This document describes the security model, authentication, authorization, and best practices for securing PolicyBind deployments.

PolicyBind is designed with security as a core principle:

1. Defense in Depth: Multiple layers of security controls
2. Least Privilege: Minimal permissions by default
3. Fail Secure: Deny access when in doubt
4. Audit Everything: Complete audit trail of all operations
5. Secure by Default: Secure configuration out of the box

For server-to-server communication, use API keys:

# Configuration
server:
  require_auth: true
  api_key_header: X-API-Key

Using API keys:

curl -X POST https://policybind.example.com/v1/enforce \
  -H "X-API-Key: your-api-key-here" \
  -H "Content-Type: application/json" \
  -d '{"provider": "openai", "model": "gpt-4"}'

API key requirements:

• Minimum 32 characters
• Cryptographically random
• Stored as secure hashes (Argon2)
• Rotated regularly (90 days recommended)

For end-user or application authentication, use PolicyBind tokens:

curl -X POST https://policybind.example.com/v1/enforce \
  -H "Authorization: Bearer pb_live_xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{"provider": "openai", "model": "gpt-4"}'

Token security features:

• Cryptographically random generation
• Secure hash storage (plaintext never stored)
• Expiration enforcement
• Permission scoping
• Revocation support

Tokens are hashed before storage:

# Tokens are never stored in plaintext
# Only the hash is stored in the database
token_hash = argon2.hash(token_value)

The plaintext token is only shown once at creation time. It cannot be recovered.

The HTTP API uses role-based access control:

Configure roles per API key:

api_keys:
  - key_hash: "..."
    name: monitoring-service
    roles: [viewer]

  - key_hash: "..."
    name: deployment-automation
    roles: [operator]

  - key_hash: "..."
    name: security-admin
    roles: [admin]

Tokens can be scoped to specific permissions:

permissions:
  # Model restrictions
  allowed_models:
    - gpt-3.5-turbo
    - gpt-4
  denied_models:
    - dall-e-*

  # Use case restrictions
  allowed_use_cases:
    - code-review
    - documentation

  # Data classification restrictions
  allowed_data_classifications:
    - public
    - internal

  # Budget limits
  budget_limit: 100.0
  budget_period: monthly

  # Rate limits
  rate_limit:
    requests_per_minute: 30

  # Time restrictions
  valid_hours: [9, 17]  # 9 AM - 5 PM only

PolicyBind ships with secure defaults:

# Enforcement defaults
enforcement:
  default_action: deny  # Deny unknown requests
  require_classification: true  # Require data classification
  log_all_requests: true  # Audit everything

# Server defaults
server:
  require_auth: true  # Require authentication
  tls_enabled: true  # Require TLS

# Token defaults
tokens:
  max_expiry_days: 365  # Maximum token lifetime
  require_expiry: true  # Tokens must expire

Always use TLS in production:

server:
  tls_enabled: true
  tls_cert_file: /etc/policybind/tls/cert.pem
  tls_key_file: /etc/policybind/tls/key.pem
  tls_min_version: "1.2"
  tls_cipher_suites:
    - TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384
    - TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256

Never store secrets in configuration files:

# BAD - secret in file
database:
  password: mysecretpassword

# GOOD - environment variable reference
database:
  password_env: POLICYBIND_DB_PASSWORD

# GOOD - file reference
database:
  password_file: /run/secrets/db-password

Use secret management systems:

• Kubernetes Secrets
• HashiCorp Vault
• AWS Secrets Manager
• Azure Key Vault

PolicyBind logs all security-relevant events:

Structured JSON logs for security analysis:

{
  "timestamp": "2024-01-15T10:30:00.123Z",
  "event_type": "enforcement",
  "request_id": "req-abc123",
  "user_id": "user-001",
  "source_ip": "10.0.1.50",
  "action": "enforce",
  "decision": "DENY",
  "reason": "Model not approved for department",
  "model": "gpt-4",
  "department": "marketing",
  "applied_rules": ["deny-marketing-gpt4"],
  "latency_ms": 0.5
}

Configure log retention for compliance:

audit:
  retention_days: 365  # 1 year minimum for compliance
  archive_enabled: true
  archive_path: /archive/policybind/
  archive_compression: gzip

Enable tamper-evident logging:

audit:
  integrity_enabled: true
  hash_algorithm: sha256
  signature_key_file: /etc/policybind/audit-signing-key.pem

Each log entry includes a hash chain:

{
  "entry_hash": "sha256:abc123...",
  "previous_hash": "sha256:xyz789...",
  "signature": "..."
}

PolicyBind uses parameterized queries exclusively:

# SAFE - parameterized query
cursor.execute(
    "SELECT * FROM tokens WHERE subject = ?",
    (subject,)
)

# NEVER - string interpolation (would be rejected in code review)
# cursor.execute(f"SELECT * FROM tokens WHERE subject = '{subject}'")

All database operations go through the repository layer which enforces parameterization.

All inputs are validated at system boundaries:

# Request fields are validated
class AIRequest:
    provider: str  # Must be non-empty
    model: str  # Must be non-empty
    user_id: str  # Must be non-empty
    # ... validated on construction

Policies are validated before loading:

• YAML syntax checking
• Schema validation
• Semantic validation
• No code execution from policies

All API inputs are validated:

• Type checking
• Length limits
• Pattern validation
• Sanitization

Protect against abuse with rate limiting:

server:
  rate_limit_enabled: true
  rate_limit_requests: 10000
  rate_limit_window_seconds: 60
  rate_limit_by: ip  # or api_key

  # Per-endpoint limits
  rate_limits:
    "/v1/enforce": 1000
    "/v1/tokens": 100
    "/v1/policies/reload": 10

server:
  max_request_size_bytes: 1048576  # 1 MB
  request_timeout_seconds: 30
  max_connections: 1000

database:
  max_query_time_seconds: 10
  max_result_rows: 10000

policies:
  max_rules_per_policy: 1000
  max_policy_size_bytes: 1048576
  max_include_depth: 10

PolicyBind does not protect against:

• Insider threats with admin access: Admins can change policies
• Physical access to database: Use disk encryption
• Compromised AI providers: PolicyBind controls access, not AI behavior
• Side-channel attacks: Standard cloud hardening required

PolicyBind assumes:

1. The server infrastructure is secure
2. TLS is properly configured
3. Secrets are managed securely
4. Administrators are trusted
5. The operating system is hardened

1. Detection: Automated alerts or manual discovery
2. Containment: Revoke tokens, suspend deployments
3. Investigation: Review audit logs
4. Remediation: Update policies, patch vulnerabilities
5. Recovery: Restore normal operations
6. Lessons learned: Update procedures

For critical security events:

# Enable emergency lockdown
policybind emergency lockdown --reason "Security incident"

# This:
# - Denies all requests
# - Revokes all tokens
# - Suspends all deployments
# - Notifies administrators

# Disable lockdown
policybind emergency unlock --ticket SEC-2024-001

PolicyBind supports compliance with:

• EU AI Act: Risk classification, documentation, audit trails
• NIST AI RMF: Governance, mapping, measurement, management
• SOC 2: Security controls, availability, confidentiality
• GDPR: Data protection, right to explanation
• HIPAA: Healthcare data handling

Export compliance evidence:

# Generate compliance report
policybind report compliance \
  --framework eu-ai-act \
  --period 2024-Q1 \
  --output compliance-report.pdf

# Export audit evidence
policybind audit export \
  --since 2024-01-01 \
  --until 2024-03-31 \
  --format json \
  --signed \
  --output evidence-package.json

• TLS enabled with strong ciphers
• Authentication required for all endpoints
• API keys rotated every 90 days
• Tokens have appropriate expiry
• Rate limiting configured
• Audit logging enabled
• Log retention configured
• Backups encrypted
• Secrets in secret manager
• Firewall rules configured
• Monitoring and alerting set up

1. Principle of least privilege: Grant minimal permissions
2. Defense in depth: Multiple security layers
3. Regular audits: Review access and policies
4. Incident readiness: Have response procedures
5. Security updates: Keep dependencies updated
6. Training: Ensure team understands security model

# Create API key
policybind api-key create \
  --name "ci-cd-pipeline" \
  --roles operator \
  --expires 90d

# Rotate API key
policybind api-key rotate \
  --name "ci-cd-pipeline"

# Revoke API key
policybind api-key revoke \
  --name "ci-cd-pipeline" \
  --reason "Employee departure"

# Create scoped token
policybind token create \
  --subject "data-science-team" \
  --expires 30d \
  --budget 500 \
  --models "gpt-4,gpt-3.5-turbo"

# Audit token usage
policybind token audit \
  --subject "data-science-team" \
  --since 2024-01-01

# Revoke compromised token
policybind token revoke \
  --id tok-abc123 \
  --reason "Potential compromise"

Report security vulnerabilities to: security@policybind.example.com

Include:

• Description of the vulnerability
• Steps to reproduce
• Potential impact
• Suggested fix (if any)

We will acknowledge within 24 hours and provide updates on remediation.