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)

# GIF arka planını eklemek için HTML
st.markdown(
    """
    <style>
    .stApp {
        background-image: url(https://i.pinimg.com/originals/19/e1/71/19e171391727335f510db47a13269d2d.gif);
        background-size: cover;
        text-align: center;  # Bu satır eklendi
    }
    </style>
    """,
    unsafe_allow_html=True
)

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

# Kullanıcı girdisi
user_input = st.text_area("Enter your XSS payload here", height=100)

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

    # Sonucu ekranda gösterme
    if prediction[0] > 0.5:
        st.write("It's an XSS payload!")
    else:
        st.write("This is NOT an XSS payload!")