---
title: Test
emoji: 🦀
colorFrom: green
colorTo: purple
sdk: docker
pinned: false
short_description: deepfakes
---

# Anti-Phishing AI Backend

FastAPI backend and HTML demo for phishing and deepfake detection. Built for hackathon.

## Stack
- **Framework**: FastAPI
- **AI Agent**: LangChain + Google Gemini 2.0 Flash (text, image, video, audio)
- **Deepfake APIs**: HuggingFace Inference API (image + audio)
- **Video**: Gemini Files API + frame-level HF image model

## Setup

```bash
cd antiphish
pip install -r requirements.txt
```

Copy the `.env` file from the parent directory or create one:
```
GEMINI_API_KEY=your_key_here
HUGGING_FACE_TOKEN=your_hf_token_here
```

## Run

```bash
uvicorn app.main:app --reload
```

- **API docs**: http://localhost:8000/docs
- **Demo frontend**: http://localhost:8000

## Walkthrough: How To Use

The Anti-Phishing AI app analyzes text, images, videos, and audio for phishing attempts, scams, and deepfakes.

### 1. Web Interface Walkthrough
When you open `http://localhost:8000`, you will see a simple user interface. Switch between tabs depending on the type of media you want to analyze:

* **Text & URLs:** Paste suspicious emails, SMS messages, or links. The app uses Gemini to detect urgency language, impersonation tactics, credential harvesting, and cross-references any URLs against suspicious top-level domains.
* **Images:** Upload an image (like a screenshot of a login page or a photo of a document). The app uses a HuggingFace model to detect if the face in the image is a deepfake, and Gemini Vision to see if the image is a fake login screen or brand impersonation.
* **Video:** Upload a short `.mp4` video. The app samples frames and runs deepfake diagnostics on them, while simultaneously uploading the video to Gemini to check for unnatural blinking, lip-sync inconsistencies, and visual anomalies.
* **Audio:** Upload an audio file (like a voicemail or recorded phone call). The HuggingFace integration checks the audio waveform for synthetic/AI-generated markers, while Gemini listens for common scam scripts (e.g., "fake bank security alert" or "tech support").

### 2. API / Developer Walkthrough
You can integrate this backend with another app or bot by sending requests directly to the API endpoints.

**Checking the API documentation:** All automated Swagger docs are at http://localhost:8000/docs.

**Testing the Text Endpoint via terminal:**
```bash
curl -X POST http://localhost:8000/analyze/text \
-H "Content-Type: application/json" \
-d '{"text": "URGENT: Your Paypal account has been locked. Click here to verify your identity: http://paypal-secure.ml/login"}'
```

**Testing the Image/Audio/Video Endpoints:**
For media, send the file as a `multipart/form-data` upload:
```bash
curl -X POST http://localhost:8000/analyze/image \
  -F "file=@/path/to/suspicious_image.jpg"
```

## Endpoints

| Method | Endpoint | Input | Description |
|---|---|---|---|
| POST | `/analyze/text` | JSON `{"text": "..."}` | Phishing text + URL detection |
| POST | `/analyze/image` | multipart file | Deepfake + phishing screenshot detection |
| POST | `/analyze/video` | multipart file | Deepfake video detection |
| POST | `/analyze/audio` | multipart file | Deepfake / AI voice detection |

## Response Format

```json
{
  "risk_score": 0.87,
  "risk_level": "HIGH",
  "threat_types": ["phishing", "urgency_language", "malicious_url"],
  "explanation": "Human-readable analysis from Gemini.",
  "tool_outputs": { ... }
}
```

`risk_level`: `LOW` (0-0.3) | `MEDIUM` (0.3-0.6) | `HIGH` (0.6-0.85) | `CRITICAL` (0.85-1.0)

## Models Used

| Modality | Model |
|---|---|
| Text / URL | Gemini 2.0 Flash (structured JSON prompt) |
| Image deepfake | `dima806/deepfake_vs_real_image_detection` (HF API) |
| Image phishing | Gemini Vision (multimodal) |
| Video deepfake | Gemini Files API + frame-sampled HF image model |
| Audio deepfake | `motheecreator/deepfake-audio-detection-v2` (HF API) |
| Audio voice scam | Gemini Audio (multimodal) |