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from fastapi import FastAPI, HTTPException
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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import httpx
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import os
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app = FastAPI(title="Phishing Detection API")
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["https://phishing-detector-frontend-eight.vercel.app"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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HF_TOKEN = os.getenv("HF_TOKEN")
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HF_MODEL_ID = os.getenv("HF_MODEL_ID", "swathi6016/phishing-detector1")
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HF_API_URL = f"https://api-inference.huggingface.co/models/{HF_MODEL_ID}"
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class URLRequest(BaseModel):
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url: str
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@app.get("/")
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async def root():
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"""Root endpoint"""
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return {
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"message": "Phishing Detection API",
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"status": "running",
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"model": "DistilBERT via HuggingFace",
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"endpoints": {
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"check": "POST /check",
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"health": "GET /health",
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"docs": "GET /docs"
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}
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}
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@app.get("/health")
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async def health():
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"""Health check"""
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return {
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"status": "healthy",
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"model": HF_MODEL_ID,
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"hf_token_set": bool(HF_TOKEN)
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}
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@app.post("/check")
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async def check_url(request: URLRequest):
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"""Check if URL is phishing"""
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if not HF_TOKEN:
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raise HTTPException(
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status_code=500,
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detail="HF_TOKEN not configured"
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)
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url = request.url.strip()
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if not url:
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raise HTTPException(status_code=400, detail="URL is required")
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try:
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headers = {"Authorization": f"Bearer {HF_TOKEN}"}
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payload = {"inputs": url}
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async with httpx.AsyncClient(timeout=30.0) as client:
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response = await client.post(HF_API_URL, headers=headers, json=payload)
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if response.status_code == 503:
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raise HTTPException(
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status_code=503,
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detail="Model is loading. Please try again in 20 seconds."
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)
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if response.status_code != 200:
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raise HTTPException(
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status_code=response.status_code,
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detail=f"HuggingFace API error: {response.text}"
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)
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result = response.json()
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if isinstance(result, list) and len(result) > 0:
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predictions = result[0] if isinstance(result[0], list) else result
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phishing_score = 0.0
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legitimate_score = 0.0
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for pred in predictions:
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label = str(pred.get("label", "")).lower()
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score = float(pred.get("score", 0.0))
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if "1" in label or "phishing" in label:
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phishing_score = score
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elif "0" in label or "legitimate" in label or "legit" in label:
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legitimate_score = score
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is_phishing = phishing_score > legitimate_score
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confidence = max(phishing_score, legitimate_score)
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if phishing_score > 0.8:
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risk_level = "HIGH RISK"
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elif phishing_score > 0.5:
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risk_level = "MEDIUM RISK"
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else:
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risk_level = "LOW RISK"
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return {
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"url": url,
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"is_phishing": is_phishing,
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"phishing_probability": phishing_score,
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"legitimate_probability": legitimate_score,
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"confidence": confidence,
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"prediction": "PHISHING" if is_phishing else "LEGITIMATE",
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"risk_level": risk_level
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}
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else:
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raise HTTPException(
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status_code=500,
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detail="Unexpected response format from model"
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)
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except httpx.TimeoutException:
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raise HTTPException(status_code=504, detail="Request timeout")
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except httpx.RequestError as e:
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raise HTTPException(status_code=500, detail=f"Connection error: {str(e)}")
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except HTTPException:
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raise
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Error: {str(e)}")
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if __name__ == "__main__":
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import uvicorn
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port = int(os.environ.get("PORT", 8000))
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uvicorn.run(app, host="0.0.0.0", port=port) |
