Patriot

Patriot is an autonomous cybersecurity agent that thinks, plans, and learns as it works. It performs analysis using task planning, self-reflection, and real-time security data. It's built specifically to help with CyberPatriot

USAGE INSTRUCTIONS BELOW

Screenshots

Overview

Patriot takes complex cybersecurity questions and turns them into clear, step-by-step research plans. It runs those tasks using live security data, checks its own work, and refines the results until it has a confident, data-backed answer.

It’s not just a chatbot. It’s an agent that plans ahead, verifies its progress, and keeps iterating until the job is done.

Key Capabilities:

• Intelligent Task Planning: Automatically decomposes complex queries into structured research steps
• Autonomous Execution: Selects and executes the right tools to gather security data
• Self-Validation: Checks its own work and iterates until tasks are complete
• Real-Time Security Data: Access to vulnerability databases, threat intelligence feeds, and more.
• Safety Features: Built-in loop detection and step limits to prevent runaway execution

Prerequisites

• Python 3.10 or higher
• uv package manager
• OpenAI API key (get here)
  OR
  
• Gemini API key (get here) (FREE TIER - RECOMMENDED)

Installation

Install UV if not already:

# On macOS and Linux.
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows.
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

1. Clone the repository:

git clone https://github.com/adhyaay-karnwal/patriot.git
cd patriot

2. Install dependencies with uv:

uv sync

3. Set up your environment variables(whichever you set, thats the provider patriot will use):

# Copy the example environment file
cp env.example .env

# Edit .env and add your API keys
# OPENAI_API_KEY=your-openai-api-key
# GEMINI_API_KEY=your-gemini-api-key

Usage

Run Patriot in interactive mode:

uv run patriot-agent

Press CTRL+C to exit or type "exit"

Example Queries

Try asking Patriot questions like:

• "How do I harden a Windows 10 image?"
• "What are the common vulnerabilities in a Cisco router?"
• "How do I analyze a pcap file for forensic evidence?"
• "What are the best practices for securing a Linux server?"

Patriot will automatically:

1. Break down your question into research tasks
2. Fetch the necessary security data
3. Perform analysis
4. Provide a comprehensive, data-rich answer

Architecture

Patriot uses a multi-agent architecture with specialized components:

• Planning Agent: Analyzes queries and creates structured task lists
• Action Agent: Selects appropriate tools and executes research steps
• Validation Agent: Verifies task completion and data sufficiency
• Answer Agent: Synthesizes findings into comprehensive responses

Project Structure

patriot/
├── src/
│   ├── patriot/
│   │   ├── agent.py      # Main agent orchestration logic
│   │   ├── model.py      # LLM interface
│   │   ├── tools.py      # Cybersecurity tools
│   │   ├── prompts.py    # System prompts for each component
│   │   ├── schemas.py    # Pydantic models
│   │   ├── utils/        # Utility functions
│   │   └── cli.py        # CLI entry point
├── pyproject.toml
└── uv.lock

Configuration

Patriot supports configuration via the Agent class initialization:

from patriot.agent import Agent

agent = Agent(
    max_steps=20,              # Global safety limit
    max_steps_per_task=5       # Per-task iteration limit
)

Roadmap

1. Add line breaks to AI answer
2. Better tool use - terminal actions + file reading
3. Better OS and systems context
4. Enhance system prompt + add make it better for windows and linux

License

Apache-2.0-license
Officially open source
Built by Adhyaay Karnwal for CyberPatriot