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xvnpw / fabric-agent-action-examples

Example of fabric-agent-action usage
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Threat model using fabric and react agent #6

Open xvnpw opened 1 day ago

xvnpw commented 1 day ago

Architecture

This document outlines the architecture of the AI Nutrition-Pro application.

Containers Context diagram

C4Container
    title Container diagram for AI Nutrition-Pro

    Container_Boundary(c0, "AI Nutrition-Pro") {
        Container(api_gateway, "API Gateway", "Kong", "Authentication of clients, filtering of input, rate limiting")
        Container(app_control_plane, "Web Control Plane", "Golang, AWS Elastic Container Service", "Provides control plane to onboard and manage clients, configuration and check billing data")
        ContainerDb(control_plan_db, "Control Plane Database", "Amazon RDS", "Stores all data related to control plan, tenants, billing")
        Container(backend_api, "API Application", "Golang, AWS Elastic Container Service", "Provides AI Nutrition-Pro functionality via API")
        ContainerDb(api_db, "API database", "Amazon RDS", "Stores dietitian' content samples, request and responses to LLM.")
        Person(admin, "Administrator", "Administrator of AI Nutrition-Pro application")
    }

    System_Ext(mealApp, "Meal Planner", "Application to create diets by dietitians")

    System_Ext(chatgpt, "ChatGPT-3.5", "LLM")

    Rel(mealApp, api_gateway, "Uses for AI content generation", "HTTPS/REST")
    Rel(api_gateway, backend_api, "Uses for AI content generation", "HTTPS/REST")
    Rel(admin, app_control_plane, "Configure system properties")
    Rel(backend_api, chatgpt, "Utilizes ChatGPT for LLM-featured content creation", "HTTPS/REST")

    Rel(app_control_plane, control_plan_db, "read/write data", "TLS")
    Rel(backend_api, api_db, "read/write data", "TLS")

External systems and persons

Name Type Description Responsibilities
Meal Planner application External system, web application One of many Meal Planner applications that can be integrated with AI Nutrition-Pro. It connects to AI Nutrition-Pro using REST and HTTPS. - uploads samples of dietitians' content to AI Nutrition-Pro
- fetches AI generated results, e.g. diet introduction, from AI Nutrition-Pro
ChatGPT-3.5 External system, API It's OpenAI product, an LLM solution It will be used to generate content based on provided samples.

AI Nutrition-Pro container context systems and persons

Name Type Description Responsibilities
Web Control Plane Internal system, Web application It's written using Golang and deployed as Docker container into AWS Elastic Container Service. It uses Control Plane Database to store data. It's used in 3 roles: Administrator, App Onboarding Manager, and Meal Planner application manager. Provide control plane to onboard and manage clients, configuration and check billing data
Control Plane Database Internal database, Amazon RDS instance Database storing data for Web Control Plane
API Gateway Internal system, API Gateway Kong API Gateway - authentication
- rate limiting
- filtering of input
API Application Internal system, API application It's written using Golang and deployed as Docker container into AWS Elastic Container Service Provides AI Nutrition-Pro functionality via API.
API database Internal database, Amazon RDS instance Stored data: samples of dietitians' content, requests, and responses to LLM. Storing data for API Application
Administrator Internal Person Administrator of AI Nutrition-Pro application. - manage server configuration
- resolve problems

Security

  1. Authentication with Meal Planner applications - each has individual API key.
  2. Authorization of Meal Planner applications - API Gateway has ACL rules that allow or deny certain actions.
  3. Encrypted network traffic - network traffic between Meal Planner applications and API Gateway is encrypted using TLS.
xvnpw commented 1 day ago

/fabric create stride threat model and summarize it. Return only summary

github-actions[bot] commented 1 day ago
(🤖 AI Generated)

ONE SENTENCE SUMMARY:

AI Nutrition-Pro delivers AI-generated nutritional content via secure integration with Meal Planner apps and OpenAI's ChatGPT.

MAIN POINTS:

  1. AI Nutrition-Pro provides AI-generated nutritional content via an API for Meal Planner applications.
  2. Integrates with external Meal Planner apps using REST APIs over HTTPS for content generation.
  3. Utilizes OpenAI's ChatGPT-3.5 to generate content based on dietitian-provided samples.
  4. Architecture includes API Gateway, Web Control Plane, and Backend API Application.
  5. API Gateway (Kong) handles authentication, rate limiting, and input filtering.
  6. Web Control Plane manages client onboarding, configuration, and billing data.
  7. Stores data in Control Plane Database and API Database using Amazon RDS.
  8. Backend API Application is developed in Golang and deployed on AWS Elastic Container Service.
  9. Security measures include individual API keys, ACL rules, and TLS encryption.
  10. Administrator oversees system configuration, management, and problem resolution.

TAKEAWAYS:

  1. AI Nutrition-Pro seamlessly integrates AI content generation into existing Meal Planner applications.
  2. Security is a priority with robust authentication, authorization, and encryption protocols.
  3. Leveraging OpenAI's ChatGPT enhances the quality and efficiency of content creation.
  4. Scalable and maintainable architecture is achieved through AWS services and containerization.
  5. Clear separation of control plane and API data improves data management and security.