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docs/SECURITY.md

Epic Tech AI Dev 2.0 - Security Design (Conceptual)

This document outlines the conceptual security architecture and considerations for the Epic Tech AI Dev 2.0 platform.

1. Core Security Principles

  • Defense in Depth: Multiple layers of security controls.
  • Principle of Least Privilege: Users and services operate with the minimum necessary permissions.
  • Secure by Default: Security features are enabled by default.
  • Zero Trust: Never trust, always verify. Authenticate and authorize every request.
  • Data Encryption: Encrypt sensitive data at rest and in transit.
  • Regular Audits & Monitoring: Continuously monitor for threats and audit system activity.
  • Secure Software Development Lifecycle (SSDLC): Integrate security into all phases of development.

2. Authentication (Conceptual)

  • User Authentication:
    • OAuth 2.0 / OpenID Connect: Preferred method, integrating with providers like GitHub, Google. This allows users to leverage existing trusted identities.
    • Multi-Factor Authentication (MFA): Enforced for all user accounts, especially those with administrative privileges.
  • Service-to-Service Authentication:
    • Internal AI agents (microservices) would authenticate with each other using methods like mutual TLS (mTLS) or short-lived JWTs/tokens issued by an internal identity provider.
  • API Authentication:
    • All API endpoints (REST/GraphQL) protected.
    • Clients (Web Dashboard, CLI, external integrations) use JWT Bearer tokens obtained via the OAuth flow.

3. Authorization (Conceptual)

  • Role-Based Access Control (RBAC):
    • Define roles (e.g., Admin, Developer, Viewer).
    • Assign permissions to roles (e.g., project:create, project:read, deployment:trigger, user:manage).
    • Users are assigned roles, inheriting permissions.
  • Attribute-Based Access Control (ABAC):
    • Could be used for more granular control, e.g., allowing a user to only access projects they own or are collaborated on.
  • Policy Enforcement Points: Authorization checks performed at the API Gateway and within individual services.

4. Secret Management (Conceptual)

  • Secure Vault: Use a dedicated secrets management solution (e.g., HashiCorp Vault, AWS Secrets Manager, Azure Key Vault).
  • Types of Secrets:
    • API keys for third-party services (GitHub, Vercel, Cloudflare, etc.).
    • Database credentials.
    • Encryption keys.
    • Internal service credentials.
  • Access Control: Strict access controls on who/what can retrieve secrets.
  • Rotation: Automated rotation policies for secrets where possible.
  • Dynamic Secrets: Generate short-lived credentials for services where supported.
  • No Hardcoded Secrets: Secrets must never be hardcoded in source code or configuration files. They should be injected at runtime from the vault or secure environment variables.

5. Data Security (Conceptual)

  • Encryption at Rest:
    • Databases (Project & State Management DB) should use transparent data encryption (TDE) or full-disk encryption.
    • Sensitive fields within the database (e.g., user-provided API keys before they are moved to a vault) should be encrypted at the application level.
    • Object storage (for build artifacts, logs) should have server-side encryption enabled.
  • Encryption in Transit:
    • TLS 1.2+ (preferably 1.3): Enforced for all external communication (User Interfaces to API Gateway, API Gateway to external platforms).
    • mTLS: For internal service-to-service communication within the cluster.
  • Data Minimization: Collect and store only the data essential for the platform's operation.
  • Input Validation & Sanitization:
    • Rigorously validate all user inputs (prompts, configuration values) to prevent injection attacks (XSS, SQLi, command injection).
    • Sanitize outputs displayed in the UI.

6. Infrastructure Security (Conceptual)

  • Network Security:
    • Firewalls, security groups, network segmentation to isolate services.
    • Private networks for internal communication.
    • DDoS protection for public-facing endpoints.
  • Container Security:
    • Scan container images for vulnerabilities.
    • Use minimal base images.
    • Run containers with least privilege (non-root users).
    • Implement runtime security monitoring for containers.
  • Secure Configurations: Harden OS, services, and applications.

7. Code Security & SSDLC (Conceptual)

  • Static Application Security Testing (SAST): Integrate into CI/CD pipelines to scan code for vulnerabilities.
  • Dynamic Application Security Testing (DAST): Periodically test running applications.
  • Dependency Scanning: Regularly scan third-party libraries for known vulnerabilities (e.g., npm audit, Snyk).
  • Code Reviews: Security-focused code reviews.
  • Threat Modeling: Identify potential threats and design mitigations.

8. Logging and Monitoring (Conceptual)

  • Comprehensive Audit Logs: Log all significant events, especially security-related ones (logins, permission changes, resource access, API calls).
  • Security Information and Event Management (SIEM): Aggregate and analyze logs to detect suspicious activity.
  • Alerting: Real-time alerts for security incidents or anomalies.
  • Intrusion Detection/Prevention Systems (IDS/IPS).

9. Incident Response Plan (Conceptual)

  • A documented plan for handling security incidents, including:
    • Preparation, Identification, Containment, Eradication, Recovery, Lessons Learned.

The security of Epic Tech AI Dev 2.0 is paramount. This conceptual design outlines key areas to address for a robust and secure platform. The current PoC server (server.js) is for demonstration only and does not implement these advanced security measures. Please confirm once you have added docs/SECURITY.MD.

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