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1 Parent(s): 7103ddc

Create app.py

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  1. app.py +20 -0
app.py ADDED
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+ import streamlit as st
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+ from sentence_transformers import CrossEncoder
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+
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+ model_name = "Anvilogic/CE-typosquat-detect"
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+ model = CrossEncoder(model_name)
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+
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+ st.title("Typosquatting Detection App")
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+ st.write("Enter two domains to check if one is a typosquatted variant of the other.")
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+
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+ domain = st.text_input("Enter the legitimate domain name:")
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+ sim_domain = st.text_input("Enter the potentially typosquatted domain name:")
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+
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+ if st.button("Check Typosquatting"):
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+ inputs = [(domain, sim_domain)]
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+ prediction = model.predict(inputs)[0]
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+
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+ if prediction > 0.5:
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+ st.success(f"The model predicts that '{sim_domain}' is likely a typosquatted version of '{domain}'.")
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+ else:
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+ st.warning(f"The model predicts that '{sim_domain}' is NOT likely a typosquatted version of '{domain}'.")