Security Misconfiguration in Adonisjs with Dynamodb

AdonisJS is a Node.js web framework that encourages structured configuration and dependency injection. When integrating with DynamoDB, misconfigurations often arise from how the SDK client is instantiated, how table names are resolved, and how IAM permissions are scoped. A typical misconfiguration is constructing the DynamoDB client with a shared, long-lived credential context that is not isolated per request or per environment, effectively exposing over-privileged credentials to downstream code. Hard-coded table names or region endpoints in source files may be acceptable in development but become a security risk when deployed to shared or multi-tenant environments where an attacker can influence runtime values through path or query parameters.

Another specific issue occurs when AdonisJS services dynamically reference DynamoDB table names using user-controlled input without strict allow-listing. For example, using a route parameter such as userId to build a table name like users_${userId}_profile can lead to Insecure Direct Object Reference (IDOR) patterns or unauthorized cross-table access if the input is not validated. DynamoDB streams and Time to Live (TTL) settings may also be misconfigured, causing sensitive data to persist longer than necessary or be exposed through backup or restore operations if encryption settings are inconsistent.

Middleware or service classes that perform data access without enforcing property-level authorization are especially risky. If an AdonisJS controller deserializes incoming JSON and passes it directly into a DynamoDB update expression without validating which fields can be modified, an attacker can exploit BFLA (Business Logic Flaws) to update attributes they should not touch, such as isAdmin or billingTier. Missing schema validation and unchecked attribute updates turn what should be a simple profile update into a privilege escalation path.

The combination of AdonisJS’s IoC container and DynamoDB’s schema-less design amplifies these risks. Developers may store complex nested objects directly in DynamoDB items without normalizing access controls per attribute. If the application does not enforce field-level read and write permissions, an attacker who gains low-privilege access can read or modify sensitive fields. Additionally, if the DynamoDB client is configured with an IAM role that has broad dynamodb:* permissions rather than least-privilege actions scoped to specific tables and operations, the blast radius of a compromised component is significantly increased.

Remediation centers on strict input validation, least-privilege IAM roles, and deterministic configuration. Always prefer environment-based configuration for endpoints and table names, and avoid deriving table names from user input. When dynamic table access is required, use an allow-list and perform exact-match validation before constructing requests.

import { DynamoDB } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocument } from '@aws-sdk/lib-dynamodb';

// Secure client construction with explicit region and credential isolation
const client = new DynamoDB({
  region: process.env.AWS_REGION || 'us-east-1',
  credentials: {
    accessKeyId: process.env.AWS_ACCESS_KEY_ID || '',
    secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY || '',
  },
});
const ddb = DynamoDBDocument.from(client);

// Validate table name against an allow-list
function resolveTable(tableKey: string): string {
  const allowed = {
    profiles: 'app-profiles-table',
    settings: 'app-settings-table',
  };
  if (!(tableKey in allowed)) {
    throw new Error('Invalid table reference');
  }
  return allowed[tableKey];
}

// Example: safe read with explicit table reference
export async function getUserProfile(userId: string) {
  const tableName = resolveTable('profiles');
  const result = await ddb.get({
    TableName: tableName,
    Key: { userId: { S: userId } },
  });
  return result.Item;
}

// Example: constrained update with field-level authorization
export async function updateUserProfile(userId: string, payload: Record) {
  const tableName = resolveTable('profiles');
  const updatableFields = new Set(['displayName', 'locale', 'timezone']);
  const updateExpressionParts = [];
  const expressionAttributeValues: Record = {};

  for (const [key, value] of Object.entries(payload)) {
    if (!updatableFields.has(key)) {
      throw new Error(`Field ${key} is not allowed to be updated`);
    }
    updateExpressionParts.push(`#${key} = :${key}`);
    expressionAttributeValues[`:${key}`] = value;
  }

  if (updateExpressionParts.length === 0) {
    throw new Error('No valid fields to update');
  }

  await ddb.update({
    TableName: tableName,
    Key: { userId: { S: userId } },
    UpdateExpression: `SET ${updateExpressionParts.join(', ')}`,
    ExpressionAttributeNames: { ['#displayName']: 'displayName' },
    ExpressionAttributeValues: expressionAttributeValues,
    ReturnValues: 'UPDATED_NEW',
  });
}

For IAM, define policies that restrict actions to specific resources. Instead of dynamodb:PutItem on *, scope to the exact table ARN and conditionally enforce encryption-in-transit using dynamodb:Endpoint conditions. In AdonisJS, centralize these configurations in a service provider so that the client and table mappings are consistent across the application. Use schema validation libraries to enforce payload shapes before constructing DynamoDB expressions, reducing the risk of malformed updates that could bypass application logic.