusatory	PI-T7	Hard ethics gate in pipeline; attribution-confidence floors; human framing (H3)
II-8 Human-on-the-loop sign-off	No estimative/warning product auto-publishes	PI-T2, PI-T4, PI-T7	Mandatory analyst sign-off state (see `FUTURE_STATEDIAGRAM.md` §18)
II-9 Tradecraft auditability	ICD-203 compliance + reproducibility logged per product	PI-T2, PI-T6	Assumption logs, source characterization, audit trail, GDPR Art. 9 basis stamped

3.5.2 Control architecture

flowchart TD
    SRC[Public sources] --> ING[Ingest plus provenance sign<br/>II-2]
    ING --> POIS{Poisoning plus injection screen<br/>II-3}
    POIS -->|Reject| QUAR[Quarantine plus alert]
    POIS -->|Clean| EVID{Evidence-anchor gate<br/>II-1}
    EVID -->|No dok_id| DROP[Reject record]
    EVID -->|Anchored| ANAL[SAT plus forecast engine]
    ANAL --> CAL{Calibration gate<br/>II-5}
    CAL -->|Drift| HOLD[Hold for retrain]
    CAL -->|OK| NEUT{Neutrality gate<br/>II-4}
    NEUT -->|Asymmetric| REWORK[Rebalance]
    NEUT -->|Symmetric| SIGN[Human sign-off<br/>II-8 plus II-9]
    SIGN --> PUB[Publish plus audit trail]
    REWORK --> ANAL

    style POIS fill:#ff006e,color:#ffffff
    style EVID fill:#ff006e,color:#ffffff
    style CAL fill:#ff006e,color:#ffffff
    style NEUT fill:#ff006e,color:#ffffff
    style SIGN fill:#9c27b0,color:#ffffff
    style PUB fill:#4caf50,color:#000000
    style DROP fill:#f44336,color:#ffffff
    style QUAR fill:#f44336,color:#ffffff

3.5.3 Framework mapping

Control	ISO 27001:2022	NIST CSF 2.0	OWASP LLM
II-1 Evidence anchor	A.5.34 (PII), A.8.28 (secure coding)	PR.DS, GV.OC	LLM09 Overreliance
II-2 Provenance	A.8.24 (crypto), A.5.33 (records)	PR.DS-6 (integrity)	LLM08
II-3 Injection defense	A.8.28, A.8.16 (monitoring)	DE.CM, PR.PS	LLM01 / LLM03
II-4 Neutrality gate	A.5.1 (policies), A.8.29 (testing)	GV.OC, GV.RR	LLM09
II-5 Calibration	A.8.16, A.5.36 (compliance)	ID.IM, DE.AE	LLM09
II-6 I&W integrity	A.8.16 (monitoring), A.5.7 (threat intelligence)	DE.CM, DE.AE	LLM04 / LLM10
II-7 FIMI ethics	A.5.34, A.18 (privacy)	GV.OC, ID.RA	—
II-8 Human-on-the-loop	A.5.4 (mgmt responsibilities)	GV.RR-1	LLM08 Excessive Agency
II-9 Tradecraft auditability	A.5.33 (records), A.8.15 (logging)	GV.RR, PR.PS	LLM08 / LLM09

Governing principle. Security for a political-intelligence capability is not perimeter defense alone — it is integrity of the analytic product. Controls II-1…II-9 ensure that even a fully compromised model or a poisoned source cannot launder a manipulated, biased, or unevidenced judgment through the platform's credibility. Every gate is fail-closed; every published product is reproducible, neutral, evidence-anchored and human-accountable under the Hack23 AI Policy.

4. 🚀 Implementation Roadmap

4.1 Timeline Overview

gantt
    title Riksdagsmonitor Security Evolution (2026-2030)
    dateFormat YYYY-MM
    section Post-Quantum
    PQC Assessment           :2027-01, 3M
    Hybrid PQC Deployment   :2027-04, 6M
    Full PQC Migration      :2028-01, 3M
    section AI Security
    Anomaly Detection       :2026-10, 3M
    Threat Intelligence     :2027-01, 3M
    Behavioral Analysis     :2027-04, 3M
    Predictive Security     :2027-07, 3M
    section Zero-Trust
    Contributor Access      :2027-04, 3M
    Infrastructure Verify   :2027-10, 3M
    Network Isolation       :2028-04, 3M
    section Monitoring
    APM Integration         :2027-01, 3M
    SIEM Integration        :2027-07, 3M
    Distributed Tracing     :2028-01, 3M

4.2 Phase-by-Phase Breakdown

2026 Q3-Q4: Foundation

✅ Complete current ISMS documentation (DONE: Feb 2026)
✅ AWS CloudFront + S3 deployment (DONE: Feb 2026)
✅ Dual deployment with GitHub Pages DR (DONE: Feb 2026)
🔄 Implement APM monitoring (Lighthouse CI)
🔄 Enable GitHub Advanced Security features
🔄 AI anomaly detection prototype
🔄 Nonce-based CSP for Chart.js/D3.js (remove 'unsafe-inline')

2027 Q1-Q2: Early Adoption

🔐 PQC assessment and hybrid deployment
🤖 AI threat intelligence integration
🛡️ Zero-trust contributor access model
📊 SIEM integration (ELK/Splunk)

2027 Q3-Q4: Expansion

🔐 Full PQC readiness testing
🤖 Behavioral analysis deployment
🛡️ Infrastructure attestation (SLSA Level 3)
📊 Advanced monitoring dashboards

2028 Q1-Q2: Maturity

🔐 Full PQC enforcement
🤖 Predictive security models
🛡️ Network micro-segmentation
📊 Distributed tracing

2028 Q3-Q4: Optimization

🔧 Performance tuning
📖 Documentation updates
🎯 Compliance validation
🏆 Maturity assessment

2029-2030: Continuous Improvement

🔄 Regular security audits
🔄 Emerging threat response
🔄 Technology refresh cycles
🔄 ISMS updates

5. 💻 Technology Evolution

5.1 Hosting Platform Migration Considerations

Current: AWS CloudFront + S3 (Multi-region, cross-region replication)
Future Options:

Platform	Pros	Cons	Timeline	Recommendation
AWS CloudFront + S3	99.9% SLA, DDoS protection, multi-region	Cost, complexity	Current	✅ Stay (already implemented)
GitHub Pages	Free, integrated, simple	Limited customization, single provider	Current (DR)	✅ Keep as DR
AWS WAF	Advanced protection, rate limiting, geo-blocking	Additional cost	2027 Q2	🟡 High priority
Multi-CDN Strategy	Resilience, performance optimization	Complexity, cost	2028 Q4	🟢 Consider for scale

Decision Criteria:

Cost-effectiveness for static content
Security feature set (WAF, DDoS, monitoring)
ISMS compliance capabilities
Migration effort vs. benefit

Recommended Path:

2026-2027: Stay on AWS CloudFront + S3, maximize security features
2027 Q2: AWS WAF integration for advanced application-layer protection
2028 Q1: Enhanced monitoring and observability (APM, SIEM)
2028 Q4: Evaluate multi-CDN strategy if traffic scales significantly

5.2 Content Delivery Network (CDN) Evolution

graph LR
    Current[AWS CloudFront + S3<br/>Multi-region deployment] --> Enhanced[AWS WAF Integration<br/>Advanced application protection]
    Enhanced --> Premium[Multi-CDN Strategy<br/>Resilience & performance]
    
    style Current fill:#4caf50,color:#000000
    style Enhanced fill:#ff9800,color:#000000
    style Premium fill:#4caf50,color:#000000

Enhancements:

AWS WAF Integration (2027 Q2)

Advanced Web Application Firewall (WAF) with CloudFront
Bot protection and rate limiting
Geo-blocking capabilities
Custom rule sets for dashboard protection
XSS and SQL injection prevention (defense-in-depth)

Multi-CDN Strategy (2028 Q4)

Primary: AWS CloudFront
Failover: Cloudflare or Fastly
Automatic failover detection via Route 53
Load balancing across CDNs for optimal performance

5.3 Security Tooling Roadmap

Tool Category	Current (2026)	Future (2027-2028)	Purpose
SAST	CodeQL	+ Semgrep, SonarCloud	Enhanced code scanning
SCA	Dependabot, dependency-review	+ npm audit, Snyk, FOSSA	Better dependency insights
DAST	None	OWASP ZAP, Burp Suite	Dynamic scanning of dashboards
Secret Scanning	GitHub	+ GitGuardian	Advanced secret detection
SBOM	Manual	CycloneDX, SPDX	Automated generation (Chart.js, D3.js)
Container Scanning	N/A	N/A	Not applicable (static hosting)
Fuzzing	None	OSS-Fuzz	Input validation for CIA data
Client-Side Security	None	JSXray, Retire.js	JavaScript vulnerability detection

6. 📋 Compliance Evolution

6.1 Framework Maturity Progression

graph TB
    subgraph "2026: Foundation"
        C1[ISO 27001: 7 controls]
        C2[NIST CSF: 6 functions]
        C3[CIS Controls: 6 controls]
    end
    
    subgraph "2027-2028: Expansion"
        C4[ISO 27001: 15 controls]
        C5[NIST CSF 2.0: Full framework]
        C6[CIS Controls: 18 controls IG2]
        C7[SOC 2 Type II readiness]
    end
    
    subgraph "2029-2030: Maturity"
        C8[ISO 27001: Certification]
        C9[ISO 27701: Privacy extension]
        C10[CIS Controls: IG3 compliance]
        C11[SOC 2 Type II audit]
    end
    
    C1 --> C4
    C2 --> C5
    C3 --> C6
    C4 --> C8
    C5 --> C9
    C6 --> C10
    C7 --> C11
    
    style C1 fill:#90caf9,color:#000000
    style C4 fill:#ff9800,color:#000000
    style C8 fill:#4caf50,color:#000000

6.2 New Compliance Requirements

NIS2 Directive (2027 Q4)

Incident reporting within 24 hours
Supply chain security requirements
Board-level security responsibility
Regular penetration testing

EU Cyber Resilience Act (2028 Q2)

Software Bill of Materials (SBOM)
Vulnerability disclosure program
Security updates for product lifetime
CE marking for digital products

AI Act (2028-2030)

AI system risk categorization
Documentation requirements for high-risk AI
Human oversight mechanisms
Transparency obligations

6.3 Per-Control Maturity Progression

Control	Framework	Current Level	2027 Target	2030 Target	Timeline	Milestone
Cryptographic Controls	ISO 27001 A.10.1	Level 2 (Classical TLS)	Level 3 (Hybrid PQC)	Level 4 (Full PQC)	2027 Q2 – 2028 Q1	PQC migration complete
Access Control	ISO 27001 A.9.1	Level 2 (MFA, SSH)	Level 3 (Zero-Trust)	Level 4 (JIT, ABAC)	2027 Q2 – 2028 Q4	Zero-trust contributor model
Network Security	ISO 27001 A.13.1	Level 2 (TLS/CDN)	Level 3 (WAF added)	Level 4 (Full ZTA)	2027 Q2 – 2028 Q4	AWS WAF + CSP nonces
Logging & Monitoring	ISO 27001 A.12.4	Level 1 (GitHub Actions)	Level 3 (APM+SIEM)	Level 4 (AI-SIEM)	2027 Q1 – 2028 Q1	Full SIEM integration
Vulnerability Management	ISO 27001 A.12.6	Level 2 (Dependabot)	Level 3 (DAST added)	Level 4 (Predictive)	2026 Q4 – 2027 Q3	DAST integration
Incident Management	ISO 27001 A.16.1	Level 2 (Documented)	Level 3 (Automated)	Level 4 (AI-assisted)	2027 Q1 – 2028 Q1	Automated playbooks
Supply Chain Security	ISO 27001 A.15.2	Level 2 (SBOM+SRI)	Level 3 (SLSA L3)	Level 4 (Full provenance)	2027 Q3 – 2028 Q1	SLSA Level 3
Identity Management	ISO 27001 A.9.4	Level 2 (MFA+SSH)	Level 3 (Zero-Trust)	Level 4 (ABAC+JIT)	2027 Q2 – 2028 Q4	Just-in-time access
Network Monitoring	NIST DE.CM-1	Level 1 (None)	Level 2 (CloudFront logs)	Level 3 (Behavioral AI)	2026 Q4 – 2027 Q3	Behavioral analysis
Threat Intelligence	NIST ID.RA-2	Level 1 (Dependabot)	Level 2 (MISP/OTX feeds)	Level 3 (Predictive)	2027 Q1 – 2027 Q3	Threat feed integration
Secure Dev Lifecycle	CIS 16	Level 2 (CodeQL+Dependabot)	Level 3 (+DAST+Fuzz)	Level 4 (Full SDL)	2026 Q4 – 2027 Q4	Full SSDLC implemented
Data Protection	CIS 3	Level 2 (SRI+CSP)	Level 3 (nonce-based)	Level 4 (Full isolation)	2027 Q1 – 2028 Q1	CSP nonces for Chart.js

6.4 CIS Controls v8.1 Implementation Roadmap

CIS Control	Description	Current (IG1)	2027 (IG2)	2030 (IG3)
CIS 1	Inventory & Control of Enterprise Assets	🟢 Complete	🟢 Full	🟢 Full
CIS 2	Inventory & Control of Software Assets	🟡 Partial (SBOM)	🟢 Full	🟢 Full
CIS 3	Data Protection	🟡 Partial (SRI, CSP)	🟢 Full (nonces)	🟢 Full
CIS 4	Secure Config of Enterprise Assets	🟢 Complete (GitHub/AWS)	🟢 Full	🟢 Full
CIS 6	Access Control Management	🟡 Partial (MFA, SSH)	🟢 Full (Zero-Trust)	🟢 Full
CIS 7	Continuous Vulnerability Management	🟡 Partial (Dependabot)	🟢 Full (+DAST)	🟢 Full
CIS 8	Audit Log Management	🔴 Minimal	🟡 Partial (APM)	🟢 Full (SIEM)
CIS 12	Network Infrastructure Management	🟡 Partial (CDN)	🟢 Full (WAF)	🟢 Full
CIS 13	Network Monitoring & Defense	🔴 Minimal	🟡 Partial	🟢 Full (AI)
CIS 16	Application Software Security	🟡 Partial (SAST)	🟢 Full (+DAST)	🟢 Full
CIS 17	Incident Response Management	🟡 Documented	🟢 Automated	🟢 AI-assisted
CIS 18	Penetration Testing	🔴 None	🟡 Annual	🟢 Continuous

7. ⚠️ Risk Management

7.1 Future Risk Register

Risk ID	Future Threat	Likelihood (2030)	Impact	Mitigation	Timeline
FR-01	Quantum decryption of TLS	HIGH	CRITICAL	PQC migration	2027-2028
FR-02	AI-powered supply chain attack (Chart.js/D3.js)	MEDIUM	HIGH	✅ SLSA Level 2+ (2026), SBOM, SRI	2027 Q4 (Level 3)
FR-03	AWS infrastructure compromise	LOW	HIGH	Multi-CDN strategy, AWS security best practices	2028
FR-04	DNS hijacking via Route 53	MEDIUM	MEDIUM	DNSSEC, DoH, IAM least privilege	2027
FR-05	Deepfake social engineering	MEDIUM	MEDIUM	MFA, training	2026
FR-06	IoT botnet DDoS	MEDIUM	LOW	AWS WAF, rate limiting, AWS Shield	2027
FR-07	Zero-day in GitHub Actions	LOW	MEDIUM	SHA-pinning, attestations	Ongoing
FR-08	Regulatory non-compliance	MEDIUM	HIGH	ISMS evolution	Ongoing
FR-09	XSS in Chart.js/D3.js dashboards	MEDIUM	MEDIUM	CSP nonces, SRI, regular updates	2027
FR-10	Client-side data exfiltration	LOW	MEDIUM	CSP, browser security, monitoring	2027

7.2 Residual Risk Evolution

graph LR
    Current[2026: 7.21/10.0<br/>LOW Risk] --> Enhanced[2027: 4.5/10.0<br/>VERY LOW Risk]
    Enhanced --> Optimized[2030: 2.0/10.0<br/>MINIMAL Risk]
    
    style Current fill:#4caf50,color:#000000
    style Enhanced fill:#4caf50,color:#000000
    style Optimized fill:#4caf50,color:#000000

Target Risk Reduction:

Current: 99.5% risk reduction (web platform with dashboards)
2027: 99.75% risk reduction (PQC + AI security + nonce-based CSP)
2030: 99.9% risk reduction (Full zero-trust + AWS WAF)

8. 📊 Success Metrics

8.1 Key Performance Indicators (KPIs)

Metric	Current (2026)	Target (2027)	Target (2030)
Residual Risk Score	7.21/10.0	4.5/10.0	2.0/10.0
MTTR (Incidents)	<17 min	<10 min	<5 min
Vulnerability Window	<7 days	<24 hours	<4 hours
Compliance Score	85%	95%	99%
Security Automation	60%	80%	95%
Threat Detection Rate	N/A	95%	99%
False Positive Rate	N/A	<5%	<2%
Dashboard XSS Protection	Basic (CSP)	Enhanced (nonce-based)	Advanced (isolation)

8.2 Maturity Assessment

Current State: Maturity Level 2 (Managed)

Documented processes
Basic automation
Reactive security posture

Target 2027: Maturity Level 3 (Defined)

Organization-wide standards
Advanced automation
Proactive threat hunting

Target 2030: Maturity Level 4 (Quantitatively Managed)

Data-driven decisions
Predictive security
Continuous optimization

9. 💰 Security Investment & Budget Planning

Per-Phase Investment Estimates

Phase	Period	Estimated Investment	Key Investments	Priority
Foundation	2026 Q3-Q4	€5,000 – €10,000	Lighthouse CI, GitHub Advanced Security, SIEM baseline	🔴 High
Early Adoption	2027 Q1-Q2	€15,000 – €25,000	AWS WAF, PQC assessment, AI anomaly detection, SIEM	🔴 High
Expansion	2027 Q3-Q4	€20,000 – €35,000	Full AI security stack, behavioral analysis, SIEM integration	🟡 Medium
Maturity	2028 Q1-Q2	€25,000 – €40,000	Full PQC migration, AWS WAF, distributed tracing	🟡 Medium
Optimization	2028 Q3-Q4	€10,000 – €20,000	Audits, compliance validation, ISO 27001 certification	🟢 Low
Continuous	2029-2030	€10,000 – €15,000/yr	Maintenance, audits, ISMS updates, training	🟢 Low

Total Estimated Investment (2026-2030): €85,000 – €145,000

Resource Requirements

Resource	Current	2027	2028	2030
Security Architect (FTE equivalent)	0.2	0.4	0.6	0.5
DevSecOps Engineer (FTE equivalent)	0.1	0.3	0.4	0.3
External Security Auditor	Annual	Annual	ISO 27001 pre-audit	Certification
PQC Specialist (Contractor)	—	Q1 2027	Q1 2028	—
SIEM Administrator	—	Q3 2027	Full	Full

Return on Investment (ROI)

Investment	Cost	Risk Reduction Value	ROI Estimate
AWS WAF + Rate Limiting	~€5,000/yr	Prevents DDoS, reduces XSS exposure	10x – 20x
AI Anomaly Detection	~€8,000/yr	Early threat detection, reduces MTTR by 70%	5x – 15x
PQC Migration	~€20,000 one-time	Future-proofs encryption against quantum threats	Long-term strategic
SIEM Integration	~€12,000/yr	Compliance automation, faster incident response	3x – 8x
ISO 27001 Certification	~€15,000	Customer trust, regulatory compliance, contracts	5x – 10x
GitHub Advanced Security	~€3,000/yr	Automated vulnerability detection in CI/CD	8x – 15x

Cost Optimization Strategies

✅ Open-Source First: Prefer OSS tools (ELK, Semgrep) over commercial solutions
✅ GitHub-Native: Leverage GitHub Advanced Security features (included in GitHub Enterprise)
✅ AWS Reserved Instances: Reserved capacity for CloudFront/WAF for cost predictability
✅ Automation: Reduce manual security effort through GitHub Actions automation
✅ Phased Investment: Align spending with roadmap milestones to manage cash flow

10. 🤝 Conclusion

This Future Security Architecture demonstrates Hack23 AB's commitment to proactive security evolution rather than reactive patching. By implementing post-quantum cryptography before it's necessary, AI-augmented security before attacks become fully autonomous, and zero-trust principles before breaches occur, Riksdagsmonitor will maintain its security leadership while delivering interactive Chart.js/D3.js dashboards.

Key Takeaways:

🔐 Post-Quantum Ready by 2028 - Ahead of predicted quantum threat timeline
🤖 AI-Augmented Security by 2027 - Machine learning for threat detection
🛡️ Zero-Trust Architecture by 2028 - Comprehensive trust verification
📊 99.9% Risk Reduction by 2030 - Industry-leading security posture
🏆 ISO 27001 Certification Track - Formal compliance validation
🎨 Nonce-Based CSP by 2027 - Eliminate 'unsafe-inline' for Chart.js/D3.js
☁️ AWS WAF Integration by 2027 - Advanced application-layer protection

Alignment with Business Goals:

💼 Competitive advantage through security leadership
🤝 Customer trust through transparency
💰 Cost efficiency through automation
🚀 Innovation enablement through secure foundation
📋 Compliance posture supporting expansion

🤖 AI/LLM Security Evolution (2026-2037)

AI Model Security Trajectory

Current State (2026): Anthropic Claude Opus 4.8 via Amazon Bedrock with safe-outputs validation

Security Implications of AI Evolution:

Period	AI Model Level	Security Challenges	Mitigations
2026-2027	Opus 4.8-5.x (minor updates ~2.3mo)	Prompt injection, model hallucination, bias	Safe-outputs validation, human review, bias testing
2028-2029	Opus 6.x-7.x (annual major upgrades)	Autonomous agent risks, multi-modal attack vectors	Agent sandboxing, output filtering, behavioral monitoring
2030-2032	Opus 8.x-10.x / Pre-AGI	AI-powered adversarial attacks, deepfake political content	AI-augmented SIEM, deepfake detection, content provenance
2033-2035	Near-AGI systems	Autonomous threat actors, AI arms race	Zero-trust AI, formal verification, cryptographic AI attestation
2036-2037	AGI / Post-AGI era	Superhuman threat actors, unknown attack vectors	Quantum-resistant crypto, AI alignment verification, democratic safeguards

AI Security Controls Roadmap

Phase 1 (2026-2027): Foundation

✅ Amazon Bedrock guardrails and content filtering
✅ Safe-outputs validation for all agent actions
✅ Model output auditing and logging
🔄 Prompt injection detection and prevention
🔄 AI model version pinning with rollback capability

Phase 2 (2028-2030): Advanced Protection

🔴 AI-powered threat detection (behavioral analytics)
🔴 Multi-modal content provenance (C2PA standard)
🔴 Autonomous agent containment and monitoring
🔴 AI model supply chain security (model signing, attestation)

Phase 3 (2031-2033): Pre-AGI Security

🔴 Formal verification of AI agent behavior
🔴 Cryptographic attestation of AI-generated content
🔴 AI alignment monitoring and enforcement
🔴 Decentralized AI security governance

Phase 4 (2034-2037): AGI-Era Security

🔴 Post-quantum cryptography fully deployed
🔴 AI-to-AI security protocols
🔴 Democratic oversight mechanisms for AGI systems
🔴 Global threat intelligence federation
🔴 Autonomous security response with human override

LLM Competitor Security Considerations

Multi-Model Security Strategy:

Evaluate security posture of each model provider (Anthropic, OpenAI, Google, Meta) at every major release
Maintain model-agnostic security controls that work across all providers via Amazon Bedrock
Monitor for model-specific vulnerabilities disclosed by security researchers
Continuous benchmarking of AI safety features every ~2.3 months aligned with minor model updates
Prepare for potential paradigm shifts (quantum AI, neuromorphic computing) requiring new security frameworks

📖 References

ISMS Documentation

SECURITY_ARCHITECTURE.md - Current security controls
THREAT_MODEL.md - Current threat analysis
WORKFLOWS.md - CI/CD workflows
ARCHITECTURE.md - System architecture
Hack23 ISMS
Information Security Policy
Secure Development Policy
Access Control Policy
Risk Management Policy
Cryptography Policy

External Standards

Citizen Intelligence Agency - Reference security architecture
Black Trigram - Reference security patterns
Hack23 ISMS-PUBLIC - ISMS policies and standards

Riksdagsmonitor Architecture Portfolio

Document	Focus
🏛️ Architecture	C4 models
📊 Data Model	Data entities
🔄 Flowchart	Process flows
📈 State Diagram	State transitions
🧠 Mindmap	Conceptual relationships
💼 SWOT	Strategic analysis
🛡️ Security Architecture	Current security controls
🎯 Threat Model	STRIDE/MITRE ATT&CK
🔮 Future Threat Model	Future threat analysis
🔮 Future Security Architecture	Planned security (this document)

Document Control
Repository: https://github.com/Hack23/riksdagsmonitor
Path: /FUTURE_SECURITY_ARCHITECTURE.md | Classification: Public | Next Review: 2026-08-31
Change Management: Requires Security Architect approval for major revisions

🌐 Evolving the Current IMF Security Boundary toward the Future Zero-Trust State

Baseline: the already-implemented IMF trust boundary, egress allow-list, and STRIDE coverage are documented in SECURITY_ARCHITECTURE.md §IMF and THREAT_MODEL.md §IMF. The diagram below shows how those existing controls evolve when the runtime moves to AWS Lambda + Aurora.

Authoritative hub: analysis/imf/README.md · analysis/imf/agentic-integration.md · analysis/imf/indicators-inventory.json · analysis/imf/data-dictionary.md · .github/aw/ECONOMIC_DATA_CONTRACT.md

Trust boundary (target zero-trust state)

flowchart LR
    subgraph Trusted["Trust Boundary — Riksdagsmonitor (AWS GovCloud-like posture)"]
        Lambda[Lambda Workers · IMF context]
        Cache[(Aurora · imf_cache · SHA-256 + vintage pin)]
        Audit[CloudTrail + GuardDuty]
    end
    subgraph Public["Public-Internet · IMF Open APIs (Datamapper unauth · SDMX subscription-key)"]
        Datamapper[www.imf.org/external/datamapper/api/v1]
        SDMX[api.imf.org]
    end
    Lambda -- HTTPS · TLS 1.3 · pinned SHA-256 --> Datamapper
    Lambda -- HTTPS · TLS 1.3 · pinned SHA-256 --> SDMX
    Datamapper -. JSON payload .-> Lambda
    SDMX -. SDMX-JSON payload .-> Lambda
    Lambda --> Cache
    Lambda --> Audit

IMF-specific controls (mapped to target frameworks)

Control	Implementation	ISO 27001	NIST CSF 2.0	CIS v8.1
Egress allow-list	Squid + iptables limit egress to `www.imf.org`, `api.imf.org` only	A.13.1	PR.AC-5	13.4
Payload integrity	SHA-256 pin per (dataflow, indicator, country, vintage); supersedes-chain	A.8.2	PR.DS-6	3.11
Vintage discipline	Reject payload >6 mo old without staleness annotation	A.8.10	PR.DS-1	3.5
Rate-limit guard	≤30 req/min self-imposed; exponential back-off; emits metric	A.13.1	PR.AC-4	4.7
Provenance audit	Every article-claim row in `article_economic_provenance`	A.5.28	DE.AE-3	8.2
No auth, no PII	IMF data is anonymous public macro statistics; GDPR DPIA short-circuit	A.5.34	GV.OV	14.2

Future BIA addition

Asset	Confidentiality	Integrity	Availability	RTO	RPO
IMF cache (Aurora)	PUBLIC	HIGH	STANDARD	24h	N/A
IMF API egress path	PUBLIC	HIGH	STANDARD	24h (fallback to last cached vintage)	N/A

Egress hosts (allow-list): www.imf.org (Datamapper REST · WEO/FM, unauthenticated), api.imf.org (SDMX 3.0 REST · IFS/BOP/DOTS/GFS/PCPS/ER/MFS_IR/MFS_PR, subscription-key authenticated via the Azure APIM Ocp-Apim-Subscription-Key header / IMF_SDMX_SUBSCRIPTION_KEY secret). Both HTTPS-only; payloads are public macro statistics with no PII.

Canonical rule. Every economic claim in a Riksdagsmonitor article cites an IMF dataflow first; World Bank citations are reserved for governance, environment and social residue (the classes IMF does not publish). SCB is the Swedish-specific ground truth layer. See ECONOMIC_DATA_CONTRACT.md v2.1 for the banned-phrase list and vintage discipline (>6 mo → annotation).

🔗 Hack23 Ecosystem

🌐 Platforms	📦 Open-Source Projects	🛡️ Governance & Standards
🗳️ Riksdagsmonitor — Swedish Parliament intelligence 🇪🇺 EU Parliament Monitor — European coverage 🕵️ Citizen Intelligence Agency — political-data engine 🌐 Hack23 AB — corporate site 📰 Hack23 Blog — engineering & policy 💼 Hack23 on LinkedIn	🗳️ Hack23/riksdagsmonitor 🕵️ Hack23/cia 🇪🇺 Hack23/euparliamentmonitor 🔌 Hack23/european-parliament-mcp ✅ Hack23/cia-compliance-manager 🥋 Hack23/black-trigram 🏠 Hack23/homepage	🛡️ Hack23 ISMS-PUBLIC — public ISMS 🔒 Information Security Policy 🤖 AI Policy 🧪 Secure Development Policy 🎯 Threat Modeling Policy ⚠️ Vulnerability Management 🏷️ Classification Framework

🗳️ Empower citizens · 🔍 Strengthen democratic accountability · 🕵️ Illuminate the political process