Broken Access Control in Loopback with Dynamodb

Broken Access Control (BAC) occurs when API endpoints fail to enforce proper authorization checks, allowing one user to access or modify another user's data. In a Loopback application using DynamoDB as the persistence layer, this risk is amplified by misconfigured model ACLs, weak role-based checks, and over-permissive IAM policies that grant broader read/write access than intended.

Loopback’s dynamic model definitions and built-in REST APIs can expose endpoints that assume authentication is sufficient for authorization. If an endpoint like /users/{id} relies only on request context.userId without validating that the userId matches the record owner or required scopes, an attacker can manipulate the parameter to access other users’ DynamoDB items. Because DynamoDB does not enforce row-level permissions natively, these checks must be implemented in application code; missing or inconsistent checks result in BOLA/IDOR flaws.

DynamoDB’s schema-less design can also contribute. When access patterns are derived from client-supplied identifiers without server-side validation, an attacker may traverse IDs (sequential or predictable keys) to enumerate resources. For example, if a Loopback model uses a string hash as a partition key but does not scope queries by the authenticated subject, a request for partitionKey = clientSuppliedId might return data across users if the application fails to append the user-specific prefix.

Insecure IAM roles attached to the Lambda or EC2 instance running Loopback can further widen the impact. Overly permissive policies (e.g., dynamodb:GetItem without a condition on the user identifier) allow any compromised credential to read or write many records. A misconfigured service role may also allow wildcard actions on DynamoDB tables, enabling privilege escalation through BFLA (Business Logic Flaws Abuse).

To detect these patterns, middleBrick runs parallel checks including Authentication, BOLA/IDOR, and Privilege Escalation while analyzing OpenAPI specs and runtime behavior. It highlights where Loopback routes interact with DynamoDB without proper ownership validation and maps findings to OWASP API Top 10 and compliance frameworks, providing remediation guidance rather than attempting automatic fixes.

Remediation focuses on ensuring every DynamoDB operation is scoped to the authenticated subject and validated server-side. Below are concrete patterns using the AWS SDK for JavaScript in a Loopback model.

1. Scope queries by user ID

Always append the user identifier to the key condition. Avoid relying solely on client-supplied IDs.

const AWS = require('aws-sdk');
const dynamo = new AWS.DynamoDB.DocumentClient();

async function getUserProfile(userId, requestingUserId) {
  // Enforce ownership: userId must match requestingUserId
  if (userId !== requestingUserId) {
    const err = new Error('Unauthorized');
    err.statusCode = 403;
    throw err;
  }
  const params = {
    TableName: process.env.USERS_TABLE,
    Key: {
      pk: `USER#${userId}`, // Partition key scoped to user
      sk: 'PROFILE'          // Sort key
    }
  };
  const { Item } = await dynamo.get(params).promise();
  if (!Item) {
    const err = new Error('Not found');
    err.statusCode = 404;
    throw err;
  }
  return Item;
}

2. Use condition expressions for writes

Prevent accidental overwrites or privilege escalation by ensuring the item belongs to the user.

async function updateUserEmail(userId, email, requestingUserId) {
  if (userId !== requestingUserId) {
    const err = new Error('Unauthorized');
    err.statusCode = 403;
    throw err;
  }
  const params = {
    TableName: process.env.USERS_TABLE,
    Key: {
      pk: `USER#${userId}`,
      sk: 'PROFILE'
    },
    UpdateExpression: 'SET email = :email',
    ConditionExpression: 'attribute_exists(pk)', // Ensure item exists
    ExpressionAttributeValues: {
      ':email': email
    }
  };
  await dynamo.update(params).promise();
  return { email };
}

3. Enforce fine-grained IAM policies

Apply least privilege at the IAM role level. Attach policies that restrict DynamoDB actions to specific resource ARNs and include conditions for user context when possible.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "dynamodb:GetItem",
        "dynamodb:PutItem",
        "dynamodb:UpdateItem"
      ],
      "Resource": "arn:aws:dynamodb:region:account:table/users-table",
      "Condition": {
        "ForAllValues:StringEquals": {
          "dynamodb:LeadingKeys": ["${aws:username}"]
        }
      }
    }
  ]
}

4. Validate and normalize keys in Loopback connectors

Configure the Loopback connector to enforce key patterns and avoid injection via model settings.

{
  "name": "db",
  "connector": "loopback-connector-dynamodb",
  "options": {
    "region": "us-east-1",
    "hashKeyName": "pk",
    "hashKeyType": "string",
    "rangeKeyName": "sk",
    "create": false
  }
}

These steps reduce the likelihood of Broken Access Control by ensuring ownership checks are mandatory, keys are well-structured, and IAM permissions follow least privilege. middleBrick’s scans can surface missing ownership validations and overly permissive IAM roles, with findings tied to specific frameworks and actionable guidance.