widgettdc-api / source_intel /THREAT_MODEL.md
Kraft102's picture
fix: sql.js Docker/Alpine compatibility layer for PatternMemory and FailureMemory
5a81b95

Hack23 Logo

๐ŸŽฏ Citizen Intelligence Agency โ€” Threat Model

๐Ÿ›ก๏ธ Proactive Security Through Structured Threat Analysis
๐Ÿ” STRIDE โ€ข MITRE ATT&CK โ€ข CIA System Architecture โ€ข Public Transparency

Owner Version Effective Date Review Cycle

๐Ÿ“‹ Document Owner: CEO | ๐Ÿ“„ Version: 1.0 | ๐Ÿ“… Last Updated: 2025-09-18 (UTC)
๐Ÿ”„ Review Cycle: Annual | โฐ Next Review: 2026-09-18
๐Ÿท๏ธ Classification: Public (Open Civic Transparency Platform)


๐ŸŽฏ Purpose & Scope

Establish a comprehensive threat model for the Citizen Intelligence Agency (CIA) civic transparency platform (Swedish parliamentary/open data OSINT). This systematic threat analysis integrates multiple threat modeling frameworks to ensure proactive security through structured analysis.

๐ŸŒŸ Transparency Commitment

This threat model demonstrates ๐Ÿ›ก๏ธ cybersecurity consulting expertise through public documentation of advanced threat assessment methodologies, showcasing our ๐Ÿ† competitive advantage via systematic risk management and ๐Ÿค customer trust through transparent security practices.

โ€” Based on Hack23 AB's commitment to security through transparency and excellence

๐Ÿ“š Framework Integration

  • ๐ŸŽญ STRIDE per architecture element: Systematic threat categorization
  • ๐ŸŽ–๏ธ MITRE ATT&CK mapping: Advanced threat intelligence integration
  • ๐Ÿ—๏ธ Asset-centric analysis: Critical resource protection focus
  • ๐ŸŽฏ Scenario-centric modeling: Real-world attack simulation
  • โš–๏ธ Risk-centric assessment: Business impact quantification

๐Ÿ” Scope Definition

Included Systems:

  • ๐ŸŒ Web application (Vaadin/Spring framework)
  • ๐Ÿ”„ Data ingestion/import services
  • ๐Ÿ’พ PostgreSQL persistence + analytical views
  • ๐Ÿ” Authentication / session / audit subsystems
  • โ˜๏ธ AWS infrastructure (WAF, ALB, EC2, RDS, KMS, GuardDuty, Security Hub)

Out of Scope:

  • Third-party downstream consumers of published open dashboards (read-only usage)
  • External data source security (Parliament API, Election Authority, World Bank)

๐Ÿ”— Policy Alignment

Integrated with ๐ŸŽฏ Hack23 AB Threat Modeling Policy methodology and frameworks.


๐Ÿ“Š System Classification & Operating Profile

๐Ÿท๏ธ Security Classification Matrix

Dimension Level Rationale Business Impact
๐Ÿ” Confidentiality Low/Public Parliamentary, governmental, or open economic sources Trust Enhancement
๐Ÿ”’ Integrity High Analytical credibility & ranking accuracy critical Operational Excellence
โšก Availability Medium-High Public civic transparency; tolerates brief maintenance Revenue Protection

โš–๏ธ Regulatory & Compliance Profile

Compliance Area Classification Implementation Status
๐Ÿ“‹ Regulatory Exposure Low Mostly open data; minimal personal data (user accounts only)
๐Ÿ‡ช๐Ÿ‡บ CRA (EU Cyber Resilience Act) Low baseline Nonโ€“safety-critical civic analytics; maintains secure development controls
๐Ÿ“Š SLA Targets (Internal) 99.5% Single-region + resilience roadmap
๐Ÿ”„ RPO / RTO RPO โ‰ค 24h / RTO โ‰ค 4h Acceptable for civic analytics with daily refresh cadence

๐Ÿ’Ž Critical Assets & Protection Goals

๐Ÿ—๏ธ Asset-Centric Threat Analysis

Following Hack23 AB Asset-Centric Threat Modeling methodology:

Asset Category Why Valuable Threat Goals Key Controls Business Value
๐Ÿ“Š Analytical Integrity Public trust in political metrics Tampering, covert manipulation DB RBAC, immutable audit (Javers), CSP, WAF Trust Enhancement
๐Ÿง  Source Code Policy logic, ranking algorithms IP theft, malicious injection Private repo controls, dependency scanning, SLSA provenance Competitive Advantage
๐Ÿ”„ Import Pipelines Freshness & correctness Poisoned input, replay, API abuse Input validation, schema checks, rate limiting Operational Excellence
๐Ÿ‘ค User Accounts Abuse vector Credential stuffing, enumeration Login throttling, password policy, MFA optional path Risk Reduction
๐Ÿ”‘ Admin Role Elevated capability Privilege escalation Method-level @Secured, restricted session generation Security Excellence
โ˜๏ธ Infrastructure Config Security baseline Supply chain/manipulation Template versioning, provenance attestations Revenue Protection

๐Ÿ” Crown Jewel Analysis

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'primaryColor': '#e8f5e9',
      'primaryTextColor': '#2e7d32',
      'lineColor': '#4caf50',
      'secondaryColor': '#ffcdd2',
      'tertiaryColor': '#fff3e0'
    }
  }
}%%
flowchart TB
    subgraph CROWN_JEWELS["๐Ÿ’Ž Crown Jewels"]
        ANALYTICAL[๐Ÿ“Š Analytical Integrity<br/>Political Rankings & Metrics]
        SOURCE[๐Ÿง  Source Code<br/>Algorithms & Business Logic]
        DATA[๐Ÿ—„๏ธ Political Data<br/>Parliament & Election Records]
    end
    
    subgraph ATTACK_VECTORS["โš”๏ธ Primary Attack Vectors"]
        DATA_POISON[๐Ÿ’‰ Data Poisoning]
        CODE_INJECT[๐Ÿ’ป Code Injection]
        PRIVILEGE_ESC[โฌ†๏ธ Privilege Escalation]
        SUPPLY_CHAIN[๐Ÿ”— Supply Chain Attack]
    end
    
    subgraph THREAT_AGENTS["๐Ÿ‘ฅ Key Threat Agents"]
        NATION_STATE[๐Ÿ›๏ธ Nation-State Actors<br/>Political Interference]
        CYBER_CRIME[๐Ÿ’ฐ Cybercriminals<br/>Data Monetization]
        HACKTIVISTS[๐ŸŽญ Hacktivists<br/>Political Agenda]
        INSIDER[๐Ÿ‘ค Malicious Insider<br/>Privileged Access]
    end
    
    DATA_POISON --> ANALYTICAL
    CODE_INJECT --> SOURCE
    PRIVILEGE_ESC --> DATA
    SUPPLY_CHAIN --> SOURCE
    
    NATION_STATE --> DATA_POISON
    CYBER_CRIME --> CODE_INJECT
    HACKTIVISTS --> PRIVILEGE_ESC
    INSIDER --> SUPPLY_CHAIN
    
    style ANALYTICAL fill:#ffcdd2,stroke:#d32f2f,color:#000
    style SOURCE fill:#ffcdd2,stroke:#d32f2f,color:#000
    style DATA fill:#ffcdd2,stroke:#d32f2f,color:#000

๐ŸŒ Data Flow & Architecture Analysis

๐Ÿ›๏ธ Architecture-Centric STRIDE Analysis

Following Architecture-Centric Threat Modeling methodology:

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'primaryColor': '#e3f2fd',
      'primaryTextColor': '#01579b',
      'lineColor': '#0288d1',
      'secondaryColor': '#f1f8e9',
      'tertiaryColor': '#fff8e1'
    }
  }
}%%
flowchart TB
    subgraph TRUST_BOUNDARY_1["๐ŸŒ Internet/DMZ Trust Boundary"]
        EXT[(๐ŸŒ Public Open Data Sources)]
        USER[๐Ÿ‘ค Public/Registered Users]
    end
    
    subgraph TRUST_BOUNDARY_2["๐Ÿ›ก๏ธ AWS Security Boundary"]
        WAF[๐Ÿ›ก๏ธ AWS WAF]
        ALB[โš–๏ธ Application Load Balancer]
    end
    
    subgraph TRUST_BOUNDARY_3["๐Ÿ”’ Application Trust Boundary"]
        IMPORT[๐Ÿ”„ Import Services]
        VALID[โœ… Schema + Validation]
        APP[๐ŸŒ Spring/Vaadin App]
        AUTH[๐Ÿ” Security Module]
    end
    
    subgraph TRUST_BOUNDARY_4["๐Ÿ—„๏ธ Data Trust Boundary"]
        DB[(๐Ÿ’พ PostgreSQL Core + Views)]
        SESS[๐Ÿ”‘ Session Store/Audit]
        LOGS[(๐Ÿ“‹ Audit & Metrics)]
    end
    
    subgraph TRUST_BOUNDARY_5["โ˜๏ธ AWS Security Services"]
        GUARDDUTY[๐Ÿ” GuardDuty]
        SECURITYHUB[๐Ÿ›ก๏ธ Security Hub]
        KMS[๐Ÿ” AWS KMS]
    end
    
    EXT -->|๐ŸŽฏ T1: API Abuse| IMPORT
    USER -->|๐ŸŽฏ T2: Web Attacks| WAF
    WAF -->|๐ŸŽฏ T3: WAF Bypass| ALB
    ALB -->|๐ŸŽฏ T4: Load Balancer Exploit| APP
    IMPORT -->|๐ŸŽฏ T5: Data Poisoning| VALID
    VALID -->|๐ŸŽฏ T6: Validation Bypass| DB
    APP -->|๐ŸŽฏ T7: Application Exploit| AUTH
    AUTH -->|๐ŸŽฏ T8: Auth Bypass| SESS
    APP -->|๐ŸŽฏ T9: Log Injection| LOGS
    
    GUARDDUTY -.->|Monitors| ALB
    SECURITYHUB -.->|Aggregates| LOGS
    KMS -.->|Encrypts| DB
    
    style TRUST_BOUNDARY_1 fill:#ffebee,stroke:#f44336,stroke-width:3px,stroke-dasharray: 5 5
    style TRUST_BOUNDARY_2 fill:#fff3e0,stroke:#ff9800,stroke-width:3px,stroke-dasharray: 5 5
    style TRUST_BOUNDARY_3 fill:#e8f5e9,stroke:#4caf50,stroke-width:3px,stroke-dasharray: 5 5
    style TRUST_BOUNDARY_4 fill:#e3f2fd,stroke:#2196f3,stroke-width:3px,stroke-dasharray: 5 5
    style TRUST_BOUNDARY_5 fill:#f3e5f5,stroke:#9c27b0,stroke-width:3px,stroke-dasharray: 5 5

๐ŸŽญ STRIDE per Element Analysis

Element S T R I D E Notable Mitigations
๐ŸŒ Web Entry (WAF/ALB) IP spoof Header tamper Limited TLS downgrade L7 flood โ€” WAF managed rules, TLS policy
๐Ÿ–ฅ๏ธ Vaadin UI Session hijack DOM/script injection (XSS) Action denial Leakage via mis-render Render lock View bypass CSP, HSTS, security headers
โš™๏ธ Service Layer Impersonation Parameter tampering Log forging Data mapping leak Thread starvation Priv esc via service call Method @Secured, input canonicalization
๐Ÿ”„ Import Jobs Source spoof Payload corruption Replay abuse Poisoned dataset Batch backlog Elevated connector perms Source signature checks, schema validation
๐Ÿ’พ Database Connection spoof Row/column mod Transaction denial Full dump Connection exhaustion Role escalation Least-privilege roles, network isolation
๐Ÿ”‘ Session/Audit Token substitution Log injection Non-repudiation risk PII over-log Log flooding Log privilege misuse Structured logging, size limits
๐Ÿ”ง Build/CI Actor spoof (PR) Artifact tamper Tamper denial Secret exposure Runner exhaustion Escalated workflow perms Hardening, pin actions, attestations
๐Ÿ” Secrets Manager API misuse Secret overwrite Retrieval repudiation Broad read API flood Policy bypass IAM SCP, rotation, minimal scope

๐ŸŽ–๏ธ MITRE ATT&CK Framework Integration

๐Ÿ” Attacker-Centric Analysis

Following MITRE ATT&CK-Driven Analysis methodology:

Phase Technique ID CIA Context Control Detection
๐Ÿ” Initial Access Exploit Public-Facing App T1190 Web endpoints, API services WAF, patch cadence, input validation WAF logs, application monitoring
๐Ÿ” Initial Access Phishing for Credentials T1566 Admin/user login targeting Password policy, lockouts, awareness Failed login monitoring, email security
โšก Execution Command/Script Interpreter T1059 Limited server scripts Hardened AMI, no interactive shells Process monitoring, endpoint detection
๐Ÿ”„ Persistence Valid Accounts T1078 Compromised user accounts Login attempt throttling, MFA Account monitoring, behavioral analysis
โฌ†๏ธ Priv Esc Exploit for Priv Esc T1068 JVM/OS vulnerabilities Patch mgmt, Inspector scanning Vulnerability scanning, system monitoring
๐ŸŽญ Defense Evasion Obfuscated Files T1027 Malicious libraries SCA + SBOM diff, code review Static analysis, artifact scanning
๐Ÿ”‘ Credential Access Brute Force T1110 Login form attacks Throttling, IP/session caps Login attempt monitoring, rate limiting
๐Ÿ” Discovery Application Enumeration T1083 Public endpoint scanning Rate limits, minimal error detail Access pattern analysis, traffic monitoring
๐Ÿ“ค Exfiltration Exfil Over HTTPS T1041 Bulk data export via APIs Query limits, audit logging Data volume monitoring, unusual access patterns
๐Ÿ’ฅ Impact Data Manipulation T1565 Rankings/doc count tampering Integrity validation jobs, checksums Data integrity monitoring, change detection

๐Ÿ“Š ATT&CK Coverage Analysis

ATT&CK Coverage Covered Techniques

Comprehensive Coverage Tracking: This threat model provides systematic coverage analysis of MITRE ATT&CK techniques, identifying which tactics and techniques are relevant to the CIA platform's threat landscape.

๐ŸŽฏ Coverage Heat Map by Tactic

Tactic Covered Techniques Total Techniques Coverage % Status
๐Ÿ” Initial Access 4 22 18.2% High Priority
๐Ÿ’ฅ Impact 5 33 15.2% High Priority
๐Ÿ“ค Exfiltration 1 19 5.3% Medium Priority
โฌ†๏ธ Privilege Escalation 4 111 3.6% Medium Priority
โšก Execution 1 51 2.0% Low Priority
๐Ÿ” Discovery 1 49 2.0% Low Priority
๐Ÿ”„ Persistence 2 130 1.5% Low Priority
๐Ÿ”‘ Credential Access 1 67 1.5% Low Priority
๐ŸŽญ Defense Evasion 2 218 0.9% Low Priority
๐Ÿ”€ Lateral Movement 0 25 0.0% Not Applicable
๐Ÿ“ฆ Collection 0 41 0.0% Not Applicable
๐Ÿ“ก Command and Control 0 47 0.0% Not Applicable

Coverage Rationale: The CIA platform's 2.4% overall coverage reflects focused threat modeling for a civic transparency application with limited attack surface. Higher coverage in Initial Access (18.2%) and Impact (15.2%) aligns with primary threat vectors for public-facing platforms and data integrity concerns.

๐Ÿ›ก๏ธ Security Control to ATT&CK Mitigation Mapping

Comprehensive security controls are mapped to specific ATT&CK mitigations and techniques:

Security Control ATT&CK Mitigation Techniques Mitigated Implementation Status
AWS WAF M1050: Exploit Protection T1190 Implemented
Multi-Factor Authentication M1032: Multi-factor Authentication T1078, T1110 Planned
AWS CloudTrail M1047: Audit T1098 Implemented
VPC Security Groups M1030: Network Segmentation T1041 Implemented
Spring Security M1035: Limit Access T1068, T1078 Implemented
AWS GuardDuty M1047: Audit T1190, T1078 Implemented
Input Validation M1021: Restrict Web Content T1190, T1059, T1565 Implemented
AWS KMS Encryption M1041: Encrypt Sensitive Information T1041 Implemented

๐Ÿ—บ๏ธ ATT&CK Navigator Visualization

The MITRE ATT&CK Navigator provides interactive visualization of threat coverage. The CIA platform's coverage can be explored using the official ATT&CK Navigator tool.

Navigator Benefits:

  • โœ… Visual heat map of covered techniques across all tactics
  • โœ… Technique-by-technique coverage details
  • โœ… Control mapping and mitigation strategies
  • โœ… Priority assessment for threat coverage expansion

๐Ÿ“ˆ Coverage Enhancement Strategy

Current Focus: Initial Access and Impact tactics (highest risk for civic transparency)

Expansion Priorities:

  1. High Priority: Expand Discovery and Collection coverage (data protection)
  2. Medium Priority: Enhance Defense Evasion techniques (detection capabilities)
  3. Low Priority: C2 and Lateral Movement (limited internal network)

Not Applicable: Lateral Movement, C2, and Collection tactics have 0% coverage as CIA platform architecture (single-tier web application with isolated database) minimizes these attack vectors.

๐Ÿ”— Related Resources

๐ŸŒณ Attack Tree Analysis

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'primaryColor': '#ffebee',
      'primaryTextColor': '#c62828',
      'lineColor': '#f44336',
      'secondaryColor': '#e8f5e9',
      'tertiaryColor': '#fff3e0'
    }
  }
}%%
flowchart TD
    GOAL[๐ŸŽฏ Compromise CIA Platform<br/>Political Data Integrity]
    
    GOAL --> PATH1[๐Ÿšช External Web Attack]
    GOAL --> PATH2[๐Ÿ”’ Internal Access Abuse]
    GOAL --> PATH3[๐Ÿ”— Supply Chain Compromise]
    GOAL --> PATH4[โ˜๏ธ Infrastructure Attack]
    
    PATH1 --> EXT1[๐ŸŒ Web Application Exploit]
    PATH1 --> EXT2[๐Ÿ”Œ API Abuse]
    PATH1 --> EXT3[๐Ÿ“ง Social Engineering]
    
    EXT1 --> EXT1A[๐Ÿ” XSS/CSRF Attack]
    EXT1 --> EXT1B[๐Ÿ’‰ SQL Injection]
    EXT1A --> EXT1A1[๐ŸŽฏ Session Hijacking]
    EXT1B --> EXT1B1[๐Ÿ—„๏ธ Database Compromise]
    
    PATH2 --> INT1[๐Ÿ‘ค Privileged User Abuse]
    PATH2 --> INT2[๐Ÿ”‘ Credential Theft]
    INT1 --> INT1A[๐Ÿ“Š Data Manipulation]
    INT2 --> INT2A[โฌ†๏ธ Privilege Escalation]
    
    PATH3 --> SUP1[๐Ÿ“ฆ Dependency Poisoning]
    PATH3 --> SUP2[๐Ÿ”ง Build Tool Compromise]
    SUP1 --> SUP1A[๐Ÿฆ  Malicious Code Injection]
    SUP2 --> SUP2A[๐Ÿ—๏ธ Build Process Tampering]
    
    PATH4 --> INF1[โ˜๏ธ AWS Service Compromise]
    PATH4 --> INF2[๐Ÿ” Key Management Attack]
    INF1 --> INF1A[๐Ÿ—„๏ธ RDS Direct Access]
    INF2 --> INF2A[๐Ÿ”“ Encryption Bypass]
    
    style GOAL fill:#d32f2f,color:#fff
    style PATH1 fill:#ff5722,color:#fff
    style PATH2 fill:#ff9800,color:#fff
    style PATH3 fill:#ffc107,color:#000
    style PATH4 fill:#9c27b0,color:#fff

๐ŸŽฏ Priority Threat Scenarios

๐Ÿ”ด Critical Threat Scenarios

Following Risk-Centric Threat Modeling methodology:

# Scenario MITRE Tactic Impact Focus Likelihood Risk Key Mitigations Residual Action
1 ๐ŸŒ Web Application Compromise Initial Access Data integrity manipulation Medium Critical WAF, validation, ORM parameterization Add periodic data hash verification
2 ๐Ÿ”— Supply Chain Dependency Attack Initial Access Code integrity & confidentiality Medium Critical SBOM, pin SHAs, attestations Add provenance verification policy gate
3 ๐Ÿ”‘ Administrative Credential Compromise Credential Access System-wide access Low-Med High Lockouts, strong policy, IP rate limiting Enforce mandatory MFA for admin
4 ๐Ÿ—„๏ธ Database Exfiltration Exfiltration Political data confidentiality Low High Network isolation, least privilege Implement query anomaly detection
5 ๐Ÿ”„ Import Pipeline Data Poisoning Impact Analytical integrity Medium Medium Schema validation, duplicate detection Add source signature/etag validation
6 โšก Distributed Denial of Service Impact Service availability Medium Medium WAF rate limits, autoscaling planned Load test + capacity model update

โš–๏ธ Risk Heat Matrix

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'primaryColor': '#fff',
      'primaryTextColor': '#000',
      'lineColor': '#333'
    }
  }
}%%
quadrantChart
    title ๐ŸŽฏ CIA Platform Risk Heat Matrix
    x-axis Low Likelihood --> High Likelihood
    y-axis Low Impact --> High Impact
    quadrant-1 Monitor & Prepare
    quadrant-2 Immediate Action Required
    quadrant-3 Accept Risk
    quadrant-4 Mitigate & Control
    
    "๐ŸŒ Web App Compromise": [0.6, 0.9]
    "๐Ÿ”— Supply Chain Attack": [0.5, 0.95]
    "๐Ÿ”‘ Admin Credential Theft": [0.4, 0.8]
    "๐Ÿ—„๏ธ DB Exfiltration": [0.3, 0.75]
    "๐Ÿ”„ Data Poisoning": [0.6, 0.6]
    "โšก DDoS Attack": [0.7, 0.5]
    "๐ŸŽญ Social Engineering": [0.5, 0.4]
    "๐Ÿ’พ Backup Theft": [0.2, 0.7]
    "๐Ÿ” Information Disclosure": [0.4, 0.3]
    "๐Ÿšจ Insider Threat": [0.25, 0.85]

๐Ÿ›ก๏ธ Comprehensive Security Control Framework

๐Ÿ”’ Defense-in-Depth Architecture

Aligned with Security Architecture implementation:

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'primaryColor': '#e8f5e9',
      'primaryTextColor': '#2e7d32',
      'lineColor': '#4caf50',
      'secondaryColor': '#e3f2fd',
      'tertiaryColor': '#fff3e0'
    }
  }
}%%
flowchart TB
    subgraph PERIMETER["๐ŸŒ Perimeter Security"]
        DNS[๐ŸŒ Route 53 DNS Security]
        WAF[๐Ÿ›ก๏ธ AWS WAF Protection]
        DDOS[โšก AWS Shield DDoS]
    end
    
    subgraph NETWORK["๐Ÿ”’ Network Security"]
        VPC[๐Ÿ›๏ธ VPC Isolation]
        NACL[๐Ÿšช Network ACLs]
        SG[๐Ÿ›ก๏ธ Security Groups]
        TLS[๐Ÿ” TLS Encryption]
    end
    
    subgraph APPLICATION["๐Ÿ“ฑ Application Security"]
        AUTH[๐Ÿ”‘ Spring Security]
        RBAC[๐Ÿ‘ฅ Role-Based Access]
        INPUT[โœ… Input Validation]
        HEADERS[๐Ÿ“‹ Security Headers]
    end
    
    subgraph DATA["๐Ÿ—„๏ธ Data Security"]
        ENCRYPT[๐Ÿ” Encryption at Rest]
        TRANSIT[๐Ÿ”’ Encryption in Transit]
        BACKUP[๐Ÿ’พ Secure Backups]
        AUDIT[๐Ÿ“‹ Audit Logging]
    end
    
    subgraph MONITORING["๐Ÿ“Š Security Monitoring"]
        GUARDDUTY[๐Ÿ” GuardDuty]
        SECURITYHUB[๐Ÿ›ก๏ธ Security Hub]
        CLOUDWATCH[๐Ÿ“ˆ CloudWatch]
        INSPECTOR[๐Ÿ” Inspector]
    end
    
    DNS --> WAF
    WAF --> VPC
    VPC --> AUTH
    AUTH --> ENCRYPT
    
    DDOS -.-> WAF
    NACL -.-> SG
    RBAC -.-> INPUT
    TRANSIT -.-> AUDIT
    
    GUARDDUTY -.-> SECURITYHUB
    CLOUDWATCH -.-> INSPECTOR
    
    style PERIMETER fill:#ffcdd2,stroke:#d32f2f,stroke-width:2px
    style NETWORK fill:#fff3e0,stroke:#ff9800,stroke-width:2px
    style APPLICATION fill:#e8f5e9,stroke:#4caf50,stroke-width:2px
    style DATA fill:#e3f2fd,stroke:#2196f3,stroke-width:2px
    style MONITORING fill:#f3e5f5,stroke:#9c27b0,stroke-width:2px

๐ŸŽญ STRIDE โ†’ Control Mapping

STRIDE Category Example Threat Primary Control Secondary Control Monitoring
๐ŸŽญ Spoofing Credential stuffing Throttling + password policy MFA (admin), account lockout Failed login attempts, IP tracking
๐Ÿ”ง Tampering SQL/logic manipulation Parameterized queries, ORM WAF rules, input validation Database activity monitoring
โŒ Repudiation Action denial Immutable audit logs (Javers) Correlated session IDs Comprehensive audit trail
๐Ÿ“ค Information Disclosure Data exfiltration Network isolation, encryption Row-level access control Unusual query pattern detection
โšก Denial of Service Request flood WAF rate limiting Auto-scaling, resource sizing Traffic pattern analysis
โฌ†๏ธ Elevation of Privilege Privilege escalation Method @Secured annotations Separate admin role tokens Privilege usage monitoring

๐Ÿ”„ Continuous Validation & Assessment

๐ŸŽช Threat Modeling Workshop Process

Following Hack23 AB Workshop Framework:

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'primaryColor': '#e3f2fd',
      'primaryTextColor': '#01579b',
      'lineColor': '#0288d1',
      'secondaryColor': '#f1f8e9',
      'tertiaryColor': '#fff8e1'
    }
  }
}%%
flowchart LR
    PRE[๐Ÿ“‹ Pre-Workshop Prep] --> ENUM[๐ŸŽฏ Asset & Trust Boundary Enumeration]
    ENUM --> THREATS[๐Ÿ” Threat Identification<br/>STRIDE + MITRE ATT&CK]
    THREATS --> MAP[โš–๏ธ Risk & Scenario Mapping]
    MAP --> PLAN[๐Ÿ›ก๏ธ Mitigation & Control Plan]
    PLAN --> INTEG[๐Ÿ”ง Pipeline Integration]
    INTEG --> MON[๐Ÿ“Š Monitoring & Metrics]
    MON --> REVIEW[๐Ÿ”„ Annual / Event Review]
    REVIEW --> THREATS

๐Ÿ“… Assessment Lifecycle

Assessment Type Trigger Frequency Scope Documentation Update
๐Ÿ“… Comprehensive Review Annual cycle Annual Complete threat model Full document revision
๐Ÿ”„ Delta Assessment Architecture changes Per change Modified components Incremental updates
๐Ÿšจ Incident-Driven Security events As needed Affected systems Lessons learned integration
๐ŸŽฏ Threat Intelligence New attack patterns Quarterly High-risk scenarios MITRE ATT&CK updates

๐Ÿ“Š Comprehensive Threat Agent Analysis

๐Ÿ” Detailed Threat Actor Classification

Following Hack23 AB Threat Agent Classification methodology:

Threat Agent Category CIA-Specific Context MITRE Techniques Risk Level Political Motivation
๐Ÿ›๏ธ Nation-State Actors External Political interference, election influence Spearphishing, Data Manipulation Critical High - targeting political transparency
๐ŸŽญ Hacktivists External Political agenda promotion, transparency manipulation Defacement, DDoS High High - political platform targeting
๐Ÿ’ฐ Cybercriminals External Data monetization, political manipulation for hire Phishing, Ransomware High Medium - financial motivation
๐Ÿ”’ Accidental Insiders Internal Unintentional data corruption, misconfigurations Data Deletion, Misconfiguration Medium Low - no political intent
๐ŸŽฏ Malicious Insiders Internal Political bias injection, data manipulation Data Manipulation, Account Manipulation High High - political influence
๐Ÿค Third-Party Providers External Indirect access through service dependencies Supply Chain Compromise, Valid Accounts Medium Variable - depends on provider

๐ŸŒ Current Threat Landscape Integration

๐Ÿ“Š ENISA Threat Landscape 2024 Application

Implementing ENISA Threat Landscape 2024 specific to CIA platform:

ENISA Priority Threat Category CIA Platform Context Specific Scenarios Mitigation Strategy
1๏ธโƒฃ โšก Availability Threats DoS against civic transparency services Political period attacks, election interference Revenue Protection WAF + DDoS protection
2๏ธโƒฃ ๐Ÿ” Ransomware Parliamentary data encryption Critical voting period disruption Business Continuity Immutable backups + isolation
3๏ธโƒฃ ๐Ÿ“Š Data Threats Political data manipulation/theft Ranking algorithm tampering, voter influence Risk Reduction Integrity validation + audit
4๏ธโƒฃ ๐Ÿฆ  Malware System infiltration for data access Persistent political espionage Operational Excellence Endpoint protection + monitoring
5๏ธโƒฃ ๐ŸŽญ Social Engineering Admin credential theft for access Targeted phishing against civic platform staff Trust Enhancement Security awareness + MFA
6๏ธโƒฃ ๐Ÿ“ฐ Information Manipulation False political data injection Disinformation campaigns via platform Competitive Advantage Source validation + verification
7๏ธโƒฃ ๐Ÿ”— Supply Chain Dependency compromise for backdoor access Third-party library infiltration Partnership Value SBOM + provenance verification

๐ŸŽฏ Multi-Strategy Threat Modeling Implementation

๐Ÿ” Complete Framework Integration

Following Hack23 AB Comprehensive Threat Modeling Strategies:

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'primaryColor': '#e8f5e9',
      'primaryTextColor': '#2e7d32',
      'lineColor': '#4caf50',
      'secondaryColor': '#ffcdd2',
      'tertiaryColor': '#e1bee7'
    }
  }
}%%
mindmap
  root)๐ŸŽฏ CIA Threat Modeling Strategies(
    (๐ŸŽ–๏ธ Attacker-Centric)
      ๐Ÿ” MITRE ATT&CK Civic Context
      ๐ŸŒณ Political Attack Trees
      ๐ŸŽญ Nation-State Perspective
      ๐Ÿ“Š Election Interference Chains
      ๐Ÿ”— Democratic Process Graphs
    (๐Ÿ—๏ธ Asset-Centric)
      ๐Ÿ’ป Parliamentary Data Assets
      ๐Ÿท๏ธ Political Information Flows
      ๐Ÿ“‹ Democratic Process Protection
      ๐Ÿ” Civic Transparency Jewels
      ๐Ÿ’Ž Electoral Integrity Targets
    (๐Ÿ›๏ธ Architecture-Centric)
      ๐ŸŽญ STRIDE per Political Component
      ๐Ÿ”„ Civic Data Flow Diagrams
      ๐Ÿ—๏ธ Democratic System Decomposition
      ๐ŸŒ Government Trust Boundaries
      ๐Ÿ“Š Political Analysis Components
    (๐ŸŽฏ Scenario-Centric)
      ๐Ÿ“ Democratic Process Abuse
      ๐Ÿšจ Election Interference Cases
      ๐Ÿ‘ค Political Actor Threats
      ๐ŸŽฒ What-If Political Scenarios
      ๐Ÿ“– Civic Engagement Stories
    (โš–๏ธ Risk-Centric)
      ๐Ÿ“Š Democratic Impact Analysis
      ๐ŸŽฏ Political Threat Intelligence
      ๐Ÿ“ˆ Election Period Probability
      ๐Ÿ’ฐ Civic Trust Impact Focus
      ๐Ÿ” Political Vulnerability Correlation

๐ŸŽฏ Scenario-Centric Threat Modeling

๐Ÿ“ Democratic Process Abuse Analysis

Following Hack23 AB Scenario-Centric Modeling:

๐Ÿšจ Political Misuse Cases

Legitimate Democratic Use Case Political Misuse Case Attack Method Democratic Impact Civic Mitigation
๐Ÿ—ณ๏ธ Election Result Analysis ๐Ÿ“Š Vote Manipulation Perception False data injection, statistic skewing Public trust erosion in democracy Source verification, data provenance tracking
๐Ÿ‘ฅ Politician Performance Tracking ๐ŸŽฏ Character Assassination Selective data presentation, bias injection Political career damage, voter manipulation Balanced metrics, transparent methodology
๐Ÿ›๏ธ Parliamentary Process Monitoring ๐Ÿ“ฐ Legislative Process Interference Timeline manipulation, procedure misrepresentation Democratic process confusion Real-time validation, audit trails
๐Ÿ’ฐ Government Spending Transparency ๐Ÿ’ธ Financial Scandal Manufacturing Misleading financial correlation, context removal Government legitimacy questioning Context preservation, expert validation
๐Ÿ“ˆ Political Trend Visualization ๐Ÿ”ฎ Election Outcome Manipulation Predictive model bias, trend fabrication Voter behavior influence, election interference Statistical validation, methodology transparency

๐Ÿ‘ค Political Persona-Based Threat Analysis

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'primaryColor': '#f3e5f5',
      'primaryTextColor': '#6a1b9a',
      'lineColor': '#9c27b0',
      'secondaryColor': '#e8f5e9',
      'tertiaryColor': '#fff3e0'
    }
  }
}%%
flowchart TD
    subgraph PERSONAS["๐Ÿ‘ฅ Political Threat Personas"]
        FOREIGN_STATE[๐Ÿ›๏ธ Foreign State Actor<br/>High Resources, Strategic Patience]
        DOMESTIC_EXTREMIST[๐ŸŽญ Domestic Extremist<br/>High Motivation, Targeted Attacks]
        POLITICAL_OPERATIVE[๐ŸŽฏ Political Operative<br/>Medium Resources, Election Timing]
        CORPORATE_INFLUENCER[๐Ÿ’ผ Corporate Influencer<br/>Financial Resources, Policy Focus]
    end
    
    subgraph METHODS["โš”๏ธ Political Attack Methods"]
        DISINFORMATION[๐Ÿ“ฐ Disinformation Campaigns]
        DATA_MANIPULATION[๐Ÿ“Š Data Manipulation]
        TIMING_ATTACKS[โฐ Strategic Timing Attacks]
        PERCEPTION_WARFARE[๐Ÿง  Perception Warfare]
    end
    
    subgraph TARGETS["๐ŸŽฏ Democratic Targets"]
        ELECTION_INTEGRITY[๐Ÿ—ณ๏ธ Election Integrity]
        POLITICAL_TRUST[๐Ÿค Political Trust]
        DEMOCRATIC_PROCESS[๐Ÿ›๏ธ Democratic Process]
        CIVIC_ENGAGEMENT[๐Ÿ‘ฅ Civic Engagement]
    end
    
    FOREIGN_STATE --> DISINFORMATION
    FOREIGN_STATE --> ELECTION_INTEGRITY
    
    DOMESTIC_EXTREMIST --> DATA_MANIPULATION
    DOMESTIC_EXTREMIST --> POLITICAL_TRUST
    
    POLITICAL_OPERATIVE --> TIMING_ATTACKS
    POLITICAL_OPERATIVE --> DEMOCRATIC_PROCESS
    
    CORPORATE_INFLUENCER --> PERCEPTION_WARFARE
    CORPORATE_INFLUENCER --> CIVIC_ENGAGEMENT
    
    style FOREIGN_STATE fill:#ffcdd2
    style DOMESTIC_EXTREMIST fill:#fff3e0
    style POLITICAL_OPERATIVE fill:#e8f5e9
    style CORPORATE_INFLUENCER fill:#e3f2fd

๐ŸŽฒ Political What-If Scenario Planning

๐Ÿ” Scenario 1: Pre-Election Platform Compromise

  • What if: The CIA platform is compromised 30 days before a major election?
  • Attack Path: Initial Access โ†’ Data Manipulation โ†’ Public Misinformation โ†’ Election Influence
  • Democratic Impact: Voter confusion, election legitimacy questions, democratic trust erosion
  • Detection: Real-time data integrity monitoring, anomaly detection, public verification systems
  • Response: Emergency transparency protocols, independent verification, rapid correction procedures

๐Ÿ” Scenario 2: Parliamentary Crisis Information Warfare

  • What if: During a government crisis, the platform becomes a disinformation vector?
  • Attack Path: Social Engineering โ†’ Insider Access โ†’ Content Manipulation โ†’ Media Amplification
  • Democratic Impact: Political instability amplification, public disorder, institutional damage
  • Detection: Editorial workflow monitoring, multi-source verification, expert validation panels
  • Response: Crisis communication protocols, expert fact-checking, transparent correction processes

๐Ÿ” Scenario 3: Long-term Democratic Erosion Campaign

  • What if: A sustained, subtle campaign gradually erodes trust in democratic institutions?
  • Attack Path: Persistent Access โ†’ Gradual Bias Introduction โ†’ Normalized Distortion โ†’ Trust Degradation
  • Democratic Impact: Slow democratic norm erosion, reduced civic participation, institutional weakening
  • Detection: Long-term trend analysis, bias detection algorithms, public trust metrics
  • Response: Regular methodology audits, transparent bias correction, public engagement initiatives

โš–๏ธ Enhanced Risk-Centric Analysis

๐Ÿ“Š Political Impact Quantification

Following Risk-Centric Threat Modeling:

๐Ÿ›๏ธ Democratic Impact Assessment Matrix

Threat Scenario Probability Democratic Impact Public Trust Impact Electoral Impact Civic Risk Score
๐Ÿ—ณ๏ธ Election Period Data Manipulation 25% Critical Very High Critical 9.5/10
๐Ÿ›๏ธ Parliamentary Process Interference 20% High High Medium 7.8/10
๐Ÿ‘ฅ Politician Reputation Attacks 30% Medium High High 8.2/10
๐Ÿ’ฐ Government Spending Manipulation 15% Medium Medium Low 5.9/10
๐Ÿ“Š Statistical Methodology Attacks 10% High Very High Medium 7.1/10

๐Ÿ“ˆ Political Threat Intelligence Integration

Intelligence Source Update Frequency Democratic Relevance Integration Method CIA Platform Application
๐Ÿ›๏ธ Election Authority Alerts Real-time 10/10 Direct API integration Election period threat escalation
๐Ÿ“ฐ Media Monitoring Hourly 8/10 Content analysis integration Misinformation pattern detection
๐ŸŒ Social Media Threat Feeds Real-time 9/10 API aggregation Coordinated attack detection
๐Ÿ” Parliamentary Security Bulletins Daily 7/10 Manual review integration Government target awareness
๐ŸŽฏ Political Cyber Threat Intelligence Weekly 9/10 Threat modeling updates Political actor capability assessment

๐ŸŽช Advanced Threat Modeling Workshop Framework

๐Ÿ“‹ Political Platform-Specific Preparation

Following Hack23 AB Workshop Framework with civic transparency adaptations:

๐ŸŽฏ CIA-Specific Workshop Scope

  • ๐Ÿ›๏ธ Democratic Process Mapping: Parliamentary procedures, election cycles, government transparency requirements
  • ๐Ÿ“Š Political Data Sensitivity: Ranking methodologies, bias detection, source verification
  • ๐Ÿ—ณ๏ธ Electoral Period Considerations: High-risk timeframes, attack surface expansion, emergency procedures
  • ๐Ÿ‘ฅ Civic Stakeholder Impact: Citizens, politicians, media, researchers, government bodies

๐Ÿ‘ฅ Political Platform Team Assembly

  • ๐Ÿ›๏ธ Civic Technology Expert: Democratic process digitization, transparency platform expertise
  • ๐Ÿ“Š Political Data Scientist: Bias detection, statistical validation, methodology transparency
  • ๐Ÿ›ก๏ธ Democracy Security Specialist: Election security, political threat landscape, civic platform protection
  • ๐Ÿ“ฐ Media Relations Coordinator: Public communication, misinformation response, transparency communication
  • โš–๏ธ Legal/Compliance Officer: Election law compliance, data protection, transparency regulations

๐Ÿ“Š Political Context Analysis Framework

๐Ÿ›๏ธ Democratic Process Security Assessment:

  • How might different political actors attempt to manipulate the platform?
  • What are the critical democratic periods requiring enhanced security?
  • How do we maintain neutrality while protecting against political manipulation?
  • What transparency measures prevent and detect bias injection?

๐Ÿ—ณ๏ธ Electoral Integrity Evaluation:

  • How could the platform influence electoral outcomes inappropriately?
  • What safeguards prevent pre-election manipulation campaigns?
  • How do we ensure equal treatment across political parties and candidates?
  • What emergency procedures exist for election period incidents?

๐Ÿ“Š Political Data Protection Analysis:

  • How do we prevent selective or biased data presentation?
  • What validation ensures ranking methodology integrity?
  • How do we protect against gradual algorithmic bias introduction?
  • What transparency measures allow public verification of fairness?

๐Ÿ“Š Political Threat Catalog Framework

๐Ÿ›๏ธ Democracy-Specific Threat Documentation

Each political threat entry includes democratic impact assessment per Threat Catalog Framework:

๐Ÿ”ด Critical Democratic Threats

๐Ÿ—ณ๏ธ Election Period Information Manipulation
  • ๐ŸŽฏ Political Tactic: Electoral Interference via Information Manipulation
  • ๐Ÿ”ง MITRE Technique: Data Manipulation (T1565)
  • ๐Ÿ›๏ธ Democratic Component: Electoral process transparency and integrity
  • ๐Ÿ“ Threat Description: Coordinated manipulation of political data during critical election periods to influence voter behavior
  • ๐Ÿ‘ฅ Threat Agent: Nation-state actors, domestic political operatives, foreign election interference groups
  • ๐Ÿ” CIA at Risk: Integrity (democratic process), Availability (public access), Confidentiality (premature results)
  • ๐Ÿ”‘ AAA Controls: Authentication for data modification, Authorization for critical period access, Accounting for all changes
  • ๐ŸŽญ STRIDE Attribute: Tampering, Information Disclosure, Repudiation
  • ๐Ÿ›ก๏ธ Security Measures: Multi-source validation, immutable audit trails, real-time integrity monitoring, emergency response protocols
  • โšก Priority: Critical
  • ๐Ÿ›๏ธ Democratic Impact: Direct election integrity threat, voter manipulation, democratic legitimacy undermining
  • โ“ Assessment Questions: Are election period protections sufficient? Can real-time manipulation be detected? Are emergency response procedures tested?
๐Ÿ›๏ธ Parliamentary Data Corruption for Policy Influence
  • ๐ŸŽฏ Political Tactic: Legislative Process Manipulation
  • ๐Ÿ”ง MITRE Technique: Supply Chain Compromise (T1195)
  • ๐Ÿ›๏ธ Democratic Component: Parliamentary transparency and legislative tracking
  • ๐Ÿ“ Threat Description: Long-term infiltration to gradually corrupt parliamentary data and influence policy perception
  • ๐Ÿ‘ฅ Threat Agent: Corporate influence groups, foreign policy interference, special interest organizations
  • ๐Ÿ” CIA at Risk: Integrity (legislative records), Confidentiality (sensitive political information)
  • ๐Ÿ”‘ AAA Controls: Authentication for data source access, Authorization for parliamentary data modification, Accounting for all legislative record changes
  • ๐ŸŽญ STRIDE Attribute: Tampering, Spoofing, Elevation of Privilege
  • ๐Ÿ›ก๏ธ Security Measures: Source verification protocols, parliamentary API security, data provenance tracking, expert validation panels
  • โšก Priority: Critical
  • ๐Ÿ›๏ธ Democratic Impact: Policy manipulation, legislative process corruption, public policy misunderstanding
  • โ“ Assessment Questions: Are parliamentary data sources verified? Can gradual corruption be detected? Are policy experts involved in validation?

๐Ÿ”„ Continuous Democratic Validation

๐Ÿ“… Political Context Assessment Lifecycle

Assessment Type Political Trigger Frequency Democratic Scope Public Transparency
๐Ÿ—ณ๏ธ Election Period Assessment Election announcement Per election cycle Complete platform security posture Enhanced transparency reporting
๐Ÿ›๏ธ Parliamentary Session Assessment Parliamentary term start/major crisis Per session/as needed Legislative tracking systems Public methodology reviews
๐Ÿ‘ฅ Political Actor Assessment New government formation Per government change Stakeholder access and bias detection Stakeholder engagement reports
๐Ÿ“Š Methodology Assessment Algorithm/ranking changes Per significant change Data processing and presentation Public methodology documentation
๐ŸŒ Democratic Landscape Assessment Major democratic events globally Quarterly Threat landscape and best practices International cooperation reports

๐Ÿ›๏ธ Democratic Validation Pipeline Integration

Democratic Control Layer Public Evidence Transparency Enforcement Democratic Threat Coverage
๐Ÿ” Political Bias Detection Public methodology documentation Open algorithm explanations Gradual bias injection, partisan manipulation
๐Ÿ“Š Source Verification Public source listings + verification status Open data provenance Information manipulation, false data injection
๐Ÿ›๏ธ Democratic Process Validation Public parliamentary procedure mapping Open process documentation Legislative process manipulation
๐Ÿ—ณ๏ธ Election Period Protection Public security posture reporting Open threat response documentation Election interference, voter manipulation
๐Ÿ‘ฅ Stakeholder Balance Verification Public engagement reports Open stakeholder consultation logs Partisan capture, interest group manipulation
๐Ÿ“ˆ Democratic Impact Assessment Public impact evaluations Open democratic health metrics Democratic erosion, civic disengagement

๐ŸŽฏ Democratic Threat Modeling Maturity

๐Ÿ“ˆ Civic Platform Maturity Framework

Following Hack23 AB Maturity Levels with democratic adaptations:

๐ŸŸข Level 1: Democratic Foundation

  • ๐Ÿ›๏ธ Basic Democratic Architecture: Core civic transparency documentation with basic bias detection
  • ๐Ÿ—ณ๏ธ Election Period Awareness: Basic election security protocols and enhanced monitoring
  • ๐Ÿ‘ฅ Stakeholder Identification: Key democratic actors mapped with influence assessment
  • ๐Ÿ“Š Transparency Baseline: Public methodology documentation and basic verification
  • ๐Ÿ›ก๏ธ Democratic Security Controls: Basic protections against political manipulation

๐ŸŸก Level 2: Democratic Process Integration

  • ๐Ÿ“… Electoral Cycle Integration: Threat assessment aligned with democratic calendar
  • ๐Ÿ“ Political Context Documentation: Enhanced threat models including political scenarios
  • ๐Ÿ”ง Democratic Tool Integration: Bias detection tools and democratic validation systems
  • ๐Ÿ”„ Civic Engagement Tracking: Public participation in threat identification and validation

๐ŸŸ  Level 3: Democratic Analysis Excellence

  • ๐Ÿ” Comprehensive Political STRIDE: Systematic threat categorization for all democratic processes
  • โš–๏ธ Democratic Risk Assessment: Political impact, civic trust, and electoral integrity criteria
  • ๐Ÿ›ก๏ธ Political Mitigation Strategies: Comprehensive controls for democratic threats
  • ๐ŸŽ“ Civic Security Education: Public education on democratic platform security

๐Ÿ”ด Level 4: Advanced Democratic Intelligence

  • ๐ŸŒ Advanced Political Modeling: Real-world political attack simulations and democratic war gaming
  • ๐Ÿ“Š Continuous Democratic Monitoring: Real-time political threat landscape integration
  • ๐Ÿ“ˆ Democratic Health Metrics: Comprehensive civic engagement and trust measurement
  • ๐Ÿ”„ Public Validation Sessions: Community-driven threat identification and mitigation validation

๐ŸŸฃ Level 5: Democratic Innovation Leadership

  • ๐Ÿ”ฎ Proactive Democratic Protection: Emerging political threat anticipation and countermeasures
  • ๐Ÿค– AI-Enhanced Democratic Security: Machine learning for bias detection and political manipulation identification
  • ๐Ÿ“Š Global Democratic Intelligence: International democratic security collaboration and best practice sharing
  • ๐Ÿ”ฌ Predictive Democratic Analytics: Advanced modeling for democratic health and threat prediction

๐ŸŒŸ Democratic Security Best Practices

๐Ÿ›๏ธ Civic Platform Security Principles

๐Ÿ—ณ๏ธ Electoral Integrity by Design

  • ๐Ÿ” Transparent Methodology: All ranking and analysis methodologies publicly documented and verifiable
  • โš–๏ธ Political Neutrality Enforcement: Systematic bias detection and correction mechanisms
  • ๐Ÿ“Š Multi-Source Validation: Cross-verification of political data from multiple independent sources
  • ๐Ÿ›ก๏ธ Election Period Protection: Enhanced security during critical democratic periods

๐Ÿ‘ฅ Democratic Participation Security

  • ๐Ÿค Stakeholder Engagement: Regular consultation with democratic actors on security concerns
  • ๐Ÿ“ข Public Validation: Community-driven verification of platform neutrality and accuracy
  • ๐Ÿ” Open Source Transparency: Public access to security methodologies and threat assessments
  • ๐Ÿ“ˆ Civic Trust Measurement: Regular assessment of public confidence in platform integrity

๐Ÿ”„ Continuous Democratic Improvement

  • โšก Proactive Political Threat Detection: Early identification of emerging democratic manipulation techniques
  • ๐Ÿ“Š Evidence-Based Security: Data-driven democratic security decisions with public accountability
  • ๐Ÿค International Cooperation: Collaboration with global democratic transparency organizations
  • ๐Ÿ’ก Innovation in Democratic Security: Leading development of new civic platform protection methods

๐Ÿ“‹ Document Control:
โœ… Approved by: James Pether Sรถrling, CEO - Hack23 AB
๐Ÿ“ค Distribution: Public
๐Ÿท๏ธ Classification: Confidentiality: Public Integrity: High Availability: Moderate
๐Ÿ“… Effective Date: 2025-09-18
โฐ Next Review: 2026-09-18
๐ŸŽฏ Framework Compliance: ISO 27001 NIST CSF 2.0 CIS Controls AWS Well-Architected Hack23 Threat Modeling