Missing Authentication in Flask with Dynamodb

When a Flask application interacts with DynamoDB without enforcing authentication, it exposes an unauthenticated attack surface that can lead to unauthorized data access or mutation. middleBrick scans this scenario as part of its Authentication check, identifying whether endpoints invoke DynamoDB operations without verifying caller identity.

Consider a Flask route that retrieves user records directly from DynamoDB using a query parameter such as user_id:

from flask import Flask, request
import boto3
from botocore.exceptions import ClientError

app = Flask(__name__)
dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
table = dynamodb.Table('users')

@app.route('/user')
def get_user():
    user_id = request.args.get('user_id')
    try:
        response = table.get_item(Key={'user_id': user_id})
        return response.get('Item', {}), 200
    except ClientError as e:
        return {'error': str(e)}, 500

In this pattern, no authentication or authorization check precedes the DynamoDB call. An attacker can invoke the endpoint with any user_id, potentially enumerating other users’ records if primary key values are predictable. This maps to the OWASP API Top 10 category Broken Object Level Authorization (BOLA), where object-level permissions are missing or incomplete.

middleBrick’s scan would flag this as a high-severity finding because the unauthenticated path to DynamoDB allows identity bypass. The scanner does not assume a shared secret or token mechanism; it tests whether the endpoint enforces access control before data retrieval. If the route is publicly reachable and the primary key is guessable, the API becomes a channel for information disclosure, aligning with BOLA/IDOR checks.

Additionally, because DynamoDB permissions are often managed via IAM policies tied to resource-level ARNs, missing authentication can lead to over-permissive access if the backend credentials have broad privileges. The scanner’s Authentication check highlights this risk by verifying whether requests reach DynamoDB without any identity validation, prompting remediation to enforce controls before the database call.

To remediate missing authentication when calling DynamoDB from Flask, enforce identity verification and principle-of-least-privilege access before any database operation. Below are concrete, syntactically correct examples demonstrating how to integrate authentication and scoped permissions.

1. Enforce token-based authentication before DynamoDB access

Validate an API key or JWT before proceeding to DynamoDB. This ensures only authenticated principals can invoke the endpoint:

from flask import Flask, request, jsonify
import boto3
from functools import wraps

app = Flask(__name__)
dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
table = dynamodb.Table('users')

def require_auth(f):
    @wraps(f)
    def decorated(*args, **kwargs):
        auth = request.headers.get('Authorization')
        if not auth or not auth.startswith('Bearer '):
            return jsonify({'error': 'Missing or invalid token'}), 401
        token = auth.split(' ')[1]
        if not validate_token(token):  # implement validate_token per your auth provider
            return jsonify({'error': 'Unauthorized'}), 403
        return f(*args, **kwargs)
    return decorated

def validate_token(token):
    # Replace with actual token validation logic (e.g., verify JRS, introspect OAuth)
    return token == 'valid_secure_token'

@app.route('/user')
@require_auth
def get_user():
    user_id = request.args.get('user_id')
    try:
        response = table.get_item(Key={'user_id': user_id})
        item = response.get('Item')
        if not item:
            return jsonify({'error': 'Not found'}), 404
        # Ensure the requesting user can only access their own data
        if item.get('user_id') != user_id:
            return jsonify({'error': 'Forbidden: cannot access other user data'}), 403
        return item, 200
    except Exception as e:
        return jsonify({'error': str(e)}), 500

2. Apply scoped IAM policies and condition keys in DynamoDB requests

Even with authentication, the backend role used by boto3 should have tightly scoped permissions. Use condition keys to enforce ownership at the database level, adding defense in depth:

import boto3
from flask import current_app

def get_user_data_safe(user_id, requester_id):
    # Assume the Flask app config holds the IAM role credentials
    session = boto3.Session(
        aws_access_key_id=current_app.config['AWS_ACCESS_KEY'],
        aws_secret_access_key=current_app.config['AWS_SECRET_KEY'],
        region_name='us-east-1'
    )
    dynamodb = session.resource('dynamodb')
    table = dynamodb.Table('users')
    # Use a condition expression to ensure users can only fetch their own records
    response = table.get_item(
        Key={'user_id': user_id},
        ConditionExpression='user_id = :requester',
        ExpressionAttributeValues={':requester': requester_id}
    )
    return response.get('Item', {})

In this pattern, the condition expression enforces ownership at the DynamoDB layer, so even if a token is compromised, the scope is limited to the user’s own data. middleBrick’s Pro plan supports continuous monitoring of such configurations, helping detect regressions in authentication and authorization rules across scans.

For teams integrating into CI/CD, the middleBrick GitHub Action can add API security checks to pipelines, failing builds if risk scores drop below a configured threshold. This ensures that changes introducing authentication gaps are caught before deployment. The CLI tool also allows on-demand scans from the terminal with middlebrick scan <url>, providing JSON or text output for scripting and automation.