🛡️ Sentinel: AI Trust Infrastructure

"Imagine giving your house keys to a stranger just because they seem smart. That is what we do with AI today."

📑 Executive Vision

Sentinel is a defense-in-depth security layer designed specifically for the Agentic AI era. It acts as a middleware between your application and Large Language Models (LLMs), ensuring that:

1. PII never leaves your perimeter: Sensitive data is masked locally before API transmission.
2. Attackers are actively neutralized: Honeytoken injection traps malicious actors attempting to prompt-inject your agents.

🏗️ System Architecture (The First Principles)

The system operates on a strictly modular architecture to ensure zero latency impact.

graph LR
    User[User Input] --> Shield[🛡️ Sentinel Shield]
    Shield -->|Masked Data| LLM[LLM Provider]
    LLM -->|Response| Shield
    Shield -->|Unmasked Response| User
    Attacker[Attacker] -->|Touch Honeytoken| Trap[🪤 Sentinel Trap]
    Trap -->|Alert & Block| Dashboard

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📂 Project Structure

sentinel-core/
├── src/
│   ├── shield/       # PII Masking & Cryptographic Logic
│   ├── trap/         # Active Defense & Honeytoken Generation
│   └── utils/        # Shared Engineering Utilities
├── tests/            # Unit & Integration Tests (TDD)
├── docs/             # Architecture Blueprints
└── main.py           # Entry Point

🚀 Roadmap

• Phase 1: The Shield - Implement local AES-256 masking for Emails, Credit Cards, and API Keys.
• Phase 2: The Trap - Develop dynamic honeytoken injection logic.
• Phase 3: The Core - Release PyPI package pip install sentinel-core.

Architected with First Principles by [Mohamed Abdelaziz]