⚠️ LEARNING PROJECT / PROOF OF CONCEPT ⚠️

This is a proof-of-concept voting system built to demonstrate an idea and share it with the community.

Important Context:

• Built by a non-developer as a learning project ("vibe coding")
• Demonstrates architecture concepts, not production-ready code
• Has not undergone professional security audits
• Should not be used in real elections without complete rewrite by professionals

Current Status: Functional demo sharing an idea with the security community.

Goal: Share this concept so others can learn from it, improve it, or use it as inspiration. If this can serve as a foundation for something better, that's the objective.

1. Reporting Vulnerabilities
2. Security Architecture
3. Threat Model
4. Known Limitations
5. Security Assumptions
6. Out of Scope
7. Roadmap to Production

We welcome security researchers to review this system and report vulnerabilities.

For non-critical issues:

• Open a GitHub Issue with label security
• Email: [your-email-here] with subject "SECURITY: [brief description]"

For critical vulnerabilities:

• Email: [your-email-here] with subject "CRITICAL SECURITY"
• Include:
  • Detailed description of the vulnerability
  • Steps to reproduce
  • Potential impact
  • Proof of concept (if available)
  • Your recommended remediation

Response Timeline:

• Best effort response - this is a learning project by a non-developer
• Issues will be documented but fixes may take time or require community help
• Community contributions for security fixes are strongly encouraged

Disclosure Policy:

• This is a public learning project - all issues are welcome to be disclosed publicly
• Credit will be given to security researchers (unless anonymity requested)
• Feel free to fork and fix - no need to wait for me!

Contributors who responsibly disclose security issues will be listed here:

• Be the first!

1. Zero PII Storage

   • No personally identifiable information stored
   • Voter identity not linkable to vote choice
   • Only cryptographic hashes stored

2. Hash-Based Authentication

   • SHA-256 hashing: hash = SHA-256(NAS|CODE|LAW_ID)
   • Offline hash generation (air-gapped security model)
   • Pre-computed hash database prevents vote fabrication

3. Duplicate Detection

   • Redis SET tracking voted hashes
   • Duplicate attempt counter per hash
   • Audit trail of all duplicate attempts

4. Complete Audit Trail

   • PostgreSQL vote_audit table (immutable)
   • Every vote logged with timestamp
   • Full traceability without compromising anonymity

5. Separation of Concerns

   • Stateless validation workers (horizontal scaling)
   • Message queue buffering (RabbitMQ)
   • No single point of failure

┌─────────────┐
│   Voter     │
│ (NAS+CODE)  │
└──────┬──────┘
       │ HTTPS (production)
       ▼
┌─────────────────┐
│ Ingestion API   │ ← Rate limiting
│   (FastAPI)     │ ← Input validation
└──────┬──────────┘
       │ Internal network
       ▼
┌─────────────────┐
│   RabbitMQ      │ ← Message queue isolation
└──────┬──────────┘
       │
       ▼
┌─────────────────┐
│ Validation      │ ← Hash verification (Redis)
│   Workers       │ ← Duplicate check (Redis)
└──────┬──────────┘
       │
       ├──→ PostgreSQL (audit log)
       └──→ RabbitMQ (aggregation queue)

Hashing:

• Algorithm: SHA-256
• Purpose: Voter authentication without PII
• Implementation: Python hashlib

TLS/SSL (Production):

• Currently: Not implemented in demo
• Production requirement: TLS 1.3
• Certificate management: Let's Encrypt (recommended)

1. External Attackers

   • Motivation: Disrupt election, manipulate results
   • Capabilities: Network access, DDoS, injection attacks
   • Likelihood: High during actual elections

2. Malicious Insiders

   • Motivation: Manipulate votes, leak voter data
   • Capabilities: Database access, system knowledge
   • Likelihood: Low (requires multi-party validation)

3. State-Level Adversaries

   • Motivation: Election interference
   • Capabilities: Advanced persistent threats, zero-days
   • Likelihood: Medium for national elections

4. Opportunistic Script Kiddies

   • Motivation: Chaos, reputation
   • Capabilities: Automated tools, known exploits
   • Likelihood: High if publicly accessible

Attack: Submit fake votes with fabricated hashes

• Mitigation: Offline hash generation, pre-validated hash database in Redis
• Status: ✅ Implemented
• Residual Risk: Hash generation process must be secured

Attack: Replay valid votes (duplicate submission)

• Mitigation: Redis voted_hashes SET, duplicate detection
• Status: ✅ Implemented
• Residual Risk: Redis compromise could disable deduplication

Attack: Modify vote in transit

• Mitigation: TLS encryption (production), message integrity checks
• Status: ⚠️ TLS not implemented in demo
• Residual Risk: High without TLS

Attack: Overwhelm API with requests

• Mitigation: Rate limiting, RabbitMQ queue buffering, CDN (production)
• Status: ⚠️ Basic rate limiting, no DDoS protection
• Residual Risk: High - needs WAF and DDoS mitigation

Attack: Exhaust database connections

• Mitigation: Connection pooling, worker scaling limits
• Status: ⚠️ Connection pooling implemented, no hard limits
• Residual Risk: Medium - needs connection limits

Attack: Fill RabbitMQ queue (queue flooding)

• Mitigation: Queue size limits, message TTL, dead letter queues
• Status: ❌ Not implemented
• Residual Risk: High - unlimited queue growth possible

Attack: Steal hash database from Redis

• Mitigation: Network isolation, Redis authentication, encryption at rest
• Status: ⚠️ No Redis authentication in demo
• Residual Risk: High - Redis exposed without auth

Attack: Access PostgreSQL vote audit logs

• Mitigation: Database authentication, encrypted connections, audit logging
• Status: ⚠️ Basic auth, no encrypted connections
• Residual Risk: Medium - needs TLS for DB connections

Attack: Link voter identity to vote choice

• Mitigation: Zero PII storage, hash-based system prevents linkage
• Status: ✅ Implemented
• Residual Risk: Low - correlation attacks still possible with metadata

Attack: SQL injection

• Mitigation: Parameterized queries, ORM usage (SQLAlchemy)
• Status: ✅ Implemented
• Residual Risk: Low - needs regular audits

Attack: NoSQL injection (Redis commands)

• Mitigation: Input validation, Redis command whitelisting
• Status: ⚠️ Basic validation
• Residual Risk: Medium - needs stricter validation

Attack: Code injection via message payloads

• Mitigation: JSON schema validation, message sanitization
• Status: ⚠️ Basic validation
• Residual Risk: Medium - needs comprehensive input validation

Attack: Compromise Docker containers

• Mitigation: Minimal base images, no root users, security scanning
• Status: ⚠️ Standard images, needs hardening
• Residual Risk: High - container security not prioritized

Attack: Exploit dependencies

• Mitigation: Dependency scanning, automated updates, minimal dependencies
• Status: ❌ No automated scanning
• Residual Risk: High - needs Dependabot/Snyk

Attack: Kubernetes cluster compromise (production)

• Mitigation: RBAC, network policies, pod security policies
• Status: ❌ Not implemented (demo is Docker Compose)
• Residual Risk: N/A for demo, critical for production

Attack: Malware on voter device

• Mitigation: None (outside system scope)
• Status: ❌ No endpoint security
• Residual Risk: High - voter devices assumed trusted

Attack: Man-in-the-Middle (MITM)

• Mitigation: TLS, certificate pinning (mobile apps)
• Status: ❌ TLS not implemented in demo
• Residual Risk: Critical - all traffic potentially interceptable

1. No TLS/SSL in Demo

   • All traffic unencrypted
   • Credentials/votes visible to network observers
   • Impact: Critical vulnerability
   • Remediation: Implement TLS 1.3 before any real deployment

2. No Redis Authentication

   • Redis accessible without password
   • Hash database exposed
   • Impact: Critical vulnerability
   • Remediation: Redis AUTH, network isolation

3. No DDoS Protection

   • Basic rate limiting insufficient
   • No WAF, no CDN
   • Impact: System can be overwhelmed
   • Remediation: Cloudflare/AWS Shield, rate limiting per IP/subnet

4. Hash Generation Process Not Secured

   • Hash generation script has no security controls
   • No verification of hash uniqueness
   • Impact: Potential for duplicate or invalid hashes
   • Remediation: Hardware Security Module (HSM) for production

5. No Intrusion Detection

   • No monitoring for suspicious activity
   • No alerting on anomalies
   • Impact: Attacks may go undetected
   • Remediation: IDS/IPS, SIEM integration

6. Limited Input Validation

   • Basic format checks only
   • No comprehensive sanitization
   • Remediation: JSON Schema validation, input sanitization library

7. No Encrypted Connections to Databases

   • PostgreSQL connections unencrypted
   • Remediation: SSL/TLS for all DB connections

8. No Container Security Scanning

   • No vulnerability scanning of Docker images
   • Remediation: Trivy, Snyk, Clair integration

9. No Automated Dependency Scanning

   • Vulnerable dependencies may exist
   • Remediation: Dependabot, Snyk, safety checks

10. No Security Audit Logs

    • System events not logged comprehensively
    • Remediation: Centralized logging (ELK stack), audit trail

11. Trust Assumptions

    • Assumes voter devices are secure
    • Assumes hash generation process is trusted
    • Assumes network infrastructure is benign (in demo)

12. Scalability vs Security Trade-offs

    • Stateless workers = easier scaling, harder to detect coordinated attacks
    • Message queue buffering = resilience, but potential message loss

13. Anonymity vs Auditability

    • Cannot trace vote to voter (by design)
    • Makes forensic investigation difficult
    • Trade-off: privacy vs accountability

This system operates under the following assumptions:

1. Network Security

   • Production: Private network or VPN for inter-service communication
   • Demo: Assumes localhost/trusted network

2. Physical Security

   • Servers are physically secure
   • No unauthorized physical access to infrastructure

3. Operator Trust

   • System administrators are trusted
   • No insider threat from operators (mitigated by multi-party controls in production)

4. Offline Hash Generation

   • Hashes generated in secure, air-gapped environment
   • Hash generation process follows strict protocol
   • No hash leakage before distribution

5. Hash Distribution

   • Voters receive NAS+CODE via secure channel (postal mail, secure portal)
   • Distribution process prevents interception

6. Voter Device Security

   • Voter devices free from malware
   • Voters use trusted browsers/applications
   • No keyloggers or screen recorders on voter devices

7. Voter Behavior

   • Voters keep credentials confidential
   • Voters do not share NAS+CODE combinations
   • Voters verify they're on correct voting website (phishing awareness)

8. Hash Algorithm Security

   • SHA-256 remains cryptographically secure
   • No practical collision or preimage attacks

9. Randomness

   • Hash generation uses cryptographically secure random number generators
   • No predictable patterns in NAS or CODE generation

The following are explicitly outside the scope of this system's security model:

1. Voter Coercion

   • System cannot prevent coercion or vote selling
   • Voters could be forced to vote in presence of coercer
   • Mitigation: Requires legal and social measures, not technical

2. Device Compromise

   • Voter device security is voter's responsibility
   • System assumes endpoint security

3. Phishing Attacks

   • Voters may be phished to fake voting sites
   • Mitigation: User education, domain verification

4. Social Engineering

   • Attackers may trick voters into revealing credentials
   • Mitigation: User awareness training

5. Advanced Persistent Threats (APTs)

   • No defenses against state-level zero-day exploits
   • Requires ongoing security research and hardening

6. Quantum Computing Attacks

   • SHA-256 vulnerable to quantum attacks (theoretical)
   • Post-quantum cryptography not implemented

7. Supply Chain Attacks

   • No verification of dependency integrity
   • Needs software bill of materials (SBOM)

Honest Assessment: As a learning project by a non-developer, this code needs significant work to be production-ready. Below is what security professionals would need to implement:

If someone wants to fork this and make it production-ready:

• TLS/SSL Implementation

  • TLS 1.3 for all external connections
  • Certificate management automation
  • HSTS headers

• Redis Security

  • AUTH password
  • Network isolation (internal network only)
  • Encrypted connections (TLS)

• Database Security

  • SSL/TLS for PostgreSQL connections
  • Strong authentication
  • Connection encryption

• DDoS Protection

  • WAF implementation (Cloudflare, AWS WAF)
  • Rate limiting per IP/subnet
  • CDN for static assets

• Input Validation

  • JSON Schema validation
  • Comprehensive sanitization
  • Security audit of all endpoints

• Professional Security Audit - Essential before any real use
• Penetration Testing - By qualified security professionals
• Code Review - By experienced developers
• Compliance Assessment - Electoral standards, data protection laws
• Complete Rewrite - Likely needed for production deployment

This is a learning project. If you're a security professional or experienced developer and see potential:

• Fork it and improve it
• Rewrite parts that need it
• Use it as inspiration for a better system
• Share improvements back with the community

I'm still learning and may not be able to implement complex security fixes quickly, but I'll do my best to:

• Document issues
• Review pull requests
• Share knowledge gained
• Support community efforts

The goal is to advance the idea, not to be the sole maintainer.

• Basic functional testing
• Load testing (8M votes capacity)
• Security testing (pending)

Before Production:

1. Penetration Testing

   • External penetration test
   • Internal penetration test
   • Social engineering assessment

2. Vulnerability Assessment

   • Automated vulnerability scanning
   • Manual code review
   • Dependency audit

3. Security Chaos Engineering

   • Simulated attacks (red team)
   • Failure injection
   • Recovery testing

4. Compliance Testing

   • Electoral standards verification
   • Data protection audit
   • Accessibility audit

Project Creator: David Marleau (learning developer, not security expert)

Honest Disclosure:

• I'm still learning and may not be able to fix complex security issues quickly
• Community contributions and forks are highly encouraged
• If you're a security professional, please help improve this or build something better

Response Approach:

• Will respond to issues as able
• May need community help for complex fixes
• Contributions and pull requests very welcome
• Feel free to fork and improve without waiting

This security policy was inspired by:

• OWASP Secure Coding Practices
• DEF CON Voting Village Reports
• NIST Cybersecurity Framework

This SECURITY.md document is licensed under CC BY 4.0.

Last Updated: November 2024 Version: 1.0 Status: Draft - Seeking Community Review