app.py

import gradio as gr
import re
import html
from transformers import pipeline
import numpy as np

# Initialize pipelines
ocr = pipeline("image-to-text", model="microsoft/trocr-base-printed")  # Consider upgrading to trocr-large-printed
classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")  # Consider fine-tuning for phishing

# Common phishing indicators
SUSPICIOUS_PHRASES = [
    "urgent", "immediately", "password", "account locked", "wire transfer",
    "bank verification", "click here", "verification code", "credit card",
    "suspended", "login now", "reset your password", "act now", "unusual activity",
    "security alert", "confirm your identity", "gift card", "lottery winner"
]

# URL detection regex
URL_PATTERN = r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+'

def extract_text_from_image(image):
    if image is None:
        return ""
    try:
        result = ocr(image)
        return result[0]["generated_text"] if result else ""
    except Exception as e:
        return f"Error processing image: {str(e)}"

def analyze_text(text):
    if not text.strip():
        return "", "", gr.update(visible=False)
    
    # Zero-shot Classification
    candidate_labels = ["Phishing Email", "Legitimate Email"]
    result = classifier(text, candidate_labels=candidate_labels)
    
    label = result["labels"][0]
    confidence = result["scores"][0]
    
    # Determine risk level and styling
    if label == "Phishing Email":
        if confidence > 0.8:
            alert_html = """
                <div style="padding: 20px; background: linear-gradient(to right, #ffebee, #ffcdd2); 
                     border-radius: 12px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); margin-bottom: 20px;">
                    <div style="display: flex; align-items: center; gap: 12px;">
                        <span style="font-size: 24px;">⚠️</span>
                        <h3 style="color: #c62828; margin: 0; font-size: 18px;">High Risk Detected - Likely Phishing Attempt</h3>
                    </div>
                </div>
            """
        else:
            alert_html = """
                <div style="padding: 20px; background: linear-gradient(to right, #fff3e0, #ffe0b2); 
                     border-radius: 12px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); margin-bottom: 20px;">
                    <div style="display: flex; align-items: center; gap: 12px;">
                        <span style="font-size: 24px;">⚡</span>
                        <h3 style="color: #ef6c00; margin: 0; font-size: 18px;">Medium Risk - Suspicious Content Detected</h3>
                    </div>
                </div>
            """
    else:
        alert_html = """
            <div style="padding: 20px; background: linear-gradient(to right, #e8f5e9, #c8e6c9); 
                 border-radius: 12px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); margin-bottom: 20px;">
                <div style="display: flex; align-items: center; gap: 12px;">
                    <span style="font-size: 24px;">✅</span>
                    <h3 style="color: #2e7d32; margin: 0; font-size: 18px;">Low Risk - Likely Legitimate</h3>
                </div>
            </div>
        """
    
    # Find suspicious phrases and URLs
    found_phrases = []
    text_lower = text.lower()
    for phrase in SUSPICIOUS_PHRASES:
        if phrase in text_lower:
            found_phrases.append(phrase)
    
    urls = re.findall(URL_PATTERN, text)
    
    # Generate detailed analysis report with modern styling
    report = [
        "<div style='background: white; padding: 24px; border-radius: 12px; box-shadow: 0 2px 8px rgba(0,0,0,0.05);'>",
        "<h3 style='color: #1a237e; margin-top: 0;'>Analysis Details</h3>",
        f"<div style='display: flex; gap: 20px; margin-bottom: 20px;'>",
        f"<div style='flex: 1; padding: 16px; background: #f5f5f5; border-radius: 8px;'>",
        f"<strong>Confidence Score:</strong> {confidence:.1%}",
        "</div>",
        f"<div style='flex: 1; padding: 16px; background: #f5f5f5; border-radius: 8px;'>",
        f"<strong>Classification:</strong> {label}",
        "</div>",
        "</div>"
    ]
    
    if found_phrases or urls:
        report.append("<div style='margin-top: 20px;'>")
        if found_phrases:
            report.extend([
                "<h4 style='color: #d32f2f;'>🚩 Suspicious Elements Detected:</h4>",
                "<ul style='list-style-type: none; padding-left: 0;'>"
            ])
            for phrase in found_phrases:
                report.append(f"<li style='margin-bottom: 8px; padding: 8px 12px; background: #ffebee; border-radius: 6px;'>Found: '{html.escape(phrase)}'</li>")
            report.append("</ul>")
        
        if urls:
            report.extend([
                "<h4 style='color: #d32f2f;'>🔗 Detected URLs:</h4>",
                "<ul style='list-style-type: none; padding-left: 0;'>"
            ])
            for url in urls:
                report.append(f"<li style='margin-bottom: 8px; padding: 8px 12px; background: #e3f2fd; border-radius: 6px; word-break: break-all;'>{html.escape(url)}</li>")
            report.append("</ul>")
        report.append("</div>")
    else:
        report.append("<p style='color: #2e7d32;'>✅ No common suspicious phrases or URLs detected.</p>")
    
    report.append("<div style='margin-top: 20px; padding: 16px; background: #e3f2fd; border-radius: 8px;'>")
    if confidence > 0.9:
        report.append("<p style='margin: 0;'><strong>🔴 High confidence in classification - exercise extreme caution!</strong></p>")
    elif confidence > 0.7:
        report.append("<p style='margin: 0;'><strong>🟡 Moderate confidence - review carefully and verify sender.</strong></p>")
    else:
        report.append("<p style='margin: 0;'><strong>🟢 Low confidence - but always remain vigilant.</strong></p>")
    report.append("</div></div>")
    
    return alert_html, "\n".join(report), gr.update(visible=True)

def process_input(text_input, image_input):
    if text_input.strip():
        return analyze_text(text_input)
    
    if image_input is not None:
        extracted_text = extract_text_from_image(image_input)
        if extracted_text.strip():
            return analyze_text(extracted_text)
        return (
            """<div style="padding: 20px; background: #fff3e0; border-radius: 12px; margin-bottom: 20px;">
                <h3 style="color: #ef6c00; margin: 0;">⚠️ OCR Processing Error</h3>
            </div>""",
            "Could not extract text from image. Please ensure the image contains clear, readable text.",
            gr.update(visible=False)
        )
    
    return "", "Please provide either text or an image to analyze.", gr.update(visible=False)

# Custom theme
custom_theme = gr.themes.Soft().set(
    body_background_fill="#f8f9fa",
    block_background_fill="white",
    block_label_background_fill="*background-3",
    input_background_fill="white",
    button_primary_background_fill="#1a237e",
    button_primary_text_color="white",
    button_secondary_background_fill="#e0e0e0",
    button_secondary_text_color="#333",
)

# CSS for responsiveness and polish
custom_css = """
    .container { max-width: 1000px; margin: auto; }
    .header { text-align: center; margin-bottom: 2rem; }
    .tool-description { max-width: 800px; margin: 0 auto 2rem auto; }
    .input-section { margin-bottom: 2rem; }
    .analysis-section { margin-top: 2rem; }
    @media (max-width: 600px) {
        .header h1 { font-size: 1.8rem; }
        .input-section { padding: 0 10px; }
        .gr-button { width: 100%; margin-bottom: 10px; }
    }
"""

# Create Gradio interface
with gr.Blocks(theme=custom_theme, css=custom_css) as demo:
    gr.HTML("""
        <div class="header">
            <h1 style="color: #1a237e; font-size: 2.5rem; margin-bottom: 1rem;">🛡️ AI Phishing Guard</h1>
            <p style="color: #555; font-size: 1.2rem;">Protect yourself from phishing attempts with AI-powered analysis</p>
        </div>
    """)
    
    with gr.Row(equal_height=True):
        with gr.Column():
            gr.HTML("""
                <div class="tool-description">
                    <h3 style="color: #1a237e;">How to Use</h3>
                    <ol style="color: #555; line-height: 1.6;">
                        <li>Paste message text or upload a screenshot</li>
                        <li>Analyze instantly as you type or click 'Analyze' for images</li>
                        <li>Review the detailed results and stay cautious</li>
                    </ol>
                    <div style="background: #e3f2fd; padding: 16px; border-radius: 8px; margin-top: 1rem;">
                        <h4 style="color: #1a237e; margin-top: 0;">This tool detects:</h4>
                        <ul style="color: #555; margin-bottom: 0;">
                            <li>Suspicious language patterns</li>
                            <li>Common phishing phrases</li>
                            <li>URLs and potential threats</li>
                            <li>Urgency indicators</li>
                        </ul>
                    </div>
                </div>
            """)
    
    with gr.Tabs():
        with gr.TabItem("✏️ Text Input"):
            text_input = gr.Textbox(
                lines=8,
                label="Message Text",
                placeholder="Paste email or message content here...",
                elem_id="text_input"
            )
        
        with gr.TabItem("📷 Screenshot Upload"):
            image_input = gr.Image(
                label="Upload Screenshot",
                type="pil",
                elem_id="image_input"
            )
    
    with gr.Row():
        analyze_button = gr.Button("🔍 Analyze", variant="primary", size="lg")
        clear_button = gr.Button("🗑️ Clear", variant="secondary", size="lg")
    
    loading = gr.HTML("<div style='text-align: center; padding: 10px;'>Analyzing... <span>⏳</span></div>", visible=False)
    
    with gr.Column(visible=False) as output_col:
        alert_html = gr.HTML()
        analysis = gr.HTML()
    
    # Examples
    examples = [
        ["Subject: URGENT - Account Security Alert\n\nDear User,\n\nWe detected unusual activity in your account. Click here immediately to verify your identity and reset your password at https://fakebank.com/reset. If you don't respond within 24 hours, your account will be suspended.\n\nBank Security Team", None],
        ["Subject: Team Meeting Tomorrow\n\nHi everyone,\n\nJust a reminder that we have our weekly team meeting tomorrow at 10 AM in the main conference room. Please bring your project updates.\n\nBest regards,\nSarah", None],
    ]
    
    gr.Examples(
        examples=examples,
        inputs=[text_input, image_input],
        outputs=[alert_html, analysis, output_col],
        fn=process_input,
        cache_examples=True
    )
    
    # Event handlers
    def with_loading(*args):
        return (gr.update(visible=True), *process_input(*args), gr.update(visible=False))
    
    text_input.change(
        fn=process_input,
        inputs=[text_input, image_input],
        outputs=[alert_html, analysis, output_col]
    )
    analyze_button.click(
        fn=with_loading,
        inputs=[text_input, image_input],
        outputs=[loading, alert_html, analysis, output_col]
    )
    clear_button.click(
        fn=lambda: ("", None, "", "", gr.update(visible=False)),
        inputs=[],
        outputs=[text_input, image_input, alert_html, analysis, output_col]
    )

# Launch the app
if __name__ == "__main__":
    demo.launch()