Missing Authentication in Django with Dynamodb

Missing authentication in a Django application that uses DynamoDB as a backend creates a risk where unauthenticated requests can directly invoke DynamoDB operations. In this context, the API surface often includes endpoint handlers that call DynamoDB without first validating identity or enforcing scoped permissions. Because DynamoDB is a managed key-value and document store, low-level API calls such as get_item, query, and scan can return sensitive data if the caller provides a valid primary key even without proving their identity.

Consider a Django view that retrieves a user profile by user_id from DynamoDB without authentication:

import boto3
from django.http import JsonResponse

dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
table = dynamodb.Table('UserProfiles')

def get_profile(request, user_id):
    response = table.get_item(Key={'user_id': user_id})
    item = response.get('Item', {})
    return JsonResponse(item)

If this view is mapped to a public endpoint and no authentication/authorization check is performed, an unauthenticated attacker can enumerate or exfiltrate other users’ data by iterating over known or guessed user_id values. This maps to the BOLA/IDOR category in middleBrick’s checks and is often flagged when the scanner observes that a DynamoDB operation is invoked without an authenticated context.

Moreover, DynamoDB’s permission model is separate from application-level authentication. Even if Django does not enforce login requirements, IAM policies associated with the credentials used by boto3 may be overly permissive, allowing broad read or write access. When combined with missing Django decorators like @login_required or permission classes, this separation can expose sensitive operations. middleBrick’s Authentication check detects whether endpoints invoke backend services like DynamoDB while bypassing identity verification, and its BOLA/IDOR check validates whether authorization is enforced per resource.

Real-world attack patterns include enumeration via predictable integer or UUID identifiers, privilege escalation through tampering with session references, and data exposure across tenant boundaries. Because DynamoDB does not natively enforce row-level ownership, developers must implement tenant or user scoping in application code. Failing to do so results in findings across multiple middleBrick checks: Authentication, BOLA/IDOR, and Property Authorization.

Remediation focuses on enforcing authentication and scoping every DynamoDB operation with the requester’s identity. In Django, use built-in decorators or permission classes to ensure that the authenticated user’s identity is verified before any DynamoDB call.

First, enforce authentication with @login_required and scope queries to the requesting user:

from django.contrib.auth.decorators import login_required
import boto3
from django.http import JsonResponse
from django.core.exceptions import PermissionDenied

dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
table = dynamodb.Table('UserProfiles')

@login_required
def get_profile(request, user_id):
    # Ensure the requesting user can only access their own profile
    if str(request.user.id) != user_id:
        raise PermissionDenied('You can only access your own profile')
    response = table.get_item(Key={'user_id': user_id})
    item = response.get('Item', {})
    return JsonResponse(item)

This pattern ensures that both Django’s authentication layer and per-request scoping are applied. The check str(request.user.id) != user_id enforces tenant isolation at the application level, which DynamoDB alone does not provide.

For class-based views, use Django REST Framework’s permission classes and pass the request user into the DynamoDB key:

from rest_framework.permissions import IsAuthenticated
from rest_framework.views import APIView
from rest_framework.response import Response
import boto3

class UserProfileView(APIView):
    permission_classes = [IsAuthenticated]
    dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
    table = dynamodb.Table('UserProfiles')

    def get(self, request, user_id):
        # Scope to the requesting user
        if str(request.user.id) != user_id:
            return Response({'error': 'Forbidden'}, status=403)
        response = self.table.get_item(Key={'user_id': user_id})
        return Response(response.get('Item', {}))

When using DynamoDB with fine-grained access control, consider scoped credentials or temporary tokens. For example, if you rely on Cognito identities, map the authenticated identity ID to a partition key prefix and enforce it in queries:

import boto3
from django.http import JsonResponse
from django.contrib.auth.decorators import login_required

# Assumes the authenticated identity ID is stored on the user model or obtained via Cognito
@login_required
def list_user_items(request):
    identity_id = request.user.cognito_identity_id  # e.g., 'us-east-1:xxx-xxx'
    dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
    table = dynamodb.Table('UserItems')
    # Prefix the partition key to enforce tenant isolation
    response = table.query(
        KeyConditionExpression='pk = :pk',
        ExpressionAttributeValues={':pk': identity_id}
    )
    return JsonResponse(response.get('Items', []), safe=False)

These examples demonstrate how to bind DynamoDB operations to the authenticated principal in Django. middleBrick’s checks complement this by verifying that authentication is present, that access patterns include identity scoping, and that outputs do not leak sensitive information. Because the scanner operates without credentials, it tests the unauthenticated attack surface; once you implement these controls, re-scan with the middleBrick CLI or Web Dashboard to confirm that findings are resolved.