---
title: Backend Authentication and Logging Status
type: note
permalink: development/backend-authentication-and-logging-status
---

# Backend Authentication and Logging Status

## Current State (December 2025)

### Authentication
**Status:** ❌ No user authentication system implemented

The backend currently has:
- **Referer validation only** - checks if requests come from allowed frontend origins
- **Test password bypass** - allows curl/debugging with `X-Test-Password` header
- **No user concept** - no user IDs, sessions, or accounts

Current validation (`_validate_referer` function):
```python
allowed_referers = [
    "https://kinemotion.vercel.app",
    "http://localhost:5173",
    # ... other dev origins
]
```

### Logging
**Status:** ⚠️ Basic print() debugging only

Current logging approach:
- Uses `print()` statements for debugging
- Logs: jump_type, filename, metrics, errors
- No structured logging framework
- No user tracking (because no users exist)

Examples from code:
```python
print(f"DEBUG: Received jump_type={jump_type}, file={file.filename}")
print(f"Error during video analysis: {error_detail}")
```

### Security Gaps

1. **No user identity tracking** - can't audit who performed actions
2. **No authentication tokens** - relies on referer header (easily spoofed)
3. **No structured logging** - difficult to correlate events or track patterns
4. **Rate limiting by IP only** - can't track per-user usage

## Future Recommendations

### 1. Implement JWT Authentication

**Libraries to consider:**
- `fastapi-users` - Full user management solution
- `python-jose` - JWT token handling
- `passlib` - Password hashing

**Example pattern:**
```python
from fastapi import Depends
from fastapi.security import OAuth2PasswordBearer

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="/login")

@app.post("/api/analyze")
async def analyze_video(
    token: str = Depends(oauth2_scheme),
    # ... other params
):
    user_id = verify_token(token)
    logger.info("Video analysis started", extra={"user_id": user_id})
    # ... process video
```

### 2. Add Structured Logging

**Replace print() with:**
```python
import logging
import structlog

logger = structlog.get_logger()

# In endpoints:
logger.info(
    "video_analysis_started",
    user_id=user_id,
    jump_type=jump_type,
    filename=file.filename,
    request_id=request_id,
)
```

### 3. Add Request Context Middleware

**Track user across entire request:**
```python
from starlette_context import context, plugins
from starlette_context.middleware import ContextMiddleware

app.add_middleware(
    ContextMiddleware,
    plugins=(
        plugins.RequestIdPlugin(),
        plugins.UserIdPlugin(),  # Custom plugin
    )
)
```

### 4. Audit Trail for Security Events

**Log security-sensitive operations:**
- Video uploads (with user_id, timestamp, file details)
- Failed authentication attempts
- Rate limit violations
- Configuration changes

## Related Documentation

- Backend README mentions: "Add authentication and rate limiting if needed" (future work)
- See `backend/docs/setup.md` line 366 for authentication TODO
- FastAPI Users docs: https://github.com/fastapi-users/fastapi-users

## References

- FastAPI JWT Auth: https://testdriven.io/blog/fastapi-jwt-auth/
- Structured logging: https://www.structlog.org/
- FastAPI Users: https://fastapi-users.github.io/fastapi-users/

---

**Tags:** #backend #security #authentication #logging #audit-trail
**Status:** Current state documented - implementation pending
**Date:** December 2, 2025
