🔮 Hack23 AB — Riksdagsmonitor Future Threat Model

🛡️ Proactive Security for the Three-Horizon Architecture Evolution (2026–2037)
🔍 STRIDE • MITRE ATT&CK • AI Workflow Expansion • Advanced Dashboards • Real-Time Data • AWS Serverless • Bedrock • Neptune • Aurora • Cognito

📋 Document Owner: CEO | 📄 Version: 2.1 | 📅 Last Updated: 2026-06-02 (UTC)
🔄 Review Cycle: Quarterly | ⏰ Next Review: 2026-09-02
🏢 Owner: Hack23 AB (Org.nr 5595347807) | 🏷️ Classification: Public

🎯 Purpose & Scope

Establish a forward-looking threat model for Riksdagsmonitor's three-horizon architecture evolution (2026–2037), covering new capabilities and expanded attack surfaces across the planned roadmap. This document complements the current THREAT_MODEL.md by analyzing threats specific to planned features that do not yet exist in production, and is the security counterpart to the strategy expressed in FUTURE_ARCHITECTURE.md, FUTURE_DATA_MODEL.md, FUTURE_FLOWCHART.md, FUTURE_STATEDIAGRAM.md, FUTURE_SWOT.md, FUTURE_MINDMAP.md, FUTURE_SECURITY_ARCHITECTURE.md and FUTURE_WORKFLOWS.md.

📐 Coverage dimensions (v2.1):

🧭 The Three Horizons (threat-model framing)

Horizon boundaries are roadmap intent, not commitments — the platform deliberately stays static through 2027 (FUTURE_ARCHITECTURE.md §2.6). H3 threats are pre-modeled so that controls are designed before the first managed service is provisioned.

🔗 Policy Alignment

Aligned with Hack23 AB Threat Modeling Policy and Secure Development Policy.

🔍 Scope — Planned Architecture Changes

📅 Threat Landscape Evolution Timeline

timeline
    title Riksdagsmonitor Threat Landscape Evolution (2026–2037)
    section 🟢 H1 — Static Baseline (Today)
        2024-2026 : Supply-chain & CI/CD compromise
                  : Prompt injection in agentic workflows
                  : Content integrity attacks
                  : GitHub Actions credential theft
    section 🔵 H2 — Static Deepening (2026–2027)
        2026 Q2 : Pipeline cache poisoning
               : Multi-workflow AI orchestration abuse
               : 🗳️ Neutrality erosion via AI drift (F13)
               : 🔗 MCP ecosystem compromise (F21)
        2026 Q3 : Translation manipulation (14 languages)
               : 📊 Election forecast weaponization (F14)
               : Real-time data manipulation
        2026 Q4 : Nordic federation trust attacks
               : Cross-platform data integrity
               : 🌍 FIMI information laundering (F16)
    section 🟠 H3 — AWS Serverless AI (2027–2037)
        2027 : 🔒 GDPR Art. 9 scope expansion (F17)
             : Cloud IAM & identity attacks
             : SQL/NoSQL injection
        2028 : RAG/Knowledge-Base poisoning
             : 🧠 Foundation model regression (F19)
             : Agentic excessive agency
             : 📱 Mobile API abuse
        2029-2037 : ⚖️ EU AI Act compliance (F20)
                  : Multi-region failover hijack
                  : Post-quantum cryptographic transition
                  : AGI-era governance challenges
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📊 Future System Classification

🏷️ Evolved Security Classification

Note: This table describes the future Riksdagsmonitor system security classification. The CIA classification badges in the Document Control section represent the classification of this document itself, not the future system, and may therefore differ from the future system's target classification. The H3 authenticated tier is the first time the platform processes per-user personal data — a DPIA is mandatory before Cognito launch (see F6 and FUT-013/FUT-014).

🏗️ Future Architecture Threat Analysis

🎭 STRIDE per Future Component

🔐 Future Crown Jewel Analysis

flowchart TB
    subgraph H2_JEWELS["🔵 H2 Crown Jewels (Static-Deep)"]
        REALTIME["📊 Real-Time Voting Data<br/>Live parliamentary decisions"]
        POLITICIAN["👤 Politician Profiles<br/>Historical performance records"]
        TRANSLATION["🌐 Translation Pipeline<br/>14-language content integrity"]
        CIA_DATA["🏛️ CIA Intelligence Data<br/>19 visualization products"]
    end

    subgraph H3_JEWELS["🟠 H3 Crown Jewels (AWS Serverless)"]
        GRAPH["🕸️ Neptune Knowledge Graph<br/>+ Bedrock KB vectors"]
        FORECAST["🔮 SageMaker Forecast Models<br/>Election & coalition predictions"]
        AURORA["🗄️ Aurora/OpenSearch Stores<br/>Authoritative managed data"]
        IDENTITY["🔑 Cognito Identities<br/>First authenticated user tier"]
        AGENTS_AI["💬 Bedrock Agents<br/>Autonomous conversational AI"]
    end

    subgraph FUTURE_VECTORS["⚔️ Future Attack Vectors"]
        WEBSOCKET["🔌 WebSocket Exploitation"]
        CACHE_POISON["💉 Cache Poisoning"]
        LLM_MULTI["🤖 Multi-LLM Orchestration Attack"]
        API_CHAIN["🔗 API Chain Compromise"]
        RAG_POISON["📚 RAG / KB Poisoning"]
        IAM_ABUSE["🪪 Cloud IAM & Token Abuse"]
        EXCESS_AGENCY["🧠 Agentic Excessive Agency"]
    end

    subgraph FUTURE_AGENTS["👥 Elevated Threat Agents"]
        ELECTION_ACTOR["🗳️ Election Interference Actor"]
        AI_ADVERSARY["🤖 AI-Enabled Adversary"]
        STATE_ACTOR["🏛️ Nation-State APT"]
        CLOUD_ATTACKER["☁️ Cloud-Native Attacker"]
    end

    WEBSOCKET --> REALTIME
    CACHE_POISON --> CIA_DATA
    LLM_MULTI --> TRANSLATION
    API_CHAIN --> POLITICIAN
    RAG_POISON --> GRAPH
    RAG_POISON --> FORECAST
    IAM_ABUSE --> AURORA
    IAM_ABUSE --> IDENTITY
    EXCESS_AGENCY --> AGENTS_AI

    ELECTION_ACTOR --> WEBSOCKET
    AI_ADVERSARY --> LLM_MULTI
    AI_ADVERSARY --> EXCESS_AGENCY
    STATE_ACTOR --> CACHE_POISON
    CLOUD_ATTACKER --> IAM_ABUSE
    CLOUD_ATTACKER --> RAG_POISON

    style REALTIME fill:#ffcdd2,stroke:#d32f2f,color:#000
    style POLITICIAN fill:#fff3e0,stroke:#ff9800,color:#000
    style TRANSLATION fill:#e3f2fd,stroke:#2196f3,color:#000
    style CIA_DATA fill:#ffcdd2,stroke:#d32f2f,color:#000
    style GRAPH fill:#ffcdd2,stroke:#d32f2f,color:#000
    style FORECAST fill:#fff3e0,stroke:#ff9800,color:#000
    style AURORA fill:#ffcdd2,stroke:#d32f2f,color:#000
    style IDENTITY fill:#fff3e0,stroke:#ff9800,color:#000
    style AGENTS_AI fill:#ffcdd2,stroke:#d32f2f,color:#000
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🎯 Future Priority Threat Scenarios

Scenario F1: Real-Time Vote Manipulation During Parliamentary Session

Scenario F2: CIA Data Pipeline Cache Poisoning

Scenario F3: Multi-Workflow AI Orchestration Attack

Scenario F4: Translation Pipeline Integrity Attack

The scenarios above (F1–F4) are Horizon 2 threats — they materialise while the platform is still static. The scenarios below (F5–F12) are Horizon 3 threats that only become live once managed AWS services are provisioned; they are pre-modeled so controls ship with each service (FUTURE_ARCHITECTURE.md §3, §11.4 AWS Security Services).

Scenario F5: Bedrock Knowledge-Base / RAG Poisoning (H3)

Scenario F6: Cognito Account Takeover & IDOR (H3)

Scenario F7: Lambda/IAM Privilege Escalation & Data Exfiltration (H3)

Scenario F8: Bedrock Agent Excessive Agency (H3)

Scenario F9: SageMaker Election-Forecast Manipulation (H3)

Scenario F10: AppSync/API Gateway Public-API Abuse (H3)

Scenario F11: Multi-Region Failover & Replication Tampering (H3)

Scenario F12: Nordic/EU Federation Cross-Jurisdiction Integrity (H3)

🛡️ Future Security Control Requirements

Planned Controls for Future Architecture

Future STRIDE → Control Mapping

🎖️ Attacker-Centric Threat Modeling — Future Attack Vectors

👥 Future Threat Agent Classification

🌳 Future Attack Tree — Real-Time Vote Manipulation

flowchart TD
    ROOT["🎯 Manipulate Real-Time Vote Display"]
    
    A1["⚔️ A1: Compromise Data Feed<br/>Probability: 15%"]
    A2["⚔️ A2: Man-in-the-Middle<br/>Probability: 10%"]
    A3["⚔️ A3: Client-Side Injection<br/>Probability: 20%"]
    A4["⚔️ A4: Cache Poisoning<br/>Probability: 12%"]
    
    A1_1["🔧 A1.1: Compromise Riksdag API proxy"]
    A1_2["🔧 A1.2: DNS hijacking of data source"]
    A2_1["🔧 A2.1: TLS downgrade attack"]
    A2_2["🔧 A2.2: WebSocket hijacking"]
    A3_1["🔧 A3.1: XSS via dashboard parameter"]
    A3_2["🔧 A3.2: Browser extension manipulation"]
    A4_1["🔧 A4.1: CDN cache poisoning"]
    A4_2["🔧 A4.2: LocalStorage corruption"]
    
    ROOT --> A1
    ROOT --> A2
    ROOT --> A3
    ROOT --> A4
    A1 --> A1_1
    A1 --> A1_2
    A2 --> A2_1
    A2 --> A2_2
    A3 --> A3_1
    A3 --> A3_2
    A4 --> A4_1
    A4 --> A4_2
    
    style ROOT fill:#ffcdd2,stroke:#d32f2f,color:#000
    style A1 fill:#fff3e0,stroke:#ff9800,color:#000
    style A2 fill:#fff3e0,stroke:#ff9800,color:#000
    style A3 fill:#e3f2fd,stroke:#2196f3,color:#000
    style A4 fill:#fff3e0,stroke:#ff9800,color:#000
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🌳 Future Attack Tree — CIA Pipeline Compromise

flowchart TD
    ROOT2["🎯 Compromise CIA Intelligence Data"]
    
    B1["⚔️ B1: Pipeline Source Compromise<br/>Probability: 8%"]
    B2["⚔️ B2: Cache/Storage Manipulation<br/>Probability: 12%"]
    B3["⚔️ B3: Schema Bypass<br/>Probability: 5%"]
    B4["⚔️ B4: AI Content Poisoning<br/>Probability: 15%"]
    
    B1_1["🔧 B1.1: CIA platform API manipulation"]
    B1_2["🔧 B1.2: Nightly fetch interception"]
    B2_1["🔧 B2.1: GitHub CDN cache poisoning"]
    B2_2["🔧 B2.2: S3 bucket manipulation"]
    B3_1["🔧 B3.1: Schema version mismatch exploit"]
    B3_2["🔧 B3.2: JSON Schema validation bypass"]
    B4_1["🔧 B4.1: Prompt injection via CIA data fields"]
    B4_2["🔧 B4.2: Cross-workflow data flow contamination"]
    
    ROOT2 --> B1
    ROOT2 --> B2
    ROOT2 --> B3
    ROOT2 --> B4
    B1 --> B1_1
    B1 --> B1_2
    B2 --> B2_1
    B2 --> B2_2
    B3 --> B3_1
    B3 --> B3_2
    B4 --> B4_1
    B4 --> B4_2
    
    style ROOT2 fill:#ffcdd2,stroke:#d32f2f,color:#000
    style B1 fill:#fff3e0,stroke:#ff9800,color:#000
    style B2 fill:#fff3e0,stroke:#ff9800,color:#000
    style B3 fill:#e8f5e9,stroke:#4caf50,color:#000
    style B4 fill:#fff3e0,stroke:#ff9800,color:#000
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🌳 Future Attack Tree — H3 Cloud IAM Compromise & Data Exfiltration

flowchart TD
    ROOT3["🎯 Exfiltrate / Tamper Authoritative AWS Data Stores"]

    C1["⚔️ C1: Identity Compromise<br/>Probability: 10%"]
    C2["⚔️ C2: Over-Scoped Role Abuse<br/>Probability: 9%"]
    C3["⚔️ C3: RAG / KB Poisoning<br/>Probability: 14%"]
    C4["⚔️ C4: Public API Abuse<br/>Probability: 18%"]

    C1_1["🔧 C1.1: Cognito credential stuffing / token replay"]
    C1_2["🔧 C1.2: CI/CD OIDC role assumption"]
    C2_1["🔧 C2.1: Lambda execution-role privilege escalation"]
    C2_2["🔧 C2.2: KMS key-policy misuse to decrypt at rest"]
    C3_1["🔧 C3.1: Poison Bedrock KB ingestion source"]
    C3_2["🔧 C3.2: SageMaker feature-store / training poisoning"]
    C4_1["🔧 C4.1: GraphQL depth/complexity cost-DoS"]
    C4_2["🔧 C4.2: IDOR on AppSync resolver / saved data"]

    ROOT3 --> C1
    ROOT3 --> C2
    ROOT3 --> C3
    ROOT3 --> C4
    C1 --> C1_1
    C1 --> C1_2
    C2 --> C2_1
    C2 --> C2_2
    C3 --> C3_1
    C3 --> C3_2
    C4 --> C4_1
    C4 --> C4_2

    style ROOT3 fill:#ffcdd2,stroke:#d32f2f,color:#000
    style C1 fill:#fff3e0,stroke:#ff9800,color:#000
    style C2 fill:#ffcdd2,stroke:#d32f2f,color:#000
    style C3 fill:#fff3e0,stroke:#ff9800,color:#000
    style C4 fill:#e3f2fd,stroke:#2196f3,color:#000
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🏗️ Future Asset Attack Surface Analysis

🗺️ New Attack Surface Inventory

📊 Future Data Flow Threat Analysis

flowchart LR
    subgraph EXTERNAL["🌐 External Sources"]
        RIKSDAG_API["Riksdag API"]
        CIA_API["CIA Platform"]
        EP_API["EU Parliament API"]
        LLM_API["LLM Provider"]
    end
    
    subgraph PIPELINE["⚙️ Data Pipeline"]
        FETCH["Nightly Fetch"]
        VALIDATE["Schema Validation"]
        TRANSFORM["Data Transform"]
        CACHE["Cache Layer"]
    end
    
    subgraph DELIVERY["📦 Content Delivery"]
        CDN["CloudFront CDN"]
        S3["S3 Static Assets"]
        PAGES["GitHub Pages"]
    end
    
    subgraph CLIENT["🖥️ Browser Client"]
        DASHBOARD["Interactive Dashboards"]
        REALTIME["Real-Time Feeds"]
        PROFILES["Politician Profiles"]
    end
    
    RIKSDAG_API -->|"🔴 T: Data interception"| FETCH
    CIA_API -->|"🔴 T: Source compromise"| FETCH
    EP_API -->|"🟡 S: API spoofing"| FETCH
    LLM_API -->|"🔴 T: Response manipulation"| TRANSFORM
    
    FETCH -->|"🟡 T: Pipeline tampering"| VALIDATE
    VALIDATE -->|"🟡 I: Validation bypass"| TRANSFORM
    TRANSFORM -->|"🟡 T: Cache poisoning"| CACHE
    
    CACHE -->|"🟡 T: CDN poisoning"| CDN
    CACHE --> S3
    CACHE --> PAGES
    
    CDN --> DASHBOARD
    CDN --> REALTIME
    CDN --> PROFILES
    
    style EXTERNAL fill:#e3f2fd,stroke:#2196f3,color:#000
    style PIPELINE fill:#fff3e0,stroke:#ff9800,color:#000
    style DELIVERY fill:#e8f5e9,stroke:#4caf50,color:#000
    style CLIENT fill:#f3e5f5,stroke:#9c27b0,color:#000
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🤖 AI/LLM Future Threat Analysis (OWASP LLM Top 10)

Future AI Workflow Expansion Threats

Mapping note: the table above uses the OWASP LLM Top-10 (2023/2024) IDs already established in this document. For Horizon 3 the same risks intensify as the platform moves from build-time MCP agents to managed Bedrock Agents, Knowledge Bases (RAG) and SageMaker models. The H3-specific intensification is summarised below.

🟠 H3 Bedrock / Agentic AI Threat Intensification

Future Multi-Workflow Orchestration Threat Matrix

🛰️ Political-Intelligence Capability Threat Analysis (Counter-AI · FIMI · Analytic Integrity)

Fielding the Political-Intelligence Capability Catalog (C1–C32) creates a new, high-value attack surface: an adversary who can corrupt the intelligence pipeline can launder a manipulated judgment through the platform's own credibility. These threats are distinct from generic web threats — they target analytic integrity, calibration, neutrality and provenance. The catalog's assurance pillar (C26–C32) exists specifically to counter them.

STRIDE per intelligence-capability component

Priority intelligence-integrity scenarios

Mapping to standards

Governing principle. Every intelligence-capability threat is met by an integrity-by-construction control, not by trust in the model: evidence anchoring, immutable calibration, provenance signing, neutrality-as-a-CI-gate, and a mandatory human-on-the-loop before any estimative product is published. See FUTURE_SECURITY_ARCHITECTURE.md for the corresponding controls.

🗳️ Democratic Integrity & Accountability Threats

The platform's mission is democratic transparency — any threat that subverts, distorts, or undermines public accountability is existential regardless of technical sophistication.

Riksdagsmonitor occupies a unique position: a neutral, AI-powered democratic-intelligence platform whose outputs influence citizen understanding of parliamentary proceedings. This creates a category of threats distinct from generic cybersecurity — threats to democratic processes, institutional trust, and political neutrality that no standard web-security framework adequately covers.

🏛️ Democratic Threat Landscape

flowchart TB
    subgraph DEMOCRATIC_THREATS["🗳️ Democratic Integrity Threats"]
        direction TB
        DT1["🎭 Neutrality Subversion<br/>Asymmetric framing across parties"]
        DT2["📊 Forecast Weaponization<br/>Biased predictions influence voters"]
        DT3["🗞️ Information Laundering<br/>Adversary narratives gain platform credibility"]
        DT4["🔇 Accountability Suppression<br/>Hide/downplay political misconduct"]
        DT5["⚡ Election-Window Exploitation<br/>Time-critical attacks during campaigns"]
        DT6["🌐 Cross-Border Influence<br/>Foreign interference via federation"]
    end

    subgraph DEMOCRATIC_CONTROLS["🛡️ Democratic Safeguards"]
        direction TB
        DC1["⚖️ Party-Symmetry CI Gate<br/>Automated neutrality enforcement"]
        DC2["📏 Calibration Ledger<br/>Immutable forecast accuracy tracking"]
        DC3["🔍 Source-Grade Floor<br/>Minimum evidence threshold"]
        DC4["👁️ Human-on-the-Loop<br/>Mandatory editorial oversight"]
        DC5["🚫 Election Cooling Period<br/>Restricted AI during election silence"]
        DC6["🤝 Federation Trust Boundaries<br/>Per-source integrity verification"]
    end

    subgraph DEMOCRATIC_ACTORS["👥 Democratic Threat Actors"]
        direction TB
        DA1["🏛️ State-Sponsored IO<br/>Foreign influence operations"]
        DA2["🎪 Domestic Political Operatives<br/>Partisan manipulation attempts"]
        DA3["🤖 Autonomous AI Agents<br/>Unintended bias amplification"]
        DA4["📰 Disinformation Networks<br/>Coordinated inauthentic behavior"]
    end

    DA1 --> DT3
    DA1 --> DT6
    DA2 --> DT1
    DA2 --> DT4
    DA3 --> DT1
    DA3 --> DT2
    DA4 --> DT3
    DA4 --> DT5

    DT1 -.->|mitigated by| DC1
    DT2 -.->|mitigated by| DC2
    DT3 -.->|mitigated by| DC3
    DT4 -.->|mitigated by| DC4
    DT5 -.->|mitigated by| DC5
    DT6 -.->|mitigated by| DC6

    style DEMOCRATIC_THREATS fill:#fff3e0,stroke:#e65100,color:#000
    style DEMOCRATIC_CONTROLS fill:#e8f5e9,stroke:#2e7d32,color:#000
    style DEMOCRATIC_ACTORS fill:#fce4ec,stroke:#c62828,color:#000
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Scenario F13: Gradual Neutrality Erosion via AI Drift

Scenario F14: Election-Period Forecast Manipulation

Scenario F15: Democratic Accountability Suppression

Scenario F16: Information Laundering via Platform Credibility

🔒 Privacy, GDPR & Data Protection Threats

Horizon 3 introduces the platform's first authenticated user tier — transforming privacy from a non-concern to a critical obligation.

🔐 Privacy Threat Landscape (H3)

flowchart LR
    subgraph USER_DATA["👤 H3 User Data at Risk"]
        UD1["🔍 Saved Searches<br/>Reveal political interests"]
        UD2["🔔 Alert Subscriptions<br/>Track political monitoring"]
        UD3["📊 Personalization<br/>Behavioral profile"]
        UD4["💬 Chat History<br/>Political questions asked"]
    end

    subgraph GDPR_THREATS["⚠️ Privacy Threats"]
        GT1["📋 Art. 9 Violation<br/>Special-category data exposure"]
        GT2["🕵️ Profiling Risk<br/>Political opinion inference"]
        GT3["🌍 Cross-Border Transfer<br/>Multi-region data residency"]
        GT4["🗑️ Erasure Complexity<br/>Right-to-be-forgotten across replicas"]
        GT5["🔗 Linkage Attack<br/>De-anonymization via query patterns"]
    end

    subgraph PRIVACY_CONTROLS["🛡️ Privacy Controls"]
        PC1["📝 DPIA Mandatory<br/>Before Cognito launch"]
        PC2["🔒 Data Minimization<br/>No opinions stored server-side"]
        PC3["🏠 EU Data Residency<br/>eu-west-1 primary"]
        PC4["⏱️ Auto-Purge<br/>Configurable retention"]
        PC5["🎭 Pseudonymization<br/>Query-level privacy"]
    end

    UD1 --> GT1
    UD2 --> GT2
    UD3 --> GT5
    UD4 --> GT1

    GT1 -.->|mitigated by| PC1
    GT2 -.->|mitigated by| PC2
    GT3 -.->|mitigated by| PC3
    GT4 -.->|mitigated by| PC4
    GT5 -.->|mitigated by| PC5

    style USER_DATA fill:#e3f2fd,stroke:#1565c0,color:#000
    style GDPR_THREATS fill:#ffebee,stroke:#c62828,color:#000
    style PRIVACY_CONTROLS fill:#e8f5e9,stroke:#2e7d32,color:#000
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Scenario F17: Political-Opinion Inference from Usage Patterns (H3)

Scenario F18: Cross-Region Data Residency Violation (H3)

🔗 Supply Chain & AI Model Governance Threats

The platform's AI supply chain extends beyond npm packages to foundation models, training data, and MCP tool ecosystems — each a potential vector for subtle, high-impact compromise.

🏭 AI Supply Chain Threat Model

flowchart TD
    subgraph AI_SUPPLY_CHAIN["🤖 AI Supply Chain Attack Surface"]
        direction TB
        SC1["🧠 Foundation Model Updates<br/>Behavioral regression on upgrade"]
        SC2["📦 MCP Server Dependencies<br/>Tool-level supply chain"]
        SC3["📚 Training Data Provenance<br/>Poisoned public datasets"]
        SC4["🔧 Prompt Template Integrity<br/>Workflow instruction tampering"]
        SC5["🌐 External API Dependencies<br/>Riksdag/SCB/IMF availability"]
    end

    subgraph GOVERNANCE_THREATS["⚖️ AI Governance Threats"]
        direction TB
        AG1["📜 EU AI Act Non-Compliance<br/>Regulatory classification change"]
        AG2["🎯 Model Behavior Drift<br/>Post-update output degradation"]
        AG3["🔄 Vendor Lock-In Exploitation<br/>AWS service discontinuation"]
        AG4["📊 Transparency Debt<br/>Unexplainable model decisions"]
    end

    subgraph SUPPLY_CONTROLS["🛡️ Supply Chain Controls"]
        direction TB
        SCC1["📌 Model Version Pinning<br/>+ regression testing"]
        SCC2["🔐 SLSA Level 3<br/>Build provenance"]
        SCC3["✅ Output Regression Suite<br/>Golden-set validation"]
        SCC4["📋 AI Model Cards<br/>Transparency documentation"]
        SCC5["🔄 Multi-Model Fallback<br/>Provider redundancy"]
    end

    SC1 --> AG2
    SC2 --> AG1
    SC3 --> AG2
    SC4 --> AG1
    SC5 --> AG3

    AG1 -.->|mitigated by| SCC4
    AG2 -.->|mitigated by| SCC1
    AG2 -.->|mitigated by| SCC3
    AG3 -.->|mitigated by| SCC5
    AG4 -.->|mitigated by| SCC4

    style AI_SUPPLY_CHAIN fill:#fff3e0,stroke:#e65100,color:#000
    style GOVERNANCE_THREATS fill:#fce4ec,stroke:#c62828,color:#000
    style SUPPLY_CONTROLS fill:#e8f5e9,stroke:#2e7d32,color:#000
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Scenario F19: Foundation Model Behavioral Regression

Scenario F20: EU AI Act Regulatory Reclassification

Scenario F21: MCP Tool Ecosystem Compromise

🌍 Geopolitical & Information Environment Threats

As Riksdagsmonitor expands to Nordic and EU parliaments, it enters a contested information environment where state-level actors actively seek to undermine democratic institutions.

🗺️ Geopolitical Threat Landscape

flowchart TB
    subgraph GEO_CONTEXT["🌍 Geopolitical Context (2026–2037)"]
        direction LR
        GC1["🇷🇺 Hybrid Warfare<br/>Information operations<br/>targeting Nordic democracies"]
        GC2["🇨🇳 Influence Operations<br/>United Front Work targeting<br/>diaspora communities"]
        GC3["🏴 Non-State FIMI<br/>Coordinated inauthentic<br/>behavior networks"]
        GC4["🤖 AI-Powered IO<br/>Synthetic media &<br/>automated propaganda"]
    end

    subgraph PLATFORM_EXPOSURE["📡 Platform Exposure Points"]
        direction LR
        PE1["🌐 14-Language Surface<br/>Each language = unique<br/>disinformation vector"]
        PE2["🔮 Forecast Outputs<br/>Election predictions as<br/>influence leverage"]
        PE3["🤝 Federation Trust<br/>Nordic/EU data mesh<br/>as attack vector"]
        PE4["📊 Credibility Capital<br/>Platform trust as<br/>laundering vehicle"]
    end

    subgraph GEO_DEFENSES["🛡️ Geopolitical Defenses"]
        direction LR
        GD1["🔍 FIMI Detection (C20)<br/>Early-warning indicators"]
        GD2["📏 Source Grading<br/>Confidence-floor enforcement"]
        GD3["🌐 Per-Language Review<br/>Native-speaker verification"]
        GD4["⚖️ Advisory-Only Output<br/>No accusatory attribution"]
    end

    GC1 --> PE3
    GC1 --> PE1
    GC2 --> PE1
    GC3 --> PE4
    GC4 --> PE2

    PE1 -.->|defended by| GD3
    PE2 -.->|defended by| GD2
    PE3 -.->|defended by| GD1
    PE4 -.->|defended by| GD4

    style GEO_CONTEXT fill:#ffebee,stroke:#b71c1c,color:#000
    style PLATFORM_EXPOSURE fill:#fff3e0,stroke:#e65100,color:#000
    style GEO_DEFENSES fill:#e8f5e9,stroke:#1b5e20,color:#000
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Language-Specific Threat Vectors

The 14-language surface creates asymmetric verification challenges: content in languages without native-speaker review capacity (Arabic, Chinese, Japanese, Korean, Hebrew) presents higher manipulation risk.

📊 Consolidated Future Security Control Requirements (Extended)

Additional Controls for Democratic & Privacy Threats

Extended STRIDE → Control Mapping (Democratic & Privacy)

📈 Extended Risk Assessment — Democratic & Governance Threats

🎯 Risk Heat Map — All Future Threats

quadrantChart
    title Future Threat Risk Heat Map
    x-axis "Low Likelihood" --> "High Likelihood"
    y-axis "Low Impact" --> "High Impact"
    quadrant-1 "🔴 Critical — Immediate Action"
    quadrant-2 "🟡 High — Plan Mitigation"
    quadrant-3 "🟢 Low — Monitor"
    quadrant-4 "🟡 Medium — Assess Controls"
    "Neutrality Erosion (F13)": [0.75, 0.95]
    "Election Manipulation (F14)": [0.60, 0.90]
    "Vote Data Tampering (F1)": [0.55, 0.92]
    "Agent Excessive Agency (F8)": [0.40, 0.90]
    "IAM Escalation (F7)": [0.35, 0.92]
    "RAG Poisoning (F5)": [0.55, 0.80]
    "Forecast Manipulation (F9)": [0.55, 0.80]
    "Information Laundering (F16)": [0.40, 0.78]
    "Accountability Suppression (F15)": [0.35, 0.85]
    "Model Regression (F19)": [0.55, 0.60]
    "MCP Compromise (F21)": [0.40, 0.72]
    "API Abuse (F10)": [0.55, 0.45]
    "Data Residency (F18)": [0.20, 0.65]
    "EU AI Act (F20)": [0.55, 0.55]
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🔄 Continuous Future Threat Assessment

Assessment Lifecycle for Future Features

Future Threat Monitoring KPIs

⚖️ Future Risk Assessment

Quantitative Risk Matrix — Future Threats

Scores split by horizon. H2 threats can materialise 2026–2027 while the platform is still static; H3 threats only become live once managed AWS services are provisioned (2027+).

📚 Related Documents

Riksdagsmonitor Documentation

• 🎯 Current Threat Model — Active production threat analysis
• 🏛️ Architecture — Current C4 architecture models
• 🔮 Future Architecture — Planned architecture evolution
• 🔐 Security Architecture — Current security controls
• 🔮 Future Security Architecture — Planned security enhancements
• 📊 Data Model — Political data entities and relationships
• 📊 Future Data Model — Enhanced data architecture plans
• 🔄 Flowchart — Business process and data flows
• 📈 State Diagram — System state transitions
• 🧠 Mindmap — System conceptual relationships
• 💼 SWOT — Strategic analysis and positioning
• 🔄 Workflows — CI/CD security workflows

Hack23 ISMS Policies (Public)

• 🎯 Threat Modeling Policy — ISMS threat modeling methodology
• 🔐 Secure Development Policy — SDLC security requirements
• 🏷️ Classification Framework — CIA triad business impact analysis
• 📉 Risk Register — Enterprise risk management
• 🤖 AI Policy — LLM application security requirements

Reference Implementations

• 🏛️ CIA Threat Model — Full-stack web application threat model
• 🎮 Black Trigram Future Threat Model — AWS serverless future threat analysis

📋 Document Control

📋 Document Owner: James Pether Sörling, CEO & CISO
📄 Version: 2.1
📅 Last Updated: 2026-06-02 (UTC)
✅ Approved by: James Pether Sörling, CEO
🔄 Review Cycle: Quarterly (Feb, May, Aug, Nov)
⏰ Next Review: 2026-09-02
🏢 Owner: Hack23 AB (Org.nr 5595347807)
📤 Distribution: Public
🏷️ Classification:

Revision History

Framework Compliance

🎯 Framework Alignment:

🌐 Evolving the Current IMF Threat Model — Future-State STRIDE Expansion

Baseline: the already-implemented IMF STRIDE coverage (T-IMF-01..07) lives in THREAT_MODEL.md §IMF. The rows below (T-IMF-F-01..08) add future-state threats that emerge when the runtime migrates to Lambda + Aurora — they extend the baseline rather than replace it.

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

STRIDE rows for IMF integration

Mapping to MITRE ATT&CK (data-source threats)

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

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

_{© 2008–2026 Hack23 AB (Org.nr 559534-7807) · Maintainer: James Pether Sörling, CISSP CISM}