Vengala Vinay

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Home » How We Audited a High-Traffic Shopify Enterprise Stack on Google Cloud and Mitigated Broken Object Level Authorization (BOLA) in API gateway endpoints

How We Audited a High-Traffic Shopify Enterprise Stack on Google Cloud and Mitigated Broken Object Level Authorization (BOLA) in API gateway endpoints

Auditing the Shopify Enterprise Stack on Google Cloud

Our engagement involved a high-traffic Shopify enterprise deployment hosted on Google Cloud Platform (GCP). The primary objective was to conduct a thorough security audit, with a specific focus on identifying and mitigating Broken Object Level Authorization (BOLA) vulnerabilities within the API Gateway endpoints that exposed custom Shopify functionalities and integrations.

The stack comprised a multi-tenant Shopify Plus instance, several custom microservices for inventory management, order fulfillment, and customer data synchronization, all orchestrated via Google Kubernetes Engine (GKE). API traffic was managed by Google Cloud API Gateway, which acted as the central ingress point for both internal and external API consumers.

Identifying BOLA in API Gateway Endpoints

BOLA, a critical OWASP Top 10 vulnerability, occurs when an application allows users to access objects they are not authorized to access. In our context, this meant a customer or an unauthorized user could potentially access or modify another customer’s order, inventory item, or sensitive profile data through our exposed APIs.

The audit methodology involved a combination of static code analysis, dynamic testing, and configuration review. We focused on API endpoints that handled sensitive resources, such as:

  • Order retrieval and modification endpoints (e.g., /api/v1/orders/{order_id})
  • Customer data access endpoints (e.g., /api/v1/customers/{customer_id})
  • Inventory management endpoints (e.g., /api/v1/inventory/{item_id})

The initial reconnaissance involved mapping out all API endpoints exposed through the API Gateway. We leveraged tools like Postman and Burp Suite to enumerate endpoints and understand their request/response structures. The key was to identify parameters that represented resource identifiers (e.g., order_id, customer_id).

Deep Dive: BOLA in a Sample Order Retrieval Endpoint

Consider a hypothetical endpoint for retrieving order details: GET /api/v1/orders/{order_id}. In a vulnerable implementation, the backend service might simply use the provided order_id to fetch data from the database without verifying if the authenticated user making the request is the legitimate owner of that order.

Our testing involved obtaining valid authentication tokens (e.g., JWTs issued by our identity provider) for two different customer accounts, Customer A and Customer B. We then attempted to retrieve an order belonging to Customer A using Customer B’s token, by manipulating the order_id path parameter.

A successful BOLA exploit would look like this:

Scenario: Customer B attempts to access Customer A’s order.

Request (using Customer B’s token):

GET /api/v1/orders/ORD1234567890 HTTP/1.1
Host: api.example.com
Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9... (Customer B's JWT)
Accept: application/json

If the backend service returned order details instead of a 403 Forbidden or 404 Not Found, BOLA was present.

Mitigation Strategy: API Gateway Authorization Policies

The most effective place to enforce BOLA checks for API Gateway-managed endpoints is at the gateway itself. This prevents unauthorized requests from even reaching the backend microservices, reducing the attack surface and the burden on individual service developers.

Google Cloud API Gateway supports custom authorizers and OpenAPI specification extensions for defining access control. For BOLA, we implemented checks by leveraging the JWT claims and by ensuring that the authenticated user’s identifier (e.g., user_id or customer_id) present in the JWT matched the owner of the requested resource.

Implementing Custom Authorizers with Cloud Functions

For complex authorization logic that couldn’t be expressed purely in OpenAPI, we deployed custom authorizers as Google Cloud Functions. These functions would receive the JWT, validate it, extract the user’s identity, and then perform additional checks based on the request path and method.

Example: Node.js Cloud Function for Order Authorization

const jwt = require('jsonwebtoken');
const { BigQuery } = require('@google-cloud/bigquery'); // Example: For checking ownership if not in JWT

const JWT_SECRET = process.env.JWT_SECRET;
const PROJECT_ID = process.env.PROJECT_ID;
const DATASET_ID = 'your_dataset';
const TABLE_ID = 'order_ownership'; // Table mapping order_id to customer_id

const bigquery = new BigQuery({ projectId: PROJECT_ID });

exports.authorizeOrderAccess = async (req, res) => {
  const token = req.headers.authorization && req.headers.authorization.split(' ')[1];
  if (!token) {
    return res.status(401).send('Unauthorized: No token provided');
  }

  try {
    const decoded = jwt.verify(token, JWT_SECRET);
    const authenticatedCustomerId = decoded.customerId; // Assuming customerId is in JWT

    // Extract order_id from the request path
    // This assumes the API Gateway passes the request path in a specific format
    // e.g., req.body.requestContext.http.path or similar, depending on gateway config
    const requestPath = req.body.requestContext.http.path; // Example path
    const orderIdMatch = requestPath.match(/^\/api\/v1\/orders\/([a-zA-Z0-9]+)$/);

    if (!orderIdMatch) {
      return res.status(400).send('Bad Request: Invalid order ID format');
    }
    const requestedOrderId = orderIdMatch[1];

    // --- BOLA Check ---
    // Option 1: If order ownership is directly in JWT (less common for dynamic resources)
    // if (decoded.ownedOrders && decoded.ownedOrders.includes(requestedOrderId)) {
    //   return res.status(200).send('Allow');
    // }

    // Option 2: Query a database/data store to verify ownership
    const query = `
      SELECT customer_id
      FROM \`${PROJECT_ID}.${DATASET_ID}.${TABLE_ID}\`
      WHERE order_id = @orderId AND customer_id = @customerId
    `;
    const options = {
      query: query,
      location: 'US',
      params: { orderId: requestedOrderId, customerId: authenticatedCustomerId },
    };

    const [rows] = await bigquery.query(options);

    if (rows.length > 0) {
      // Ownership verified
      return res.status(200).send('Allow');
    } else {
      // Ownership not verified
      return res.status(403).send('Forbidden: User does not own this order');
    }

  } catch (err) {
    console.error('Authorization error:', err);
    if (err.name === 'TokenExpiredError') {
      return res.status(401).send('Unauthorized: Token expired');
    }
    return res.status(500).send('Internal Server Error during authorization');
  }
};

This Cloud Function would be configured as a custom authorizer in the API Gateway’s OpenAPI specification.

OpenAPI Specification for API Gateway Integration

The OpenAPI (Swagger) definition for the API Gateway needs to be updated to reference the custom authorizer. For endpoints requiring BOLA checks, we’d add a security requirement.

swagger: '2.0'
info:
  title: Shopify Enterprise API
  version: 1.0.0
schemes:
  - https
host: api.example.com
paths:
  /api/v1/orders/{order_id}:
    get:
      summary: Get order details
      operationId: getOrderById
      produces:
        - application/json
      parameters:
        - name: order_id
          in: path
          required: true
          type: string
      security:
        - customAuth: [] # References the security scheme defined below
      responses:
        '200':
          description: Order details
          schema:
            $ref: '#/definitions/Order'
        '401':
          description: Unauthorized
        '403':
          description: Forbidden
        '404':
          description: Not Found
definitions:
  Order:
    type: object
    properties:
      id:
        type: string
      customer_id:
        type: string
      # ... other order properties

securityDefinitions:
  customAuth:
    x-google-backend:
      # This points to the Cloud Function deployed as an HTTP endpoint
      address: https://your-cloud-function-url.cloudfunctions.net/authorizeOrderAccess
      # If your Cloud Function requires authentication itself (e.g., IAM),
      # you might need to configure service accounts or other auth mechanisms here.
      # For a simple JWT authorizer, often no additional auth is needed for the function endpoint itself.
    type: api_key # This type is a placeholder; the actual mechanism is defined by x-google-backend
    name: Authorization # This name is also somewhat symbolic here, as the function reads headers directly

In this OpenAPI snippet:

  • security: - customAuth: [] declares that this endpoint requires authentication via the customAuth scheme.
  • securityDefinitions.customAuth defines how customAuth is implemented. x-google-backend is crucial here, pointing to the Cloud Function’s URL.

The API Gateway will intercept requests to GET /api/v1/orders/{order_id}, extract the JWT, and forward it (along with other request details) to the specified Cloud Function URL. The Cloud Function then performs the authorization logic and returns 200 Allow or 403 Forbidden to the API Gateway, which then either allows the request to the backend or denies it.

Backend Service-Level Safeguards

While the API Gateway is the primary defense, it’s prudent to implement defense-in-depth. Backend services should also validate that the authenticated user (identified from the JWT passed by the gateway) is authorized to access the requested resource. This acts as a crucial fallback if the gateway logic is bypassed or misconfigured.

Example: Python Backend Service (Flask)

from flask import Flask, request, jsonify
import jwt
import os

app = Flask(__name__)
JWT_SECRET = os.environ.get('JWT_SECRET')

# Assume a function to fetch order details from a database
def get_order_from_db(order_id):
    # ... database query logic ...
    # Returns {'order_id': '...', 'customer_id': '...', ...} or None
    pass

@app.route('/api/v1/orders/', methods=['GET'])
def get_order(order_id):
    auth_header = request.headers.get('Authorization')
    if not auth_header:
        return jsonify({'error': 'Authorization header missing'}), 401

    try:
        token = auth_header.split(' ')[1]
        decoded_token = jwt.decode(token, JWT_SECRET, algorithms=["HS256"])
        authenticated_customer_id = decoded_token.get('customerId')

        if not authenticated_customer_id:
            return jsonify({'error': 'Invalid token payload'}), 401

        order = get_order_from_db(order_id)

        if not order:
            return jsonify({'error': 'Order not found'}), 404

        # --- BOLA Check at Backend ---
        if order['customer_id'] != authenticated_customer_id:
            # Log this incident for security monitoring
            print(f"BOLA attempt detected: Customer {authenticated_customer_id} tried to access order {order_id} owned by {order['customer_id']}")
            return jsonify({'error': 'Forbidden'}), 403

        return jsonify(order), 200

    except jwt.ExpiredSignatureError:
        return jsonify({'error': 'Token expired'}), 401
    except jwt.InvalidTokenError:
        return jsonify({'error': 'Invalid token'}), 401
    except Exception as e:
        print(f"An unexpected error occurred: {e}")
        return jsonify({'error': 'Internal server error'}), 500

if __name__ == '__main__':
    app.run(debug=True, host='0.0.0.0', port=int(os.environ.get('PORT', 8080)))

This Python code demonstrates how the backend service extracts the JWT, verifies it, and then crucially compares the customer_id from the token against the customer_id associated with the requested order_id fetched from the database. Any mismatch triggers a 403 Forbidden response and a security alert.

Testing and Verification

Post-implementation, a rigorous testing phase is essential. This includes:

  • Positive Testing: Verifying that authorized users can access their own resources.
  • Negative Testing: Attempting to access resources belonging to other users, different customer accounts, or non-existent resources using various authentication states (valid tokens, expired tokens, no tokens).
  • Fuzzing: Using tools to send malformed requests to identify unexpected authorization bypasses.
  • Penetration Testing: Engaging external security experts to simulate real-world attacks against the API endpoints.

We utilized automated test suites integrated into our CI/CD pipeline to ensure that new deployments did not reintroduce BOLA vulnerabilities. These tests specifically targeted the API Gateway’s authorization logic and the backend service’s access control checks.

Conclusion

Securing high-traffic enterprise applications requires a multi-layered approach. By strategically implementing BOLA checks at the Google Cloud API Gateway using custom authorizers and reinforcing these with backend service-level validations, we significantly hardened the application against unauthorized data access. This case study highlights the importance of understanding API security primitives and leveraging cloud-native services for robust authorization enforcement.