Comprehensive security guidelines for AI applications. Implement defense-in-depth strategies with encryption, authentication, and compliance frameworks.
Zero-trust authentication
End-to-end encryption
Model protection
Continuous monitoring
# MCPCodex Security Best Practices Checklist
## 🔐 Authentication & Authorization
- [ ] Implement multi-factor authentication (MFA)
- [ ] Use strong password policies (12+ chars, complexity)
- [ ] Implement OAuth 2.0 + PKCE for client authentication
- [ ] Use JWT tokens with short expiration times
- [ ] Implement proper session management
- [ ] Use role-based access control (RBAC)
- [ ] Implement API key rotation policies
- [ ] Enable audit logging for authentication events
## 🛡️ Data Protection
- [ ] Encrypt data at rest using AES-256
- [ ] Use TLS 1.3 for data in transit
- [ ] Implement end-to-end encryption for sensitive data
- [ ] Use secure key management (AWS KMS, HashiCorp Vault)
- [ ] Implement data classification policies
- [ ] Use secure backup and recovery procedures
- [ ] Implement data retention policies
- [ ] Use secure data disposal methods
## 🔍 AI Model Security
- [ ] Implement model input validation
- [ ] Use prompt injection prevention
- [ ] Implement output filtering and sanitization
- [ ] Use model versioning and integrity checks
- [ ] Implement context isolation between users
- [ ] Use secure model hosting and deployment
- [ ] Implement model access controls
- [ ] Monitor for adversarial attacks
## 🌐 Infrastructure Security
- [ ] Use infrastructure as code (IaC)
- [ ] Implement network segmentation
- [ ] Use Web Application Firewall (WAF)
- [ ] Implement DDoS protection
- [ ] Use secure container images
- [ ] Implement vulnerability scanning
- [ ] Use security monitoring and SIEM
- [ ] Implement incident response procedures
## 📝 Compliance & Governance
- [ ] Implement GDPR compliance measures
- [ ] Use SOC 2 Type II controls
- [ ] Implement PCI DSS for payment data
- [ ] Use HIPAA controls for healthcare data
- [ ] Implement data privacy controls
- [ ] Use regular security assessments
- [ ] Implement security training programs
- [ ] Use third-party security audits
# Secure MCPCodex Configuration
# config/security.yaml
security:
# Authentication Configuration
authentication:
provider: "oauth2"
multi_factor:
enabled: true
providers: ["totp", "sms", "email"]
session:
timeout: 3600 # 1 hour
secure_cookies: true
same_site: "strict"
jwt:
algorithm: "RS256"
expiration: 900 # 15 minutes
refresh_expiration: 86400 # 24 hours
issuer: "mcpcodex.com"
audience: "mcpcodex-api"
# API Security
api:
rate_limiting:
enabled: true
requests_per_minute: 60
burst_size: 10
cors:
allowed_origins: ["https://app.mcpcodex.com"]
allowed_methods: ["GET", "POST", "PUT", "DELETE"]
allowed_headers: ["Authorization", "Content-Type"]
credentials: true
headers:
x_frame_options: "DENY"
x_content_type_options: "nosniff"
x_xss_protection: "1; mode=block"
strict_transport_security: "max-age=31536000; includeSubDomains"
# AI Model Security
ai_models:
input_validation:
max_length: 8192
content_filtering: true
prompt_injection_detection: true
output_filtering:
pii_detection: true
harmful_content_filter: true
bias_detection: true
context_isolation:
user_separation: true
tenant_separation: true
session_isolation: true
# Data Protection
data:
encryption:
at_rest:
algorithm: "AES-256-GCM"
key_rotation: 90 # days
in_transit:
tls_version: "1.3"
cipher_suites: ["TLS_AES_256_GCM_SHA384"]
classification:
levels: ["public", "internal", "confidential", "restricted"]
default_level: "internal"
retention:
logs: 90 # days
user_data: 2555 # 7 years
ai_models: 365 # 1 year
# Infrastructure Security
infrastructure:
network:
ingress_whitelist: ["10.0.0.0/8", "192.168.0.0/16"]
egress_restrictions: true
containers:
read_only_filesystem: true
no_root_user: true
resource_limits: true
monitoring:
security_events: true
anomaly_detection: true
threat_intelligence: true
# Compliance Settings
compliance:
gdpr:
enabled: true
data_retention_period: 2555 # days
right_to_be_forgotten: true
soc2:
enabled: true
audit_logging: true
access_reviews: true
pci_dss:
enabled: false
tokenization: true
cardholder_data_encryption: true
#!/bin/bash
# MCPCodex Security Hardening Script
set -e
echo "🔐 MCPCodex Security Hardening"
echo "=============================="
# Security audit
echo "🔍 Running security audit..."
mcpcodex security audit --comprehensive
# Vulnerability scanning
echo "🛡️ Scanning for vulnerabilities..."
mcpcodex scan vulnerabilities --container-images --dependencies --code --infrastructure
# SSL/TLS configuration
echo "🔒 Configuring SSL/TLS..."
mcpcodex security tls --version 1.3 --hsts-enabled --certificate-auto-renewal
# Authentication hardening
echo "👤 Hardening authentication..."
mcpcodex auth harden --mfa-required --password-complexity --session-timeout 3600 --jwt-rotation
# API security
echo "🌐 Securing APIs..."
mcpcodex api secure --rate-limiting --cors-strict --input-validation --output-filtering
# Data encryption
echo "🔐 Configuring encryption..."
mcpcodex encryption setup --at-rest AES-256-GCM --in-transit TLS-1.3 --key-rotation-days 90
# Network security
echo "🌐 Configuring network security..."
mcpcodex network secure --firewall-rules --intrusion-detection --ddos-protection
# Container security
echo "📦 Securing containers..."
mcpcodex container harden --non-root-user --read-only-filesystem --resource-limits --security-scanning
# Monitoring and alerting
echo "📊 Setting up security monitoring..."
mcpcodex monitoring security --siem-integration --anomaly-detection --threat-intelligence --incident-response
# Compliance checks
echo "📋 Running compliance checks..."
mcpcodex compliance check --gdpr --soc2 --iso27001 --generate-report
echo "✅ Security hardening completed!"
Comprehensive security assessment.
mcpcodex security audit
Scan for security vulnerabilities.
mcpcodex scan vulnerabilities
Configure encryption settings.
mcpcodex encryption setup
Real-time security monitoring.
mcpcodex monitor security
Build secure AI applications with defense-in-depth security strategies.