Integer Overflow in Adonisjs with Dynamodb

AdonisJS is a Node.js web framework that encourages structured request handling and validation. When integrating with DynamoDB, values such as auto-incremented identifiers, numeric counters, or version attributes are often parsed from user-controlled input and then stored or used in low-level DynamoDB operations. If numeric values are not explicitly bounded and validated, an attacker can supply values that overflow JavaScript’s safe integer range (Number.MAX_SAFE_INTEGER = 9007199254740991) or cause runtime coercion issues, leading to unexpected behavior, malformed requests, or privilege escalation.

DynamoDB itself does not perform application-level integer overflow checks; it stores numbers as arbitrary-precision numeric values but preserves the exact value provided. If an AdonisJS layer accepts a large integer from a request (e.g., quantity, price, or a loop index), performs arithmetic, and writes the result to DynamoDB without validation, the computed value may wrap around or become negative. For example, incrementing a counter with current + 1 where current is near Number.MAX_SAFE_INTEGER can produce an incorrect result that downstream logic misinterprets as zero or a very small number, bypassing guardrails.

The risk is amplified when these numeric fields influence access control or conditional writes. An attacker might submit a crafted numeric parameter that, after overflow, satisfies an authorization check or causes the application to write to another user’s item. Because DynamoDB stores the corrupted value, the inconsistency persists until corrected, potentially leading to data integrity issues or unauthorized data exposure.

In the context of an unauthenticated scan, middleBrick tests input validation and property authorization across API endpoints. It checks whether numeric inputs are properly constrained before they are used in DynamoDB operations. Findings related to insufficient validation map to the Input Validation and Property Authorization checks, highlighting where integer overflow can affect security controls.

To mitigate integer overflow when working with DynamoDB in AdonisJS, enforce strict numeric validation, use bounded integers, and avoid unsafe arithmetic on user-supplied values. Prefer server-side arithmetic or transactions to maintain consistency, and validate ranges explicitly before constructing DynamoDB expressions.

Validation and bounded integers

Validate incoming numbers against expected ranges and use integer types that fit your domain. For IDs and counters, prefer database-generated values or controlled increments rather than client-supplied large integers.

const schema = use('Validator').createSchema;
const rules = {
  quantity: 'number|min:1|max:1000',
  price: 'number|min:0|max:1000000|decimal:2',
  version: 'integer|min:0'
};

const validated = await schema.validate({ body }, rules);
if (validated.fails()) {
  return response.badRequest(validated.messages());
}

Safe arithmetic and conditional update with DynamoDB

Use DynamoDB’s UpdateExpression with ADD for counters and ConditionExpression to enforce invariants. Avoid computing new values in JavaScript and writing them directly, which is prone to overflow and race conditions.

const { DynamoDBDocumentClient, UpdateCommand } = require("@aws-sdk/lib-dynamodb");
const client = DynamoDBDocumentClient.from(new DynamoDB({}));

const params = {
  TableName: "products",
  Key: { id: "item-123" },
  UpdateExpression: "SET quantity = quantity + :inc",
  ConditionExpression: "quantity + :inc <= :max",
  ExpressionAttributeValues: {
    ":inc": 1,
    ":max": 10000
  },
  ReturnValues: "UPDATED_NEW"
};

try {
  const result = await client.send(new UpdateCommand(params));
  console.log("Updated:", result.Attributes);
} catch (error) {
  if (error.name === "ConditionalCheckFailedException") {
    // Handle overflow-safe condition failure
    console.error("Increment would exceed safe limit");
  } else {
    throw error;
  }
}

Use transactions for multi-item consistency

When multiple items must remain consistent, use DynamoDB transactions to ensure that all-or-nothing semantics are enforced, preventing partial updates caused by intermediate overflow states.

const { DynamoDBDocumentClient, TransactWriteCommand } = require("@aws-sdk/lib-dynamodb");
const client = DynamoDBDocumentClient.from(new DynamoDB({}));

const transactionItems = [
  {
    Update: {
      TableName: "accounts",
      Key: { id: "user-1" },
      UpdateExpression: "SET balance = balance - :debit",
      ConditionExpression: "balance >= :debit",
      ExpressionAttributeValues: { ":debit": 50 }
    }
  },
  {
    Update: {
      TableName: "accounts",
      Key: { id: "user-2" },
      UpdateExpression: "SET balance = balance + :credit",
      ExpressionAttributeValues: { ":credit": 50 }
    }
  }
];

const txParams = { TransactItems: transactionItems };
try {
  const result = await client.send(new TransactWriteCommand(txParams));
  console.log("Transaction succeeded");
} catch (error) {
  console.error("Transaction failed:", error);
}

Server-side increment with DynamoDB atomic counters

For counters, rely on DynamoDB’s native ADD action rather than reading, modifying, and writing values in the application. This avoids race conditions and ensures atomicity.

const params = {
  TableName: "stats",
  Key: { id: "daily-views" },
  UpdateExpression: "ADD viewCount :inc",
  ExpressionAttributeValues: { ":inc": 1 },
  ReturnValues: "UPDATED_NEW"
};

const result = await client.send(new UpdateCommand(params));
console.log("New count:", result.Attributes.viewCount);

Middleware for sanitization in AdonisJS

Create a request sanitiser middleware to clamp numeric inputs before they reach controllers or services. This centralises validation and reduces the chance of missing an overflow-prone parameter.

// start/hooks/sanitize-numbers.js
const clamp = (value, min, max) => Math.min(Math.max(value, min), max);

const sanitizeNumbers = (schema) => async (ctx, next) => {
  const body = ctx.request.body();
  const sanitized = Object.keys(body).reduce((acc, key) => {
    const val = Number(body[key]);
    acc[key] = Number.isNaN(val) ? body[key] : clamp(val, schema[key]?.min ?? -Infinity, schema[key]?.max ?? Infinity);
    return acc;
  }, {});
  ctx.request.merge({ body: sanitized });
  await next();
};

module.exports = { sanitizeNumbers };