Update app.py

app.py

@@ -4,16 +4,18 @@ from urllib.parse import urlparse
 import csv
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 import torch
-#URL model
+import os
+
+# URL model
 url_tokenizer = AutoTokenizer.from_pretrained("najla45/phishing_detection_fine_tuned_bert")
 url_model = AutoModelForSequenceClassification.from_pretrained("najla45/phishing_detection_fine_tuned_bert")
 url_classifier = pipeline("text-classification", model=url_model, tokenizer=url_tokenizer)
 
-#email model
+# Email model
 email_tokenizer = AutoTokenizer.from_pretrained("cybersectony/phishing-email-detection-distilbert_v2.4.1")
 email_model = AutoModelForSequenceClassification.from_pretrained("cybersectony/phishing-email-detection-distilbert_v2.4.1")
 
-#logic for checking the state of url
+# Logic for checking the state of URL
 def is_phishing_url(url):
     suspicious_keywords = ['secure', 'account', 'update', 'free', 'login', 'verify', 'banking']
     domain = urlparse(url).netloc
@@ -35,7 +37,7 @@ def is_phishing_url(url):
 
     return score
 
-#logic checking for phishing email
+# Logic checking for phishing email
 def predict_email(email_text):
     inputs = email_tokenizer(email_text, return_tensors="pt", truncation=True, max_length=512)
     with torch.no_grad():
@@ -52,10 +54,9 @@ def predict_email(email_text):
     max_label, max_score = max(labels.items(), key=lambda x: x[1])
     return max_label, max_score, labels
 
-
-#LOGGING ALL DATA TO CSV FILE
-import os
+# Logging all data to CSV file
 LOG_FILE = os.path.join(os.path.dirname(__file__), "phishing_log.csv")
+
 def log_to_csv(url, rule_score, bert_label, bert_score, final_decision):
     try:
         file_exists = os.path.isfile(LOG_FILE)
@@ -67,8 +68,7 @@ def log_to_csv(url, rule_score, bert_label, bert_score, final_decision):
     except Exception as e:
         print(f"Error writing to CSV: {e}")
 
-
-#Combining URL and email checking logic
+# Combining URL and email checking logic
 def combined_phishing_detector(url, input_type, log=True):
     if input_type == "URL":
         rule_score = is_phishing_url(url)
@@ -86,21 +86,23 @@ def combined_phishing_detector(url, input_type, log=True):
         rule_score = "N/A"
         rule_result = "Not Applicable"
         final_decision = "Phishing" if bert_label.startswith("phishing") and bert_score > 0.7 else "Safe"
+    else:
+        rule_score = "N/A"
+        bert_label = "unknown"
+        bert_score = 0.0
+        final_decision = "Safe"
 
-    
     if log:
         log_to_csv(url, rule_score, bert_label, bert_score, final_decision)
 
     return url, rule_score, bert_label, bert_score, final_decision
 
-
-
 def run_detector(text, input_type):
-    url,rule_score, bert_label, bert_score,final_decision = combined_phishing_detector(text, input_type,log=True)
-    
+    url, rule_score, bert_label, bert_score, final_decision = combined_phishing_detector(text, input_type, log=True)
+
     # Add emoji based on result
     if final_decision.lower() == "phishing":
-        emoji =  "🚨"   # warning
+        emoji = "🚨"   # warning
     elif final_decision.lower() == "safe":
         emoji = "✅"  # check mark
     else:
@@ -112,43 +114,51 @@ def run_detector(text, input_type):
         f"🤖 BERT Label: {bert_label}\n"
         f"🔍 Confidence: {bert_score:.2f}"
     )
-    return message,LOG_FILE
-
-#---GUI-----
-gr.HTML("""
-<link href="https://fonts.googleapis.com/css2?family=Poppins:wght@400;500;600;700&display=swap" rel="stylesheet">
-<h1 style='text-align:center; color:white; font-family: "Poppins", sans-serif;'>🔐 Phishing URL & Email Detector (BERT + Rules) 🔐</h1>
-""")
-
-with gr.Blocks(css="""
-.gradio-container {
-    background-image: url('https://c8.alamy.com/comp/M79X4X/cyber-security-buzzwords-phishing-alert-with-blue-numbers-in-background-M79X4X.jpg');
-    background-size: cover;
-    background-position: center;
-    background-repeat: no-repeat;
-    font-family: 'Poppins', sans-serif;
-    color: white;
-}
-input, textarea, button, label, .gr-box, .gr-button, .gr-textbox, .gr-radio, .gr-file {
-    font-family: 'Poppins', sans-serif !important;
-    color: white;
-}
-""") as demo:
-
-    gr.HTML("<h1 style='text-align:center; color:white;'>🔐 Phishing URL & Email Detector (BERT + Rules) 🔐</h1>")
+    return message, LOG_FILE
+
+# ---------- GUI ----------
+with gr.Blocks() as demo:
+
+    # Custom font + CSS + title (no background image)
+    gr.HTML("""
+    <link href="https://fonts.googleapis.com/css2?family=Poppins:wght@400;500;600;700&display=swap" rel="stylesheet">
+    <style>
+    .gradio-container {
+        background: radial-gradient(circle at top, #1e293b, #020617);
+        background-attachment: fixed;
+        font-family: "Poppins", sans-serif;
+        color: white;
+    }
+    .gradio-container * {
+        font-family: "Poppins", sans-serif !important;
+    }
+    label, .gr-textbox, .gr-button, .gr-file {
+        color: white !important;
+    }
+    </style>
+    <h1 style='text-align:center; color:white;'>🔐 Phishing URL & Email Detector (BERT + Rules) 🔐</h1>
+    """)
 
     with gr.Row():
-        input_text = gr.Textbox(label="Enter URL or Email", lines=5)
+        input_text = gr.Textbox(label="Enter URL or Email", lines=5, placeholder="Paste URL or email content here...")
         input_type = gr.Radio(["URL", "Email/Message"], label="Input Type")
 
-    result_output = gr.Textbox(label="Detection Result", lines=4, interactive=False)
+    result_output = gr.Textbox(label="Detection Result", lines=6, interactive=False)
     log_file_output = gr.File(label="Download Log File")
 
     detect_button = gr.Button("Detect")
 
-    detect_button.click(fn=run_detector, inputs=[input_text, input_type], outputs=[result_output, log_file_output])
+    detect_button.click(
+        fn=run_detector,
+        inputs=[input_text, input_type],
+        outputs=[result_output, log_file_output]
+    )
 
-    
 demo.launch(share=True)
 
 
+
+     
+
+
+