Poodle Attack in Adonisjs with Dynamodb

A Poodle (Padding Oracle On Downgraded Legacy Encryption) attack targets systems that negotiate SSL 3.0 and use block ciphers with CBC mode. In an AdonisJS application that stores session data or sensitive payloads in DynamoDB, the risk arises when TLS 3.0 is enabled and responses reveal padding errors differently based on whether ciphertext decrypts correctly. AdonisJS may use cookie-based sessions or JWTs stored in DynamoDB; if an attacker can force or observe decryption of crafted ciphertexts via error timing or behavior, they can gradually recover plaintext without needing to break the cipher directly.

With DynamoDB as the persistence layer, the exposure surface includes how AdonisJS reads and writes encrypted items. For example, if encrypted strings are stored in a DynamoDB attribute and the application decrypts them in an error-prone way (e.g., throwing distinct errors for padding failures versus other exceptions), an attacker who can inject or manipulate ciphertext—perhaps via an insecure endpoint or a compromised client-side token—can use adaptive chosen-ciphertext queries to a TLS endpoint or a custom decryption routine to learn about valid padding. This is especially relevant when AdonisJS uses the same key material across sessions or when key rotation is infrequent, and when DynamoDB streams or backups are not protected against unauthorized read access.

The combination is problematic when TLS 3.0 is negotiable, CBC cipher suites are in use, and error handling leaks padding validation outcomes. An attacker can intercept or modify in-transit data between the client and AdonisJS server, then observe differences in behavior (e.g., HTTP 400 versus 500, timing differences, or structured error messages) when malformed padding is submitted. If the application also stores related metadata or encrypted blobs in DynamoDB, an attacker might leverage stored ciphertexts to mount offline attacks or replay modified ciphertexts against the API to extract information one byte at a time.

In practice, a scan by middleBrick against an AdonisJS endpoint backed by DynamoDB might flag findings related to SSL 3.0 support, weak cipher suites, and inconsistent error handling that could facilitate padding oracle behavior. Even when TLS is modern, if AdonisJS deserializes encrypted payloads without integrity checks (e.g., missing authentication) and stores them in DynamoDB, an attacker who can tamper with stored ciphertexts might be able to conduct offline decryption attempts. The scan would highlight missing integrity protection on data at rest in DynamoDB and the presence of legacy protocol support that increases the likelihood of successful Poodle-style attacks.

Remediation centers on disabling SSL 3.0, preferring strong cipher suites, and ensuring decryption routines do not leak padding information. In AdonisJS, configure the HTTPS/TLS server to disable SSL 3.0 and explicitly enable TLS 1.2 or TLS 1.3. For data stored in DynamoDB, use authenticated encryption (e.g., AES-GCM) so that integrity is verified before decryption, and ensure errors are uniform and do not distinguish padding failures from other issues.

When reading encrypted items from DynamoDB, avoid conditional logic that branches on padding validity. Instead, use constant-time comparisons and handle decryption failures generically. Below is a concrete AdonisJS example using the AWS SDK for DynamoDB with Node.js built-in crypto to perform authenticated decryption, preventing padding oracle leaks.

import { DynamoDBClient, GetCommand } from '@aws-sdk/client-dynamodb';
import { unmarshal } from '@aws-sdk/util-dynamodb';
import crypto from 'crypto';

const client = new DynamoDBClient({ region: 'us-east-1' });
const algorithm = 'aes-256-gcm';

export async function getSecureItem(tableName, keyId, ivBase64, authTagBase64) {
  const cmd = new GetCommand({
    TableName: tableName,
    Key: { id: { S: keyId } },
  });

  const { Item } = await client.send(cmd);
  if (!Item) {
    throw new Error('Not found');
  }

  const encryptedData = Item.encryptedData?.B?.toString('base64');
  const storedIv = Item.iv?.S || ivBase64;
  const storedAuthTag = Item.authTag?.S || authTagBase64;

  if (!encryptedData) {
    throw new Error('Invalid payload');
  }

  const key = crypto.scryptSync(process.env.APP_KEY_SECRET, 'salt-unique-per-app', 32);
  const iv = Buffer.from(storedIv, 'base64');
  const authTag = Buffer.from(storedAuthTag, 'base64');
  const decipher = crypto.createDecipheriv(algorithm, key, iv);
  decipher.setAuthTag(authTag);

  try {
    let decrypted = decipher.update(Buffer.from(encryptedData, 'base64'));
    decrypted = Buffer.concat([decrypted, decipher.final()]);
    return JSON.parse(decrypted.toString('utf8'));
  } catch (err) {
    // Generic error to avoid leaking padding or auth failures
    throw new Error('Invalid data');
  }
}

For data written to DynamoDB, use authenticated encryption before storage:

export function encryptForDynamo(data, key) {
  const algorithm = 'aes-256-gcm';
  const iv = crypto.randomBytes(12);
  const cipher = crypto.createCipheriv(algorithm, key, iv);
  let encrypted = cipher.update(JSON.stringify(data), 'utf8');
  encrypted = Buffer.concat([encrypted, cipher.final()]);
  return {
    encryptedData: encrypted.toString('base64'),
    iv: iv.toString('base64'),
    authTag: cipher.getAuthTag().toString('base64'),
  };
}

Ensure TLS configuration in AdonisJS disables SSL 3.0 and weak ciphers. In your HTTPS server setup, prefer modern protocols and explicitly set secure options. Also rotate encryption keys periodically and avoid storing the same key across unrelated records. middleBrick can validate these changes by scanning endpoints to confirm SSL 3.0 is not offered and that only strong cipher suites are negotiated.

Finally, restrict access to DynamoDB items using IAM policies and enable encryption at rest. Monitor access patterns to detect anomalous ciphertext requests that might indicate probing for oracle behavior. By combining protocol hygiene, authenticated encryption, and uniform error handling, the AdonisJS + DynamoDB stack can resist Poodle-style attacks while maintaining data confidentiality and integrity.