Out Of Bounds Write in Adonisjs with Dynamodb

An Out Of Bounds Write occurs when application logic allows writing data to memory locations outside the intended buffer or data structure. In the combination of AdonisJS with DynamoDB, this typically arises from unchecked user input used to control item attributes, array indices, or pagination tokens that influence which items are read or written. Because AdonisJS is a Node.js web framework, JavaScript runtime behavior and DynamoDB’s schema-less design can allow malformed or oversized payloads to be processed without adequate validation, leading to writes beyond expected boundaries.

DynamoDB itself does not provide traditional memory buffers, but an Out Of Bounds condition can manifest through unexpected attribute placement, item size limits, or misuse of key schema attributes. For example, if an endpoint accepts an array index from request parameters to update a specific element in a DynamoDB list attribute, failing to validate that index can cause writes to unintended positions within the list, potentially corrupting other items or exceeding item size limits (400 KB). Additionally, if user-controlled keys are used to construct DynamoDB key attribute names without normalization, it may result in attributes being written under unexpected names, effectively creating out-of-bounds attribute mappings that break schema expectations and can expose sensitive data through other queries.

When using DynamoDB with AdonisJS, developers often rely on the AWS SDK directly or an ORM layer. If input is not validated against the expected data types and constraints, an attacker can supply large strings or nested objects that cause item sizes to approach or exceed limits, triggering partial writes or shifting data layout within the item. This can lead to data corruption or unexpected behavior when the item is subsequently read. Moreover, if pagination or filtering parameters derived from user input are used to construct KeyConditionExpression or FilterExpression without strict validation, an attacker might manipulate these values to access or overwrite items outside the intended scope, effectively creating an out-of-bounds access pattern.

To detect such issues, middleBrick performs an OpenAPI/Swagger spec analysis (supporting 2.0, 3.0, and 3.1) with full $ref resolution, cross-referencing spec definitions with runtime findings. During an unauthenticated scan, it tests input validation and property authorization checks, identifying cases where array indices, key attributes, or item sizes are not properly constrained. The LLM/AI Security checks also look for patterns where large or malformed payloads could lead to boundary violations, while the Input Validation and Data Exposure checks surface missing safeguards that enable out-of-bounds writes.

An example of vulnerable AdonisJS code that could lead to an Out Of Bounds Write with DynamoDB is shown below. This endpoint updates an item in a DynamoDB table using a user-supplied index to modify an array attribute without validating the index range or item size.

const { DynamoDBClient, UpdateItemCommand } = require('@aws-sdk/client-dynamodb');
const { marshall, unmarshall } = require('@aws-sdk/util-dynamodb');

async function updateListItem(userId, itemId, index, newValue) {
  const client = new DynamoDBClient({ region: 'us-east-1' });
  const params = {
    TableName: 'ItemsTable',
    Key: marshall({ userId: { S: userId }, itemId: { S: itemId } }),
    UpdateExpression: 'SET #list[#idx] = :val',
    ExpressionAttributeNames: {
      '#list': 'myList',
      '#idx': index.toString()
    },
    ExpressionAttributeValues: marshall({ ':val': { S: newValue } })
  };
  await client.send(new UpdateItemCommand(params));
}

In this example, the index is directly converted to a string and injected into the UpdateExpression without range checking. An attacker could supply a negative or extremely large index, causing writes outside the intended array boundaries or triggering item size violations. middleBrick identifies such patterns by correlating expression attribute usage with runtime behavior and highlighting missing validation in the findings report, along with remediation guidance aligned with OWASP API Top 10 and common compliance frameworks.

Remediation focuses on strict input validation, bounded operations, and safe attribute handling to prevent Out Of Bounds Writes when using DynamoDB with AdonisJS. Always validate array indices against the actual list length before using them in UpdateExpression, and enforce item size limits before sending requests to DynamoDB. Use ExpressionAttributeNames cautiously and avoid directly interpolating user input into key paths.

Below is a secure version of the previous example, incorporating index validation and size checks. This approach ensures that writes remain within intended boundaries and item sizes stay within DynamoDB limits.

const { DynamoDBClient, UpdateItemCommand } = require('@aws-sdk/client-dynamodb');
const { marshall, unmarshall } = require('@aws-sdk/util-dynamodb');

async function updateListItem(userId, itemId, index, newValue) {
  if (!Number.isInteger(index) || index < 0 || index > 99) {
    throw new Error('Index out of allowed range');
  }
  const client = new DynamoDBClient({ region: 'us-east-1' });
  // First, fetch the item to check current list size and item size limit
  const getParams = {
    TableName: 'ItemsTable',
    Key: marshall({ userId: { S: userId }, itemId: { S: itemId } })
  };
  const getItemCommand = new GetItemCommand(getParams);
  const item = await client.send(getItemCommand);
  const itemData = unmarshall(item.Item);
  const list = itemData.myList || [];
  if (index >= list.length) {
    throw new Error('Index exceeds current list length');
  }
  const updatedList = list.map((val, i) => (i === index ? newValue : val));
  const itemSize = JSON.stringify(updatedList).length;
  if (itemSize > 390000) { // leave margin for other attributes
    throw new Error('Item size would exceed DynamoDB limit');
  }
  const params = {
    TableName: 'ItemsTable',
    Key: marshall({ userId: { S: userId }, itemId: { S: itemId } }),
    UpdateExpression: 'SET #list = :list',
    ExpressionAttributeNames: {
      '#list': 'myList'
    },
    ExpressionAttributeValues: marshall({ ':list': updatedList })
  };
  await client.send(new UpdateItemCommand(params));
}

This code validates the index range, checks the current list length, and ensures the updated item remains under DynamoDB’s 400 KB item size limit. By replacing the entire list rather than performing an in-place index write, it avoids boundary issues and simplifies size validation. For APIs exposed through AdonisJS routes, integrate this function with request parsing and error handling middleware to return appropriate HTTP status codes and messages.

middleBrick’s findings include prioritized remediation guidance mapped to frameworks like OWASP API Top 10, helping you address Input Validation and Data Exposure risks systematically. With the Pro plan, you can enable continuous monitoring to detect regressions, and the GitHub Action can fail builds if risk scores exceed your configured threshold, ensuring that such issues are caught before deployment.