app.py

import streamlit as st
import tensorflow as tf
import pickle

# Model ve Vectorizer'ı yükleme
model = tf.keras.models.load_model("xss_detection_model-3.h5")

with open("vectorizer.pkl", "rb") as file:
    vectorizer = pickle.load(file)

# Streamlit başlığı
st.title("XSS Detector")

# Kullanıcı girdisi
user_input = st.text_area("XSS payload'ınızı buraya girin", height=100)

# Tespit butonu
if st.button("Tespit Et"):
    transformed_input = vectorizer.transform([user_input]).toarray()
    prediction = model.predict(transformed_input)

    # Sonucu ekranda gösterme
    if prediction[0] > 0.5:
        st.write("Bu bir XSS payload!")
    else:
        st.write("Bu bir XSS payload DEĞİL!")