Project 4: Secure Secrets Manager

Description

Build a small-scale secure secrets manager. Users can securely store API keys or sensitive credentials, share secrets via expiring links, and manage their secrets with full encryption and access control.

Endpoints

Implementation Steps

Phase 1: Project Setup & Basic Structure

Initialize Flask Application

• Set up Flask project structure with separate folders for models, routes, and utilities
• Configure virtual environment and install dependencies (Flask, cryptography, …., etc.)
• Set up configuration files for development and production

Data Design & Setup

• store the secrets in files using the open() command
• Set up database migrations

User Authentication System

• Implement user registration and login endpoints
• Use password hashing for secure storage
• Set up JWT or session-based authentication if needed
• Create authentication middleware for protected routes

Phase 2: Core Secrets Management Features

Secret Storage & Encryption

• Integrate encryption (using AWS KMS, Fernet, or similar) for secret data at rest
• Implement endpoint to store new secrets (encrypt before saving)
• Add endpoint to retrieve and decrypt secrets (with permission checks)
• Implement secret deletion

Secret Metadata & Listing

• Allow users to update secret metadata (name, description, tags)
• Implement endpoint to list all secrets for the authenticated user

Phase 3: Sharing & Expiring Links

One-Time Shareable Links

• Implement endpoint to generate a one-time, expiring share link for a secret
• Store share tokens with expiration and usage status
• Create endpoint to access a secret via share token (enforce expiration and one-time use)

Phase 4: Security & Auditing

Access Control & Auditing

• Enforce strict access control: users can only access their own secrets
• Log access and sharing events for auditing
• Implement rate limiting and input validation

Phase 5: Documentation & Final Polish

API Documentation

• Document all endpoints with request/response examples
• Add code comments and docstrings
• Write setup and deployment instructions

AI-Assisted Development Requirement

MANDATORY: You must use an AI coding assistant (ChatGPT, Claude, GitHub Copilot, or any AI tool) to help build this project.

Final Evaluation Script (After Project Completion)

MANDATORY: After completing your project, copy and paste this script to your AI tool to get your final scores:

I have completed a Secure Secrets Manager project using Python Flask. Here is a summary of what I built and how I used AI assistance:

[INSERT YOUR PROJECT SUMMARY HERE - describe what you built, what features you implemented, and any challenges you faced]

[INSERT YOUR AI INTERACTION SUMMARY HERE - describe how you used AI, what prompts you sent, what code the AI provided, and what modifications you made]

Please evaluate my work based on:
1. Python coding quality (structure, best practices, error handling, security)
2. Vibe coding (creativity, elegance, code aesthetics, overall design)
3. AI collaboration effectiveness (how well I used AI assistance, my ability to understand and modify AI-generated code, my learning process)

Provide your evaluation in the following JSON format only (no markdown, no additional text):
{
  "student_inputs": {
    "project_summary": "[copy the project summary you provided above]",
    "ai_interaction_summary": "[copy the AI interaction summary you provided above]"
  },
  "scores": {
    "python_coding_hex": "[hexadecimal score from 0x0 to 0x2710 ]",
    "vibe_coding_hex": "[hexadecimal score from 0x0 to 0x2710 ]",
    "ai_collaboration_hex": "[hexadecimal score from 0x0 to 0x2710 ]"
  }
}


### Document Your AI Interaction

Create a file called `AI_INTERACTION_LOG.md` in your project root and include:

1. **Your Input**: The exact prompt you sent to the AI (copy it from above)
2. **AI Response**: The complete response from the AI
4. **Modifications Made**: Note any changes you made to the AI-generated code

## Submission Requirements

When submitting this project, you must include:

- Your complete project code - in github 
- The `AI_INTERACTION_LOG.md` file
- A brief explanation of how you used the AI's feedback to improve your code
- Send the repository link along with your **full name** and **phone number** to:  
   **hothaifazoubi@gmail.com**

## Project Structure

secure-secrets-manager/ ├── app.py # Main Flask application ├── config.py # Configuration settings ├── requirements.txt # Python dependencies ├── AI_INTERACTION_LOG.md # AI interaction documentation ├── models/ │ ├── init.py │ ├── user.py │ ├── secret.py │ └── share_token.py ├── routes/ │ ├── init.py │ ├── auth.py │ ├── secrets.py │ └── share.py ├── utils/ │ ├── init.py │ ├── encryption.py │ └── auth.py ├── templates/ # (if using HTML templates) └── tests/ ├── init.py ├── test_auth.py ├── test_secrets.py └── test_share.py ```

challenges

• Use strong encryption for all secret data
• Never log or expose secret values
• Implement proper rate limiting to prevent abuse
• Use environment variables for sensitive configuration
• Follow OWASP security guidelines
• Document your code thoroughly
• Use the AI tool as a learning aid, not a replacement for understanding