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