vuln_detection.py

import os

# Directory and file structure
structure = {
    "malware_detection_project": {
        "config": {
            "api_config.json": '''{
    "cve_api_url": "https://cve.circl.lu/api/cve/",
    "virustotal_api_key": "your_virustotal_api_key",
    "exploit_db_api_url": "https://www.exploit-db.com/",
    "network_analysis_tool": "nmap",
    "apk_analysis_tool": "apktool"
}''',
            "model_config.json": '''{
    "model_type": "RandomForest",
    "n_estimators": 100,
    "test_size": 0.2,
    "random_state": 42
}'''
        },
        "data": {
            "cve_data.json": '''{
    "CVE-2024-1234": {
        "score": 9.8,
        "description": "Critical vulnerability in XYZ",
        "exploitability": 10
    },
    "CVE-2024-5678": {
        "score": 6.5,
        "description": "Moderate vulnerability in ABC",
        "exploitability": 6
    }
}''',
            "exploit_data.json": '''{
    "CVE-2024-1234": {
        "exploit_available": true
    },
    "CVE-2024-5678": {
        "exploit_available": false
    }
}''',
            "virustotal_data.json": '''{
    "hash_1": {
        "malicious": 1,
        "harmless": 0,
        "suspicious": 0
    },
    "hash_2": {
        "malicious": 0,
        "harmless": 1,
        "suspicious": 0
    }
}''',
            "network_data.json": '''{
    "192.168.1.1": {
        "open_ports": 3,
        "vulnerable_services": 1,
        "traffic_pattern": "anomalous"
    },
    "192.168.1.2": {
        "open_ports": 2,
        "vulnerable_services": 0,
        "traffic_pattern": "normal"
    }
}''',
            "apk_data.json": '''{
    "apk_1": {
        "permissions": 5,
        "malicious_activity": 1,
        "obfuscation_level": 7
    },
    "apk_2": {
        "permissions": 3,
        "malicious_activity": 0,
        "obfuscation_level": 4
    }
}'''
        },
        "src": {
            "logger.py": '''import logging

def setup_logger():
    logger = logging.getLogger('MalwareDetectionLogger')
    logger.setLevel(logging.DEBUG)
    handler = logging.FileHandler('malware_detection.log')
    handler.setLevel(logging.DEBUG)
    formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
    handler.setFormatter(formatter)
    logger.addHandler(handler)
    return logger

logger = setup_logger()
''',
            "data_fetcher.py": '''import json
from .logger import logger

def load_data(file_path):
    logger.info(f"Loading data from {file_path}")
    try:
        with open(file_path, 'r') as file:
            data = json.load(file)
            return data
    except FileNotFoundError:
        logger.error(f"File not found: {file_path}")
        return {}
    except json.JSONDecodeError:
        logger.error(f"Error decoding JSON from {file_path}")
        return {}

def fetch_cve_data():
    return load_data('data/cve_data.json')

def fetch_exploit_data():
    return load_data('data/exploit_data.json')

def fetch_virustotal_data():
    return load_data('data/virustotal_data.json')

def fetch_network_data():
    return load_data('data/network_data.json')

def fetch_apk_data():
    return load_data('data/apk_data.json')
''',
            "feature_engineering.py": '''import pandas as pd
from .logger import logger

def create_feature_set(cve_data, exploit_data, vt_data, network_data, apk_data):
    logger.info("Creating feature set from the raw data")
    records = []

    for cve_id, cve_details in cve_data.items():
        vt_record = vt_data.get('hash_1', {})
        exploit_record = exploit_data.get(cve_id, {})
        network_record = network_data.get('192.168.1.1', {})
        apk_record = apk_data.get('apk_1', {})

        record = {
            'cve_score': cve_details.get('score', 0),
            'exploitability': cve_details.get('exploitability', 0),
            'exploit_available': int(exploit_record.get('exploit_available', False)),
            'malicious': vt_record.get('malicious', 0),
            'harmless': vt_record.get('harmless', 0),
            'suspicious': vt_record.get('suspicious', 0),
            'open_ports': network_record.get('open_ports', 0),
            'vulnerable_services': network_record.get('vulnerable_services', 0),
            'traffic_pattern_anomalous': 1 if network_record.get('traffic_pattern') == 'anomalous' else 0,
            'permissions': apk_record.get('permissions', 0),
            'malicious_activity': apk_record.get('malicious_activity', 0),
            'obfuscation_level': apk_record.get('obfuscation_level', 0),
            'is_vulnerable': 1 if cve_details.get('score', 0) > 7 else 0
        }
        records.append(record)

    df = pd.DataFrame(records)
    logger.info(f"Feature set created with {df.shape[0]} records")
    return df
''',
            "model_trainer.py": '''from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score
from .logger import logger
import json

def load_model_config():
    logger.info("Loading model configuration")
    with open('config/model_config.json', 'r') as file:
        return json.load(file)

def train_model(df):
    logger.info("Starting model training")
    config = load_model_config()

    X = df.drop('is_vulnerable', axis=1)
    y = df['is_vulnerable']

    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=config['test_size'], random_state=config['random_state'])

    model = RandomForestClassifier(n_estimators=config['n_estimators'], random_state=config['random_state'])
    model.fit(X_train, y_train)

    y_pred = model.predict(X_test)
    accuracy = accuracy_score(y_test, y_pred)
    logger.info(f"Model training completed with accuracy: {accuracy * 100:.2f}%")

    return model
''',
            "predictor.py": '''import pandas as pd
from .logger import logger

def predict_vulnerability(model, cve_data, exploit_data, vt_data, network_data, apk_data):
    logger.info("Starting prediction on new data")
    
    input_data = pd.DataFrame([{
        'cve_score': cve_data.get('score', 0),
        'exploitability': cve_data.get('exploitability', 0),
        'exploit_available': int(exploit_data.get('exploit_available', False)),
        'malicious': vt_data.get('malicious', 0),
        'harmless': vt_data.get('harmless', 0),
        'suspicious': vt_data.get('suspicious', 0),
        'open_ports': network_data.get('open_ports', 0),
        'vulnerable_services': network_data.get('vulnerable_services', 0),
        'traffic_pattern_anomalous': 1 if network_data.get('traffic_pattern') == 'anomalous' else 0,
        'permissions': apk_data.get('permissions', 0),
        'malicious_activity': apk_data.get('malicious_activity', 0),
        'obfuscation_level': apk_data.get('obfuscation_level', 0)
    }])

    prediction = model.predict(input_data)
    logger.info(f"Prediction result: {'Vulnerable' if prediction[0] == 1 else 'Not Vulnerable'}")
    return prediction[0]
'''
        },
        "main.py": '''from src.data_fetcher import fetch_cve_data, fetch_exploit_data, fetch_virustotal_data, fetch_network_data, fetch_apk_data
from src.feature_engineering import create_feature_set
from src.model_trainer import train_model
from src.predictor import predict_vulnerability
from src.logger import logger

if __name__ == '__main__':
    logger.info("Starting Malware Detection Project")

    # Fetch data
    cve_data = fetch_cve_data()
    exploit_data = fetch_exploit_data()
    vt_data = fetch_virustotal_data()
    network_data = fetch_network_data()
    apk_data = fetch_apk_data()

    # Create features
    features_df = create_feature_set(cve_data, exploit_data, vt_data, network_data, apk_data)

    # Train model
    model = train_model(features_df)

    # Predict on a new example (using first entry in cve_data for illustration)
    if cve_data:
        first_cve = next(iter(cve_data.values()))
        prediction = predict_vulnerability(model, first_cve, exploit_data.get('CVE-2024-1234', {}), vt_data.get('hash_1', {}), network_data.get('192.168.1.1', {}), apk_data.get('apk_1', {}))

        logger.info(f"Prediction for first CVE: {'Vulnerable' if prediction == 1 else 'Not Vulnerable'}")
    else:
        logger.warning("No CVE data available for prediction")
'''
        }
    }


# Create directories and files
def create_structure(base_path, structure):
    for name, content in structure.items():
        path = os.path.join(base_path, name)
        if isinstance(content, dict):
            os.makedirs(path, exist_ok=True)
            create_structure(path, content)
        else:
            with open(path, 'w') as file:
                file.write(content)

# Usage
base_path = "malware_detection_project"
create_structure(base_path, structure)