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import streamlit as st
from sentence_transformers import CrossEncoder
model_name = "Anvilogic/CE-typosquat-detect"
model = CrossEncoder(model_name)
st.title("Typosquatting Detection App")
st.write("Enter two domains to check if one is a typosquatted variant of the other.")
domain = st.text_input("Enter the legitimate domain name:")
sim_domain = st.text_input("Enter the potentially typosquatted domain name:")
if st.button("Check Typosquatting"):
inputs = [(domain, sim_domain)]
prediction = model.predict(inputs)[0]
if prediction > 0.5:
st.success(f"The model predicts that '{sim_domain}' is likely a typosquatted version of '{domain}'.")
else:
st.warning(f"The model predicts that '{sim_domain}' is NOT likely a typosquatted version of '{domain}'.")
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