Credential Stuffing in Dynamodb

Credential stuffing attacks against APIs backed by Amazon Dynamodb typically exploit two weaknesses: inadequate authentication enforcement at the application layer and overly permissive access controls at the database layer. Attackers use lists of compromised credentials (from previous breaches) to gain unauthorized access to user accounts. In a Dynamodb context, this often manifests through API endpoints that directly expose database query operations without robust authorization checks.

A common vulnerable pattern is an API endpoint that retrieves user data by accepting a user identifier (e.g., userId) and constructing a Dynamodb GetItem or Query operation without verifying that the authenticated user is authorized to access that specific item. For example, a Node.js Lambda function might look like this:

// VULNERABLE: No authorization check on userId
const AWS = require('aws-sdk');
const dynamodb = new AWS.DynamoDB.DocumentClient();

exports.handler = async (event) => {
  const userId = event.pathParameters.userId; // Attacker-controlled
  const params = {
    TableName: 'Users',
    Key: { userId: userId }
  };
  const result = await dynamodb.get(params).promise();
  return { statusCode: 200, body: JSON.stringify(result.Item) };
};

Here, any authenticated user (or even an unauthenticated attacker if the endpoint is public) can supply any userId and retrieve data. This is a classic Broken Object Level Authorization (BOLA/IDOR) flaw (OWASP API Top 10:2023 #1). The underlying Dynamodb table might have no additional access controls beyond the IAM role attached to the Lambda, which often has broad dynamodb:GetItem permissions.

Another vector is exploiting predictable partition keys. Dynamodb requires a primary key (partition key, optionally with sort key). If an application uses sequential numbers, email addresses, or other guessable values as the partition key, an attacker can systematically enumerate accounts by trying different keys, a form of Insecure Direct Object Reference. For instance, if userId is an integer auto-incremented by the application, an attacker can script requests with userId=1, userId=2, etc., to harvest data.

Finally, if the API uses a shared or weak secret (like a static API key) for authentication and that secret is leaked or guessed, an attacker can perform credential stuffing at scale against the entire user base, effectively bypassing per-user authentication entirely. The Dynamodb table's IAM policy might allow the dynamodb:Scan action for that role, enabling bulk data exfiltration.

Detecting credential stuffing vulnerabilities in Dynamodb-backed APIs requires testing for BOLA/IDOR and weak authentication. Manual testing involves attempting to access resources belonging to other users by manipulating identifiers in API requests. However, automated scanning is more efficient. A scanner must understand the API's contract (e.g., OpenAPI spec) to identify endpoints that accept object identifiers and then probe them for authorization bypasses.

middleBrick performs this detection through its BOLA/IDOR check. When you submit an API endpoint URL, it analyzes the OpenAPI/Swagger specification (if available) to identify parameters that likely reference objects (like /users/{userId}). It then sends sequential test requests, substituting the target identifier with values from other authenticated users (or using a provided authentication token) to see if the API returns data it shouldn't. For Dynamodb-specific contexts, the scanner also looks for common query patterns that map directly to Dynamodb operations, such as presence of TableName, Key, or ExpressionAttributeValues in request/response payloads, which indicate direct database access.

To scan your own API, use the middleBrick CLI tool:

middlebrick scan https://api.yourdomain.com/v1/users/{userId} --token "your_auth_token"

The --token flag provides an authenticated session so the scanner can test horizontal privilege escalation (accessing other users' data). The resulting report includes a BOLA/IDOR section with a severity score and specific endpoints where object-level authorization was bypassed. For Dynamodb-backed APIs, findings often include the exact request that leaked data and the response containing another user's information, mapped to the Dynamodb table operation that likely occurred.

The scanner also checks for authentication weaknesses that facilitate credential stuffing, such as lack of rate limiting on login endpoints (which middleBrick's Rate Limiting check assesses) and weak password policies (inferred from response patterns). If the API uses an LLM component (e.g., for chat-based support), middleBrick's unique LLM/AI Security checks would additionally probe for system prompt leakage or injection that could reveal Dynamodb connection details.

Remediation for credential stuffing in Dynamodb APIs centers on enforcing authorization at the application layer and securing database access. The primary fix is to implement robust resource ownership checks in every endpoint that accesses user-specific data. Never trust client-provided identifiers; always compare them against the authenticated user's identity from the session or token.

Here is a secure Node.js Lambda example using AWS SDK and a hypothetical authentication middleware that sets event.requestContext.authorizer.claims.sub as the authenticated user ID:

// SECURE: Compare requested userId with authenticated user
const AWS = require('aws-sdk');
const dynamodb = new AWS.DynamoDB.DocumentClient();

const authorizeUser = (event) => {
  const authUserId = event.requestContext.authorizer.claims.sub;
  const requestedUserId = event.pathParameters.userId;
  if (authUserId !== requestedUserId) {
    throw new Error('Unauthorized');
  }
};

exports.handler = async (event) => {
  authorizeUser(event); // Enforce ownership
  const userId = event.pathParameters.userId;
  const params = {
    TableName: 'Users',
    Key: { userId: userId }
  };
  const result = await dynamodb.get(params).promise();
  return { statusCode: 200, body: JSON.stringify(result.Item) };
};

Additionally, apply the principle of least privilege to the IAM role used by your compute environment (Lambda, EC2, etc.). The IAM policy should grant only the specific Dynamodb actions (dynamodb:GetItem, dynamodb:Query) on the exact tables and indexes required, and only for items where the partition key matches the user's ID if possible using condition keys. For example:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": ["dynamodb:GetItem"],
      "Resource": "arn:aws:dynamodb:*:*:table/Users",
      "Condition": {
        "ForAllValues:StringEquals": {
          "dynamodb:LeadingKeys": ["${aws:PrincipalTag/userId}"]
        }
      }
    }
  ]
}

This policy uses IAM condition keys to restrict access to items where the partition key equals the principal's tagged userId. You must tag the IAM principal (e.g., the Lambda execution role) with the appropriate user ID at runtime, which requires integration with your authentication system.

Other critical Dynamodb-specific measures include:

• Encryption at rest and in transit: Enable AWS-managed or customer-managed KMS encryption for the table and enforce TLS for all connections.
• Fine-grained access control with IAM: Avoid using root credentials; use IAM roles with scoped permissions.
• Input validation: Sanitize and validate all user-supplied input before using it in Dynamodb operations to prevent injection (though Dynamodb is generally resistant to SQL injection, it is vulnerable to expression injection if using filter expressions).
• Monitoring and alerting: Enable Dynamodb Streams and CloudWatch metrics to detect anomalous access patterns, such as a sudden spike in GetItem calls for many different partition keys from a single source.

middleBrick's reports provide specific remediation guidance for each finding, including references to Dynamodb documentation and IAM policy examples tailored to the detected issue. Integrating middleBrick into your CI/CD pipeline via the GitHub Action ensures these checks run on every pull request, preventing vulnerable configurations from reaching production.