Python
# Security Architecture Generator
def generate_security_architecture(system_type):
    return {
        "threat_model": analyze_attack_surface(system_type),
        "zero_trust": design_trust_boundaries(),
        "runtime_protection": create_sandbox_isolation(),
        "network_security": implement_mtls_mesh(),
        "ai_defense": deploy_prompt_firewall(),
        "governance": enforce_rbac_policies(),
        "monitoring": setup_forensic_logging()
    }

# Example: AI OS Security Stack
ai_os_security = {
    "authentication": "SPIFFE/SPIRE + Vault",
    "authorization": "OPA + RBAC",
    "network": "Istio mTLS + WireGuard",
    "runtime": "Falco + gVisor sandboxing",
    "ai_safety": "Semantic validation + output filtering",
    "monitoring": "ELK + Wazuh + CrowdSec"
}

Security Architecture Design Process:

Progress:

• 1. Threat Surface Analysis
• 2. Trust Boundary Definition
• 3. Zero Trust Implementation
• 4. Runtime Protection Design
• 5. Network Security Architecture
• 6. AI Security Controls
• 7. Governance Framework
• 8. Monitoring & Response

1. Threat Surface Analysis

Attack Vector Assessment:
- External API exposure
- Internal service communication
- AI model manipulation
- Container escape paths
- Privilege escalation routes
- Memory corruption risks
- Orchestration hijacking
- Supply chain vulnerabilities

2. Zero Trust Architecture

Trust Boundaries:
- Identity verification at every hop
- Network micro-segmentation
- Application-level encryption
- Continuous verification
- Least privilege access
- Device attestation

3. Runtime Protection Stack

Isolation Layers:
- Process sandboxing (gVisor/Kata)
- Memory protection (ASLR/DEP)
- Syscall filtering (seccomp-bpf)
- Resource quotas (cgroups)
- Network namespaces
- File system isolation

4. AI Security Framework

AI Defense Controls:
- Input sanitization
- Prompt injection detection
- Output validation
- Reasoning consistency checks
- Model integrity verification
- Training data poisoning detection

Example 1: Multi-Agent AI System Input: Distributed AI agent orchestration platform Output:

YAML
security_architecture:
  network_segmentation:
    ai_core: "10.1.0.0/24"
    user_runtime: "10.2.0.0/24"
    persistence: "10.3.0.0/24"
    admin: "10.4.0.0/24"
  
  authentication:
    method: "mTLS + SPIFFE"
    rotation: "24h"
    ca_hierarchy: "3-tier"
  
  ai_safety:
    prompt_firewall: "semantic_analysis"
    output_validation: "constitutional_ai"
    reasoning_check: "consistency_validation"

Example 2: Enterprise API Gateway Input: Public-facing AI service API Output:

YAML
api_security:
  waf_rules:
    - sql_injection_protection
    - xss_prevention
    - rate_limiting: "1000req/min"
    - geo_blocking: ["high_risk_countries"]
  
  authentication:
    oauth2_oidc: true
    jwt_validation: "RS256"
    token_rotation: "1h"
  
  network_protection:
    ddos_mitigation: "cloudflare"
    ssl_termination: "tls1.3_only"
    hsts_enforcement: true