AI Network Search

This Python script performs network port scanning using multiple heuristic algorithms, including Q-learning, Monte Carlo simulation, Instance-Based Learning (IBL), and A* search. It identifies live IPs within a given subnet and scans a wide range of ports to rank them based on their likelihood of being open.

Features

1. Live IP Detection: Pings IP addresses within a given range to identify active hosts.
2. Port Scanning: Scans the identified live hosts for open ports using different heuristic behaviors.
3. Heuristic Behaviors:
   • Instance-Based Learning (IBL): Uses past port scan results to inform future scans.
   • Monte Carlo Simulation: Randomized port scans to estimate probabilities of open ports.
   • Q-learning: Reinforcement learning approach to prioritize ports based on past rewards.
   • A Search*: Uses a priority-based heuristic to guide port scanning.

Requirements

• Python 3.7+
• Libraries: ipaddress, pythonping, socket, speedyibl, random, collections, heapq, time

Install the required libraries with:

pip install pythonping speedyibl

Usage

1. Run the script:

   python <script_name>.py

2. Input Parameters:
   • IP Range: Enter a subnet range (e.g., 192.168.1.0/24).
   • Behavior ID: Choose from 1 to 4 to select a heuristic behavior:
     • 1 = Instance-Based Learning
     • 2 = Monte Carlo Simulation
     • 3 = Q-learning
     • 4 = A* Search

Example

Enter the IP range (e.g., 192.168.1.0/24): 192.168.1.0/24
Enter the behavior number (1-4): 1

Notes

• Adjustable Parameters: You can modify the number of trials, scan attempts, or learning parameters directly in the functions.
• Security: This tool is for educational purposes. Ensure you have permission before scanning any network.