Padding Oracle in Adonisjs with Firestore

A padding oracle attack occurs when an application reveals whether decrypted ciphertext has valid padding, allowing an attacker to iteratively decrypt encrypted data without knowing the key. In AdonisJS, this typically arises when using AES encryption (for example via CryptoJS or Node.js crypto) to protect sensitive values before storing them in Firestore, and then returning distinct error responses based on padding validity.

Firestore itself does not introduce padding oracle issues, but the way AdonisJS handles encrypted fields and Firestore errors can create an oracle. Consider an endpoint that accepts an identifier, retrieves a document from Firestore, decrypts a field, and returns different HTTP statuses or messages when decryption fails (e.g., due to invalid padding) versus when it succeeds. An attacker who can control the ciphertext and observe these responses can perform a padding oracle attack to recover plaintext.

For example, if AdonisJS uses crypto.privateDecrypt or manual PKCS7 padding checks and responds with a 400 for bad padding versus a 200 for good padding, the distinction becomes an oracle. Firestore adds a network boundary and potential timing differences; if error handling in AdonisJS exposes stack traces or specific failure reasons when a Firestore document is not found or a field is missing, an attacker can correlate these behaviors with ciphertext modifications to infer padding validity.

Real-world impact aligns with OWASP API Security Top 10 categories: broken object level authorization (BOLA) can intersect with this when encrypted IDs are manipulated, and data exposure can occur if sensitive information is recovered via the oracle. PCI-DSS and SOC2 controls also highlight the need to protect encrypted data and avoid information leakage through error handling.

To detect this using middleBrick, you would submit the API endpoint to scanning; the tool runs active tests including input validation and checks for information leakage in responses. Findings would highlight insecure error handling or lack of uniform failure responses, with remediation guidance mapped to frameworks like OWASP API Top 10.

Remediation focuses on ensuring decryption never distinguishes between padding errors and other failures, and that responses are uniform. Avoid exposing padding-related exceptions directly, and treat all decryption failures as generic authentication or integrity errors.

Use AdonisJS middleware to centralize error handling so that any decryption or Firestore-related exception results in a consistent 401/403 response without details. Below is a secure pattern for decrypting a Firestore document field in AdonisJS using Node.js crypto with constant-time comparison and safe error handling.

import crypto from 'crypto';
import { HttpContextContract } from '@ioc:Adonis/Core/HttpContext';
import Document from 'App/Models/Document';

export default class DocumentsController {
  public async show({ params, response }: HttpContextContract) {
    try {
      const record = await Document.findOrFail(params.id);
      // Assume `encryptedData` is stored as base64 in Firestore
      const encryptedBuffer = Buffer.from(record.encryptedData, 'base64');
      const iv = encryptedBuffer.slice(0, 16);
      const ciphertext = encryptedBuffer.slice(16);

      const key = Buffer.from(process.env.ENC_KEY!, 'hex');
      const decipher = crypto.createDecipheriv('aes-256-cbc', key, iv);

      let decrypted = decipher.update(ciphertext);
      decrypted = Buffer.concat([decrypted, decipher.final()]);

      // Constant-time comparison for a MAC or expected prefix to avoid padding oracle
      const hmac = crypto.createHmac('sha256', key).update(decrypted).digest('hex');
      const expectedMac = record.mac;
      const isValid = crypto.timingSafeEqual(Buffer.from(hmac), Buffer.from(expectedMac));

      if (!isValid) {
        throw new Error('authentication_failed');
      }

      return response.json({ data: decrypted.toString('utf8') });
    } catch (error) {
      // Generic response to prevent oracle
      return response.unauthorized('Invalid request');
    }
  }
}

In this pattern, final() is called inside the try block, and any padding or decryption errors are caught uniformly. MAC verification using timingSafeEqual prevents attackers from distinguishing padding failures from MAC mismatches.

When integrating with Firestore, ensure that document reads do not leak existence via timing or status codes. middleBrick scans can verify that error handling is consistent and that no distinguishing messages appear for missing documents versus decryption failures.

For broader protection, enable continuous monitoring using the Pro plan to detect regressions in error handling or new endpoints that might reintroduce an oracle. The GitHub Action can enforce a security score threshold, failing builds if findings indicate insecure error patterns.