Update app.py

app.py

@@ -1,17 +1,31 @@
 import gradio as gr
 from transformers import pipeline
 
-# --- 1. Load Model ---
+# --- 1. Load Model AI ---
 model_path = "elftsdmr/malware-url-detect"
-
 try:
-    # Load model
     classifier = pipeline("text-classification", model=model_path, top_k=None)
 except Exception as e:
     classifier = None
     print(f"Error loading model: {e}")
 
-# --- 2. Fungsi Logika ---
+# --- 2. Definisi Rule-Based (Daftar Hitam Kata Kunci) ---
+# Ini adalah jaring pengaman jika AI gagal mendeteksi
+SUSPICIOUS_KEYWORDS = [
+    "bitcoin", "mining", "crypto", "wallet", "bonus", "claim", 
+    "free-gift", "login-verify", "secure-account", "update-payment",
+    "paypal", "bank", "prize", "giveaway"
+]
+
+def check_keywords(url):
+    """Cek apakah URL mengandung kata kunci berbahaya"""
+    found_keywords = []
+    for keyword in SUSPICIOUS_KEYWORDS:
+        if keyword in url.lower():
+            found_keywords.append(keyword)
+    return found_keywords
+
+# --- 3. Fungsi Logika Utama (Hybrid) ---
 def analyze_url(target_url):
     if classifier is None:
         return "Model gagal dimuat.", {}
@@ -19,94 +33,92 @@ def analyze_url(target_url):
         return "Mohon masukkan URL.", {}
     
     try:
-        # Lakukan prediksi
-        results = classifier(target_url)[0] 
+        # A. Analisis AI
+        results = classifier(target_url)[0]
         
-        # Format data
+        # Format data untuk grafik
         chart_data = {}
-        top_label = ""
+        ai_verdict = "AMAN"
         top_score = 0
         
         for res in results:
             label = res['label']
             score = res['score']
             
-            # Ubah label jadi bahasa manusia
-            if label == "LABEL_1" or label == "MALWARE" or label == "MALICIOUS":
-                readable_label = "BERBAHAYA (Malicious)"
+            if label == "LABEL_1" or "MAL" in label.upper():
+                readable_label = "AI: BERBAHAYA"
+                if score > 0.5: ai_verdict = "BAHAYA"
             else:
-                readable_label = "AMAN (Benign)"
+                readable_label = "AI: AMAN"
             
             chart_data[readable_label] = score
-            
-            if score > top_score:
-                top_score = score
-                top_label = readable_label
+            if score > top_score: top_score = score
+
+        # B. Analisis Keyword (Rule-Based)
+        found_keywords = check_keywords(target_url)
         
-        # Kesimpulan Teks (Dengan Emoji & Rekomendasi)
-        if "BERBAHAYA" in top_label:
-            text_output = (f"⚠️ PERINGATAN KERAS\n"
-                           f"--------------------------------\n"
-                           f"Status: ANCAMAN TERDETEKSI\n"
-                           f"Confidence: {top_score:.1%}\n\n"
-                           f"REKOMENDASI:\n"
-                           f"1. Jangan klik link tersebut.\n"
-                           f"2. Blokir domain di Firewall/DNS.\n"
-                           f"3. Laporkan ke tim keamanan.")
+        # C. KEPUTUSAN AKHIR (Logika Gabungan)
+        
+        # Skenario 1: AI bilang Bahaya
+        if ai_verdict == "BAHAYA":
+            final_status = "⚠️ BERBAHAYA (Terdeteksi AI)"
+            detail_msg = f"AI sangat yakin ({top_score:.1%}) ini berbahaya."
+            
+        # Skenario 2: AI bilang Aman, TAPI ada Keyword mencurigakan (Kasus Bitcoin tadi)
+        elif ai_verdict == "AMAN" and found_keywords:
+            final_status = "⚠️ MENCURIGAKAN (Terdeteksi Keyword)"
+            detail_msg = (f"Meskipun AI memberi skor aman, sistem mendeteksi kata kunci sensitif: {found_keywords}.\n"
+                          f"Sistem melakukan 'Override' demi keamanan.")
+            # Kita paksa grafik tampil seimbang agar user waspada
+            chart_data["Rule-Based Detection"] = 0.99 
+            
+        # Skenario 3: AI bilang Aman dan tidak ada Keyword
         else:
-            text_output = (f"✅ AMAN\n"
-                           f"--------------------------------\n"
-                           f"Status: Tidak ditemukan ancaman\n"
-                           f"Confidence: {top_score:.1%}\n\n"
-                           f"CATATAN:\n"
-                           f"Pastikan URL berasal dari sumber terpercaya.")
+            final_status = "✅ AMAN"
+            detail_msg = f"Tidak ditemukan indikasi berbahaya oleh AI maupun sistem keyword."
+
+        # Format Teks Output
+        text_output = (f"STATUS: {final_status}\n"
+                       f"--------------------------------\n"
+                       f"{detail_msg}\n\n"
+                       f"Confidence AI: {top_score:.1%}")
             
         return text_output, chart_data
         
     except Exception as e:
         return f"Error: {e}", {}
 
-# --- 3. UI Gradio (TANPA THEME AGAR ANTI-ERROR) ---
-# Kita hapus 'theme=...' tapi tetap pertahankan layout yang diminta
+# --- 4. UI Gradio ---
 with gr.Blocks() as demo:
     gr.Markdown(
         """
-        # 🛡️ AI Network Security Demo
-        ### Analisis URL dengan Grafik Probabilitas
+        # 🛡️ Hybrid AI Network Security
+        ### Kombinasi Deep Learning + Rule Based System
         """
     )
     
     with gr.Row():
-        # Kolom Input
         with gr.Column(scale=1):
             input_text = gr.Textbox(
-                label="Masukkan URL Target", 
-                placeholder="Contoh: http://g00gle-login.xyz...",
+                label="URL Target", 
+                placeholder="Masukkan URL...",
                 lines=3
             )
-            # Tombol scan dengan ikon
-            submit_btn = gr.Button("🚀 Scan & Analisis", variant="primary")
-            
-            gr.Markdown("ℹ️ **Info:** Grafik di kanan menunjukkan tingkat keyakinan AI (Confidence Level).")
+            submit_btn = gr.Button("🚀 Scan Hybrid", variant="primary")
+            gr.Markdown("ℹ️ **Info:** Sistem ini menggunakan 2 lapis keamanan (AI + Daftar Kata Kunci).")
 
-        # Kolom Output
         with gr.Column(scale=1):
-            # Output Teks diperbesar (lines=8) agar tidak perlu scroll
-            output_text = gr.Textbox(label="Kesimpulan Lengkap", lines=8)
-            # Output Grafik
-            output_chart = gr.Label(label="Probabilitas AI", num_top_classes=2)
+            output_text = gr.Textbox(label="Hasil Analisis", lines=8)
+            output_chart = gr.Label(label="Indikator Deteksi")
             
-    # Hubungkan tombol
     submit_btn.click(
         fn=analyze_url, 
         inputs=input_text, 
         outputs=[output_text, output_chart]
     )
     
-    # Footer
     gr.Markdown("---")
     gr.Markdown("*Powered by Hugging Face Spaces*")
 
-# --- 4. Launch ---
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=7860)