Bleichenbacher Attack in Sails with Dynamodb

A Bleichenbacher attack is a chosen-ciphertext attack against asymmetric encryption padding schemes, commonly RSA PKCS#1 v1.5. In a Sails application that uses Dynamodb as a persistence store, the vulnerability arises when error messages or timing differences during decryption are exposed to the attacker. For example, if your Sails backend calls a DynamoDB item that stores an encrypted token or credential and then performs RSA decryption in Node.js, an attacker can iteratively supply modified ciphertexts and observe distinct responses (e.g., HTTP 400 with "invalid padding" vs. a different behavior). These differences allow the attacker to gradually decrypt ciphertext without knowing the private key, provided they can distinguish valid padding from invalid padding via the API surface.

In the Sails + Dynamodb context, this often maps to an API endpoint that accepts an encrypted identifier (such as a user ID or reset token), retrieves the corresponding item from DynamoDB, and attempts to decrypt it using a private key. If the endpoint does not use constant-time comparisons and does not normalize errors, the unauthenticated attack surface exposed by middleBrick scanning can reveal timing discrepancies or error-message patterns that facilitate a Bleichenbacher attack. A typical vulnerable route might look like:

// Sails controller (vulnerable example)
module.exports.decryptToken = async function (req, res) {
  const { ciphertextB64 } = req.allParams();
  const ciphertext = Buffer.from(ciphertextB64, 'base64');
  try {
    const item = await dynamodb.get({ TableName: 'tokens', Key: { id: 'bleichen-token' } }).promise();
    const encryptedData = item.Item.encryptedData; // stored in DynamoDB
    const decipher = crypto.createDecipheriv('aes-256-cbc', key, iv);
    // Suppose encryptedData was RSA-wrapped AES key; we attempt RSA decryption
    const decryptedKey = crypto.privateDecrypt({ key: privateKey, padding: crypto.constants.RSA_PKCS1_PADDING }, ciphertext);
    const aesKey = decryptedKey.slice(0, 32);
    const result = decipher.update(aesKey) + decipher.final('utf8');
    return res.ok(result);
  } catch (err) {
    // Distinct error messages or status codes can aid Bleichenbacher
    return res.serverError({ error: err.message });
  }
};

An attacker can use this behavior to conduct an interactive Bleichenbacher attack by sending many ciphertexts and observing responses. middleBrick’s unauthenticated scan can surface such endpoints by detecting missing rate limiting, inconsistent error handling, and unauthenticated LLM endpoints (if any), which may indirectly highlight places where error distinctions are observable. The scan checks for Input Validation and Authentication configurations, helping you identify whether endpoints expose sensitive error information or are susceptible to padding-oracle-like behavior when used with Dynamodb-stored encrypted data.

Moreover, if your Sails app uses Dynamodb streams or inventory-management patterns to trigger decryption routines, an attacker might abuse event-driven paths to amplify the oracle. middleBrick’s checks for Unsafe Consumption and Inventory Management can flag risky integrations where event sources interact with cryptographic operations without proper validation.

Remediation focuses on ensuring that decryption errors do not leak distinguishable information and that cryptographic operations are performed safely. Always use constant-time operations for comparisons and avoid exposing low-level error details to the client. When storing encrypted items in Dynamodb, design your data access layer to separate retrieval from decryption and to treat all decryption failures identically.

Below is a hardened Sails controller example that mitigates Bleichenbacher-style risks when working with items stored in DynamoDB:

// Sails controller (hardened example)
const crypto = require('crypto');

module.exports.decryptTokenSafe = async function (req, res) {
  const { ciphertextB64 } = req.allParams();
  if (!ciphertextB64 || !ciphertextB64.trim()) {
    return res.badRequest({ error: 'Invalid input' });
  }
  const ciphertext = Buffer.from(ciphertextB64, 'base64');

  try {
    const item = await sails.helpers.dynamodb.getItem({ TableName: 'tokens', Key: { id: 'bleichen-token' } });
    if (!item) {
      // Return a generic error without indicating whether the item exists
      return res.unauthorized({ error: 'Invalid request' });
    }
    const encryptedData = item.encryptedData; // stored in DynamoDB

    // Use constant-time padding check and avoid leaking which step failed
    const decryptedKey = crypto.privateDecrypt({
      key: sails.config.privateKey,
      padding: crypto.constants.RSA_PKCS1_PADDING,
      // input is ciphertext
    }, ciphertext);

    // If key derivation or decryption fails, treat it as a generic failure
    const aesKey = decryptedKey.slice(0, 32);
    const iv = decryptedKey.slice(32, 48);
    const decipher = crypto.createDecipheriv('aes-256-cbc', aesKey, iv);
    let decrypted;
    try {
      decrypted = Buffer.concat([decipher.update(encryptedData), decipher.final()]);
    } catch (decErr) {
      decrypted = null;
    }
    if (!decrypted) {
      return res.unauthorized({ error: 'Invalid request' });
    }
    return res.ok({ token: decrypted.toString('utf8') });
  } catch (err) {
    // Log full error internally, return generic response to caller
    sails.log.error('Decryption failure', err);
    return res.unauthorized({ error: 'Invalid request' });
  }
};

Key points in this fix:

• Input validation is strict and does not reveal whether the stored item exists.
• Decryption errors are caught and mapped to a generic unauthorized response, preventing padding-oracle behavior.
• Use of constants for key and IV derivation ensures deterministic, testable behavior.
• Logging the full error server-side helps with diagnostics without exposing details to the API client.

Additionally, you can integrate middleBrick’s scans (CLI: middlebrick scan <url>, Dashboard, or GitHub Action) to continuously validate that endpoints handling encrypted Dynamodb items do not expose timing differences or distinct error messages. The scan’s Input Validation and Authentication checks, combined with its Unauthenticated LLM endpoint detection (if LLM flows are involved), help surface risky patterns before attackers can probe them.