Credential Stuffing in Django

Credential stuffing attacks target the login endpoint of a Django application by automating requests with large lists of username/password pairs harvested from previous breaches. Because Django’s default authentication backend (django.contrib.auth.backends.ModelBackend) checks credentials against the database using check_password, an attacker can iterate through millions of combos if the view lacks any throttling or anomaly detection.

Typical vulnerable code paths include:

• A custom login view that directly calls authenticate(request, username=username, password=password) without checking request frequency.
• The built‑in django.contrib.auth.views.LoginView when used without additional throttling middleware.
• API endpoints built with Django REST Framework that expose obtain_auth_token or TokenObtainPairView (JWT) and rely solely on serializer validation.

When successful, the attacker gains an authenticated session (session cookie or token) and can perform actions as the compromised user. This maps to OWASP API2:2019 Broken Authentication and has been observed in real‑world incidents such as the 2020 credential stuffing campaign against multiple SaaS platforms that used Django‑based backends.

Detecting credential stuffing in Django requires observing patterns that differ from normal user behavior: a high volume of failed logins from a single IP address or targeting many usernames with the same password, and vice‑versa. Django provides several hooks for visibility:

• The user_login_failed signal fires on every failed authentication attempt.
• Custom middleware can inspect request.META['REMOTE_ADDR'] and the submitted username to count failures.
• Django’s logging (LOGGING configuration) can capture authentication warnings from django.contrib.auth.

Example detection middleware that logs and thresholds failed attempts:

# middleware/credential_stuffing.py
from django.core.cache import cache
from django.http import HttpResponseTooManyRequests
import hashlib

class CredentialStuffingMiddleware:
    def __init__(self, get_response):
        self.get_response = get_response
        self.limit = 10   # attempts
        self.window = 60  # seconds

    def __call__(self, request):
        if request.path == '/accounts/login/' and request.method == 'POST':
            ip = request.META.get('REMOTE_ADDR', '0.0.0.0')
            username = request.POST.get('username', '')
            key = f'login_fail:{ip}:{hashlib.sha256(username.encode()).hexdigest()}'
            fails = cache.get(key, 0)
            if fails >= self.limit:
                return HttpResponseTooManyRequests('Too many login attempts')
        response = self.get_response(request)
        return response

    def process_response(self, request, response):
        if request.path == '/accounts/login/' and request.method == 'POST':
            if response.status_code == 401 or response.status_code == 403:
                ip = request.META.get('REMOTE_ADDR', '0.0.0.0')
                username = request.POST.get('username', '')
                key = f'login_fail:{ip}:{hashlib.sha256(username.encode()).hexdigest()}'
                cache.incr(key, delta=1)
                cache.expire(key, self.window)
        return response

When this middleware is added to MIDDLEWARE, it will begin throttling after ten failed attempts from the same IP/username pair within a minute.

middleBrick can detect credential‑stuffing risk without any code changes: by submitting the API URL, the scanner performs unauthenticated black‑box tests that include rapid credential spraying against login endpoints. If the endpoint responds with successful authentication (200 OK) for multiple guessed pairs, middleBrick reports a finding under the “Authentication” category with severity High, includes the observed success rate, and provides remediation guidance.

Effective mitigation combines Django’s native security features with disciplined rate limiting and monitoring. The following steps are recommended:

1. Use Django’s built‑in authentication views (LoginView) and ensure they are protected by a throttling mechanism.
2. Implement per‑IP and/or per‑username rate limiting via middleware or a third‑party package such as django-ratelimit.
3. Employ constant‑time comparison for any custom password checks to avoid timing attacks (django.utils.crypto.constant_time_compare).
4. Enable the user_login_failed signal to alert on anomalous patterns (e.g., sudden spike in failures).
5. Consider account lockout after a configurable number of failed attempts, but combine with CAPTCHA to prevent denial‑of‑service.
6. Regularly review Django’s security releases; patches for authentication‑related issues are issued as CVEs (e.g., CVE-2020-XXXXX for password‑reset token handling).

Example of a throttled login view using django-ratelimit:

# views.py
from django.contrib.auth.views import LoginView
from django_ratelimit.decorators import ratelimit

@ratelimit(key='ip', rate='5/m', method='POST', block=True)
class ThrottledLoginView(LoginView):
    template_name = 'registration/login.html'
    # AuthenticationForm is used by default; ensures constant‑time password checking

# urls.py
from django.urls import path
from .views import ThrottledLoginView

urlpatterns = [
    path('accounts/login/', ThrottledLoginView.as_view(), name='login'),
]

If you prefer not to add external dependencies, the custom middleware shown in the Detection section can be extended to return a 429 response and optionally present a CAPTCHA challenge.

After applying these controls, re‑run middleBrick (e.g., middlebrick scan https://api.example.com) to verify that the Authentication score improves. The tool will continue to report any residual risk, allowing you to track progress over time via the Dashboard or through the GitHub Action that can fail a build if the score drops below your defined threshold.