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""" |
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Creating a REST API for predicting phishing probability of URLs. |
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Exposes POST /predict endpoint: |
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- Accepts JSON: {"url": "<URL>"} |
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- Returns JSON: {"phishing": <probability>} |
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Features: |
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- Interactive API docs available at /docs (Swagger UI) and /redoc (ReDoc) |
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- Automatic input validation |
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- Returns 400 if "url" is missing or invalid |
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- Returns 500 for unexpected errors |
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Usage: |
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1. Run the server: |
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uvicorn app:app --reload |
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2. Open browser to http://127.0.0.1:8000/docs to test endpoints interactively |
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""" |
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import sys |
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from pathlib import Path |
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sys.path.append(str(Path(__file__).resolve().parent.parent)) |
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import torch |
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from flask import Flask, request, jsonify |
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from data.tokenizer import url_to_ids |
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app = Flask(__name__) |
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model = torch.jit.load("./models/phish_model_ts.pt") |
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model.eval() |
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@app.route("/", methods=["GET"]) |
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def home(): |
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return """ |
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<!doctype html> |
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<html lang="en"> |
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<meta charset="utf-8"> |
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<meta name="viewport" content="width=device-width, initial-scale=1"> |
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<title>PhishGuard API</title> |
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<style> |
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body { |
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font-family: system-ui; |
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background: #f6f8fa; |
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margin: 2rem; |
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line-height: 1.6; |
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} |
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h1 { color: #d32f2f; } |
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pre { |
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background: #ebebeb; |
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padding: 1rem; |
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overflow-x: auto; |
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border-radius: 6px; |
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white-space: pre-wrap; |
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} |
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code { |
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background: #ebebeb; |
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padding: 2px 4px; |
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border-radius: 4px; |
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} |
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.step { margin: 1.2rem 0; } |
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</style> |
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<h1>PhishGuard API</h1> |
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<p> |
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This server predicts how <em>phishy</em> a URL is.<br> |
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Send a POST request to <code>/predict</code> with JSON: |
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</p> |
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<pre>{"url": "https://example.com"}</pre> |
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<p><i>Tip: Replace <code>https://example.com</code> with any URL you want to check.</i></p> |
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<h2>❶ Test in CMD / Terminal (5 seconds)</h2> |
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<div class="step"> |
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<b>Copy → paste → Enter:</b> |
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<pre> |
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curl -X POST http://127.0.0.1:8000/predict \ |
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-H "Content-Type: application/json" \ |
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-d "{\"url\": \"https://example.com\"}" |
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</pre> |
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<p><i>Replace the URL with the one you want to test.</i></p> |
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</div> |
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<h2>② GUI inside VS Code</h2> |
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<div class="step"> |
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<b>Using Thunder Client (free):</b><br> |
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1. Install "Thunder Client" from Extensions.<br> |
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2. New Request → POST<br> |
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3. URL: <code>http://127.0.0.1:8000/predict</code><br> |
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4. Body → Raw → JSON<br> |
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5. Paste:<br> |
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<code>{"url": "https://example.com"}</code><br> |
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6. Send. |
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</div> |
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<h2>③ Postman (any OS)</h2> |
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<div class="step"> |
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1. New Request → POST<br> |
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2. URL: <code>http://127.0.0.1:8000/predict</code><br> |
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3. Body → Raw → JSON<br> |
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4. Paste payload → Send. |
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</div> |
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<h2>What the number means</h2> |
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<ul> |
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<li>0.0 – 0.5 → likely <strong>safe</strong></li> |
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<li>0.5 – 1.0 → likely <strong>phishing</strong></li> |
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</ul> |
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<p>That's it — happy testing!</p> |
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</html> |
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""", 200 |
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@app.route("/predict", methods = ["POST"]) |
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def predict(): |
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"""Processing POST requests and returning phishing score""" |
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try: |
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data = request.get_json(force = True) |
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url = data.get("url") |
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ids = torch.tensor([url_to_ids(url)], dtype= torch.long) |
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with torch.no_grad(): |
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score = float(model(ids)[0]) |
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return jsonify({"phishing" : score}) |
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except Exception as e: |
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return jsonify({"error" : str(e)}), 500 |
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if __name__ == "__main__": |
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app.run(port=5000, debug = False) |
