Adaptive AI Malware Simulator

What It Does

Installation

pip install numpy scikit-learn

Usage

python adaptive_ai_malware_simulator.py --environment example_config.json --logfile simulation_results.json

Source Code

import json
import logging
import numpy as np
from sklearn.ensemble import RandomForestClassifier
import argparse

# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

def simulate_adaptive_malware(environment_config, log_file):
    """
    Simulates adaptive AI-driven malware behavior.

    Args:
        environment_config (dict): Configuration for the environment including defenses.
        log_file (str): Path to the log file where results will be saved.

    Returns:
        None
    """
    logging.info("Starting simulation with environment configuration: %s", environment_config)

    # Extract defense mechanisms and system data from the environment configuration
    defenses = environment_config.get("defenses", [])
    system_data = environment_config.get("system_data", [])

    if not defenses or not system_data:
        logging.error("Invalid environment configuration: Missing defenses or system data.")
        raise ValueError("Environment configuration must include 'defenses' and 'system_data'.")

    # Simulate adaptive malware behavior
    np.random.seed(42)  # For reproducibility
    X = np.array(system_data)
    y = np.random.choice([0, 1], size=len(X))  # Random labels (0: benign, 1: malicious)

    # Train a simple model to simulate malware learning
    model = RandomForestClassifier()
    model.fit(X, y)

    # Simulate adaptation by predicting against defenses
    predictions = model.predict(X)
    adaptation_results = [
        {"data_point": data.tolist(), "predicted_label": int(pred), "defense": defenses}
        for data, pred in zip(X, predictions)
    ]

    # Log results
    with open(log_file, "w") as log:
        json.dump(adaptation_results, log, indent=4)

    logging.info("Simulation completed. Results saved to %s", log_file)

def main():
    """
    CLI entry point for the Adaptive AI Malware Simulator.
    """
    parser = argparse.ArgumentParser(description="Adaptive AI Malware Simulator")
    parser.add_argument('--environment', type=str, required=True, help='Path to the environment configuration JSON file.')
    parser.add_argument('--logfile', type=str, required=True, help='Path to the output log file.')

    args = parser.parse_args()

    try:
        # Load environment configuration
        with open(args.environment, 'r') as env_file:
            environment_config = json.load(env_file)

        # Run the simulation
        simulate_adaptive_malware(environment_config, args.logfile)

    except Exception as e:
        logging.error("An error occurred: %s", e)
        raise

if __name__ == "__main__":
    main()