Broken Access Control in Flask with Dynamodb

Broken Access Control in a Flask application using Amazon DynamoDB typically arises when authorization checks are incomplete or bypassed before issuing DynamoDB operations. In this stack, the risk often maps to the BOLA/IDOR category in middleBrick’s 12-check set, where attackers manipulate object identifiers to access other users’ resources.

Consider a Flask route that retrieves a user profile by an user_id taken directly from the request (e.g., a URL parameter) and uses it as a key in a DynamoDB get_item call without verifying that the authenticated principal owns that user_id. Because the scan tests unauthenticated attack surfaces, middleBrick can detect when an endpoint accepts an ID and returns data without proper ownership validation, even if the caller never authenticates.

DynamoDB itself does not enforce object-level ownership; it enforces permissions at the table or item level via IAM policies and condition expressions. If the backend uses a shared IAM role with broad read permissions (for example, dynamodb:GetItem on the table) and relies solely on the application to filter by user_id, a missing or weak check results in Insecure Direct Object References (IDOR). An attacker can iterate over plausible IDs and enumerate other users’ data, a classic BOLA pattern that middleBrick flags with severity and remediation guidance.

Additionally, if the Flask app constructs DynamoDB requests using string interpolation or unsanitized input for table names or key attributes, attackers may force access to unintended partitions. For example, using an attacker-controlled value as a sort key prefix without validation can expose multiple items. middleBrick’s Input Validation and Property Authorization checks are designed to surface these risks by correlating spec definitions (OpenAPI) with runtime behavior, highlighting endpoints where identifiers flow unchecked into DynamoDB requests.

Insecure use of secondary indexes can also contribute. If a Global Secondary Index (GSI) is used and queries are not scoped with the partition key of the base table, an attacker might perform a query that returns items they should not see. The combination of Flask routing that does not enforce tenant or user context and DynamoDB query patterns that omit strict key conditions creates a path for unauthorized data access that middleBrick’s BOLA/IDOR and Property Authorization checks evaluate.

Finally, misconfigured CORS or missing CSRF protections in the Flask app can aid unauthorized requests from browsers, while the backend trusts the caller-supplied identifier. middleBrick’s unauthenticated scan can detect endpoints that return different data based on an ID parameter without confirming identity or ownership, emphasizing the need for robust access control integrated with DynamoDB key design.

Remediate Broken Access Control by enforcing ownership checks and scoping DynamoDB requests to the authenticated subject. Below are concrete, working examples for Flask using boto3 with DynamoDB.

1. Enforce ownership with partition key scoping

Ensure every DynamoDB operation includes the user identifier as part of the key, and validate that the incoming identifier matches the authenticated user’s ID before the request.

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

app = Flask(__name__)
# In production, use AWS credentials scoped with least privilege
TABLE_NAME = 'users'
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table(TABLE_NAME)

def get_current_user_id():
    # Replace with your auth logic (session, JWT, etc.)
    return request.headers.get('X-User-Id')

@app.route('/profile/<user_id>')
def get_profile(user_id):
    current_user_id = get_current_user_id()
    if not current_user_id or current_user_id != user_id:
        return jsonify({'error': 'access denied'}), 403
    response = table.get_item(Key={'user_id': user_id})
    item = response.get('Item')
    if item is None:
        return jsonify({'error': 'not found'}), 404
    return jsonify(item)

2. Use condition expressions for extra safety

When updating items, add a condition that the partition key matches the authenticated user to prevent accidental overwrites or confused deputy issues.

import boto3
from botocore.exceptions import ClientError

@app.route('/profile/<user_id>', methods=['PUT'])
def update_profile(user_id):
    current_user_id = get_current_user_id()
    if not current_user_id or current_user_id != user_id:
        return jsonify({'error': 'access denied'}), 403
    data = request.get_json()
    try:
        table.update_item(
            Key={'user_id': user_id},
            UpdateExpression='SET display_name = :val',
            ConditionExpression='user_id = :uid',
            ExpressionAttributeValues={':val': data['display_name'], ':uid': user_id},
        )
    except ClientError as e:
        if e.response['Error']['Code'] == 'ConditionalCheckFailedException':
            return jsonify({'error': 'conflict'}), 409
        raise
    return jsonify({'status': 'ok'})

3. Query with strict partition key and avoid broad scans

Design your DynamoDB schema so that user-specific queries always include the user_id as the partition key. Avoid Scan operations; use Query with a FilterExpression only after scoping by key.

@app.route('/messages/<user_id>')
def list_messages(user_id):
    current_user_id = get_current_user_id()
    if not current_user_id or current_user_id != user_id:
        return jsonify({'error': 'access denied'}), 403
    response = table.query(
        KeyConditionExpression='user_id = :uid',
        ExpressionAttributeValues={':uid': user_id}
    )
    return jsonify(response.get('Items', []))

4. Apply least-privilege IAM for the Flask role

Configure the IAM entity used by the Flask app to allow only necessary actions on specific resources. For example, restrict to dynamodb:GetItem and dynamodb:Query on the table with a condition on the partition key when possible.

# Example IAM policy snippet (not code executed by Flask)
{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "dynamodb:GetItem",
                "dynamodb:Query"
            ],
            "Resource": "arn:aws:dynamodb:region:account-id:table/users",
            "Condition": {
                "ForAllValues:StringEquals": {
                    "dynamodb:LeadingKeys": ["${cognito-identity.amazonaws.com:sub}"]
                }
            }
        }
    ]
}

5. Validate and normalize identifiers

Do not trust route parameters or query strings. Normalize and validate identifiers to prevent path traversal or injection-style key manipulation.

import re

def normalize_user_id(raw):
    # Allow only alphanumeric and underscore
    if not re.match(r'^[A-Za-z0-9_-]+$', raw):
        raise ValueError('invalid user_id')
    return raw

@app.route('/profile/<user_id>')
def get_profile(user_id):
    user_id = normalize_user_id(user_id)
    current_user_id = normalize_user_id(get_current_user_id())
    if current_user_id != user_id:
        return jsonify({'error': 'access denied'}), 403
    response = table.get_item(Key={'user_id': user_id})
    return jsonify(response.get('Item', {}))

By combining route-level ownership checks, strict key condition usage, least-privilege IAM, and input validation, the Flask + DynamoDB stack reduces the risk of IDOR and BOLA to align with middleBrick’s findings and remediation guidance.