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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}'.") | |