| import gradio as gr
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| import joblib
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| import pandas as pd
|
| import re
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| import os
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|
|
|
|
|
|
|
|
| def extract_features(url):
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| features = {
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| 'url_length': len(url),
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| 'num_dots': url.count('.'),
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| 'num_hyphens': url.count('-'),
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| 'num_slash': url.count('/'),
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| 'num_underscore': url.count('_'),
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| 'num_digits': sum(c.isdigit() for c in url),
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| 'has_https': 1 if url.startswith('https') else 0,
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| 'has_ip': 1 if re.search(r'\d+\.\d+\.\d+\.\d+', url) else 0,
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| 'num_suspicious': sum(1 for word in ['login','verify','secure','account','signin','auth']
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| if word in url.lower()),
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| 'num_at': url.count('@'),
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| 'num_question': url.count('?'),
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| 'num_equal': url.count('=')
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| }
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| return pd.DataFrame([features])
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|
|
| def predict_url(url):
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| if not url:
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| return "⚠️ Enter a URL", ""
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|
|
|
|
| model = joblib.load('malicious_url_detector.pkl')
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| features = extract_features(url)
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| pred = model.predict(features)[0]
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| prob = model.predict_proba(features)[0]
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|
|
| if pred == 1:
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| return f"🚨 MALICIOUS\nConfidence: {prob[1]:.1%}", ""
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| return f"✅ SAFE\nConfidence: {prob[0]:.1%}", ""
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|
|
| interface = gr.Interface(
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| fn=predict_url,
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| inputs=gr.Textbox(label="Enter URL", placeholder="https://...", lines=2),
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| outputs=gr.Textbox(label="Result", lines=3),
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| title="🛡️ AI Malicious URL Detector",
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| description="This AI model detects phishing and malicious URLs in real-time.",
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| examples=[
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| ["https://google.com"],
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| ["https://paypal.com.login.verify.secure.com"],
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| ["https://github.com"],
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| ["http://192.168.1.1/banking/login"]
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| ]
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| )
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|
|
| interface.launch() |
