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import streamlit as st
from urllib.parse import urlparse
from sklearn.preprocessing import MinMaxScaler
import pickle
# Load the model
file = open("phishing_rf_model.saved", "rb")
rf_model = pickle.load(file)
file.close()
# Load the MinMaxScaler
min_scaler = MinMaxScaler()
# Function to extract features from URL
def extract_features_from_url(url):
parsed_url = urlparse(url)
num_dots = url.count('.')
subdomain_level = len(parsed_url.netloc.split('.')) - 1
path_level = len(parsed_url.path.split('/')) - 1
url_length = len(url)
num_dash = url.count('-')
num_dash_in_hostname = parsed_url.netloc.count('-')
at_symbol = '@' in parsed_url.netloc
tilde_symbol = '~' in parsed_url.netloc
num_underscore = url.count('_')
num_percent = url.count('%')
num_query_components = len(parsed_url.query.split('&'))
num_ampersand = url.count('&')
num_hash = url.count('#')
num_numeric_chars = sum(c.isdigit() for c in url)
no_https = not url.startswith('https://')
random_string = '?' in parsed_url.query
ip_address = parsed_url.netloc.count('.')
domain_in_subdomains = '.' in parsed_url.netloc[:-1]
domain_in_paths = '.' in parsed_url.path
https_in_hostname = 'https' in parsed_url.netloc
hostname_length = len(parsed_url.netloc)
path_length = len(parsed_url.path)
query_length = len(parsed_url.query)
double_slash_in_path = '//' in parsed_url.path
num_sensitive_words = 0 # You need to define how to extract this feature
return [num_dots, subdomain_level, path_level, url_length, num_dash,
num_dash_in_hostname, at_symbol, tilde_symbol, num_underscore, num_percent,
num_query_components, num_ampersand, num_hash, num_numeric_chars, no_https,
random_string, ip_address, domain_in_subdomains, domain_in_paths, https_in_hostname,
hostname_length, path_length, query_length, double_slash_in_path, num_sensitive_words]
# Function to predict using the model
def predict_phishing(url):
features = extract_features_from_url(url)
scaled_features = min_scaler.transform([features])
prediction = rf_model.predict(scaled_features)
return prediction
# Streamlit UI
def main():
st.title("Phishing URL Detector")
url_input = st.text_input("Enter the URL:")
if st.button("Check Phishing"):
if url_input:
prediction = predict_phishing(url_input)
if prediction[0] == 1:
st.error("Phishing URL Detected!")
else:
st.success("Safe URL")
else:
st.warning("Please enter a URL")
if __name__ == "__main__":
main()
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