app.py

from flask import Flask, request, jsonify
import numpy as np
import joblib  # to save and load the trained model
import re
from urllib.parse import urlparse
from tld import get_tld
from sklearn.ensemble import RandomForestClassifier

app = Flask(__name__)

# Load your trained model
model = joblib.load('random_forest_model.pkl')  # save your trained model using joblib

# Define your feature extraction functions here...

def having_ip_address(url):
    # Your implementation
    pass

def abnormal_url(url):
    # Your implementation
    pass

def count_dot(url):
    # Your implementation
    pass

# Define other functions similarly...

def main(url):
    status = []
    status.append(having_ip_address(url))
    status.append(abnormal_url(url))
    status.append(count_dot(url))
    status.append(count_www(url))
    status.append(count_atrate(url))
    status.append(no_of_dir(url))
    status.append(no_of_embed(url))
    status.append(shortening_service(url))
    status.append(count_https(url))
    status.append(count_http(url))
    status.append(count_per(url))
    status.append(count_ques(url))
    status.append(count_hyphen(url))
    status.append(count_equal(url))
    status.append(url_length(url))
    status.append(hostname_length(url))
    status.append(suspicious_words(url))
    status.append(digit_count(url))
    status.append(letter_count(url))
    status.append(fd_length(url))
    tld = get_tld(url, fail_silently=True)
    status.append(tld_length(tld))
    return status

@app.route('/predict', methods=['POST'])
def predict():
    data = request.json
    url = data.get('url')
    features = np.array(main(url)).reshape(1, -1)
    prediction = model.predict(features)
    
    if int(prediction[0]) == 0:
        result = "SAFE"
    elif int(prediction[0]) == 1:
        result = "DEFACEMENT"
    elif int(prediction[0]) == 2:
        result = "PHISHING"
    elif int(prediction[0]) == 3:
        result = "MALWARE"
        
    return jsonify({"prediction": result})

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=8000)