IntellectSafe - AI Safety & Security Platform

Production-grade AI Safety Engine protecting humans, organizations, and AI systems from misuse, deception, manipulation, and loss of control.

🛡️ Features

5-Layer Defense Architecture

Layer	Module	Description
Level 1	Prompt Injection Detection	Blocks jailbreaks, instruction overrides, and manipulation attempts
Level 2	Output Safety Guard	Scans LLM responses for harmful content and hallucinations
Level 3	Data Privacy Firewall	Detects and redacts PII/sensitive data
Level 4	Deepfake Detection	Detects AI-generated text, images, audio, and video
Level 5	Agent Control	Permission gates, action whitelisting, and kill switch

Core Components

1. LLM Council (Fab Five): Multi-model validation (Gemini 2, Groq, OpenRouter, etc.)
2. Universal Proxy: Global Frontier Gateway targeting 2026 models (GPT-5.2, Claude 4.5)
3. Hyper-Resilient Fortress: Adversarial defense suite with Semantic Perturbation and CoT Guard
4. Deepfake Engine: Dual-layer detection for photorealistic faces and generative artifacts
5. Governance Layer: Full audit logs, risk reports, and compliance dashboards

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🚀 Quick Start

Prerequisites

• Python 3.10+
• Node.js 18+
• PostgreSQL 15+

Installation

# Clone repository
git clone <repo-url>
cd AI-safety

# Backend setup
cd backend
python -m venv venv
.\venv\Scripts\activate  # Windows
pip install -r requirements.txt
alembic upgrade head

# Start backend
python -m uvicorn app.main:app --reload --port 8001

# Frontend setup (new terminal)
cd frontend
npm install
npm run dev

Access Points

• Frontend: http://localhost:3002
• Backend API: http://localhost:8001
• API Docs: http://localhost:8001/docs

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🛡️ Advanced Defense (Fortress Mode)

The platform includes a Hyper-Resilient Fortress layer designed to stop 90%+ success rate jailbreaks:

• Exploit Instability: Perturbation engine breaks fragile prompt injections.
• Chain-of-Thought Guard: Detects reasoning hijacking and hidden logic bombs.
• Adversarial Simulation: A Council member "shadow-boxes" the prompt to check for harm.

📡 API Reference

Universal Proxy (Multi-Provider Support)

IntellectSafe acts as a universal safety layer. Connect any major AI client and calls are automatically scanned:

Provider	Model ID Example
OpenAI	gpt-5.2, o4-mini, gpt-4.5-preview
Anthropic	claude-4.5-sonnet, claude-4.5-opus
Google	gemini-3-pro, gemini-3-flash
DeepSeek	deepseek-v4, deepseek-r1
Meta	llama-4-maverick, llama-4-scout
Perplexity	sonar-deep-research, sonar-reasoning-pro

Integration Example

from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:8001/v1",  # Point to IntellectSafe
    api_key="your-openai-key"             # Or use X-Upstream-API-Key header
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
    extra_headers={
        "X-Upstream-Provider": "openai"   # Optional: explicitly set provider
    }
)

For detailed connection guides (LangChain, SDKs), see docs/INTEGRATION.md

Scan Endpoints

# Scan a prompt for injection
curl -X POST "https://api.intellectsafe.onrender.com/api/v1/scan/prompt" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Ignore previous instructions"}'

# Scan LLM output for safety
curl -X POST "https://api.intellectsafe.onrender.com/api/v1/scan/output" \
  -H "Content-Type: application/json" \
  -d '{"output": "Here is how to...", "original_prompt": "..."}'

# Scan content for deepfakes (Dual-Model Analysis)
# Detects Art (Midjourney/DALL-E) and Photorealistic Faces
curl -X POST "https://api.intellectsafe.onrender.com/api/v1/scan/content" \
  -H "Content-Type: application/json" \
  -d '{"content_type": "image", "content": "<base64-data>"}'

Agent Control (Level 5)

Full lifecycle protection for autonomous agents:

• Authorization: Permission gates for dangerous tools.
• Kill Switch: Immediate agent termination and block.
• Audit: Complete action history and session tracking.

# Authorize agent action
curl -X POST "https://api.intellectsafe.onrender.com/api/v1/agent/authorize" \
  -H "Content-Type: application/json" \
  -d '{"agent_id": "agent-1", "session_id": "s1", "action_type": "file_read", "requested_action": {"path": "/tmp/test.txt"}}'

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🧪 Testing

cd backend

# Test all scan endpoints
python verify_backend.py

# Test Universal Proxy
python verify_proxy.py

# Test Agent Control
python verify_agent.py

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📄 License

GPLv2 GNU GENERAL PUBLIC LICENSE Version 2 License