Credential Stuffing in Feathersjs with Hmac Signatures

Credential stuffing relies on automated sign-in attempts using breached username and password pairs. In Feathersjs applications that use Hmac Signatures for request authentication, the vulnerability arises when the Hmac verification does not adequately bind the request to a per‑user or per‑session context and when rate limiting or anomaly detection is absent. Feathersjs itself is framework agnostic about transport and storage, so if you implement Hmac based authentication (for example, signing a canonical string that includes user credentials or a static secret) without additional protections, an attacker can replay captured signed requests or systematically try credential pairs against the endpoint.

Consider a Feathers service that accepts a POST to /authentication with a payload containing an identifier and a signature. If the signature is computed over a static string such as the user’s password or a static secret, the same signature can be reused across multiple accounts when the attacker iterates over a list of credentials. Moreover, if the endpoint does not enforce strict rate limiting per IP or account and does not require additional proof of possession that changes per session (for example, a nonce or a one‑time token), the attacker can perform high‑volume, low‑and‑slow credential stuffing without triggering defenses. The risk is compounded when the Hmac implementation does not include a timestamp or nonce, enabling replay attacks where a single valid signed request can be repeatedly used to authenticate.

In a black‑box scan, middleBrick tests for these weaknesses among its 12 parallel checks, including Authentication, BOLA/IDOR, Rate Limiting, and Unsafe Consumption. It inspects the API surface to determine whether Hmac based authentication can be exercised without valid user‑specific context, whether the same signature can authenticate multiple accounts, and whether there are observable differences in response that allow account enumeration. These checks highlight scenarios where Hmac signatures are computed over data that does not change per login attempt or where the signing process leaks information that aids an attacker in narrowing credential candidates.

Real world attack patterns such as those enumerated in OWASP API Top 10 (e.g., Broken Object Level Authorization and Improper Rate Limiting) map well to this scenario. For instance, if a Feathersjs API uses Hmac Signatures without tying the signature to a per request nonce or session token, an attacker can submit the same signed payload to many accounts, effectively automating credential validation. Even if the API responds with generic authentication failure messages, differing response times or status code distributions can leak whether a given credential pair is valid, enabling the attacker to iteratively refine their list of usernames and passwords.

To illustrate the signing flow that can be vulnerable, here is a realistic example of how Hmac Signatures might be implemented in a Feathersjs service before remediations. This example intentionally demonstrates practices that can contribute to credential stuffing risks when used without additional safeguards.

// Example: Potentially vulnerable Hmac signing in Feathersjs (pre‑remediation)
const crypto = require('crypto');

function signPayload(data, secret) {
  return crypto.createHmac('sha256', secret).update(data).digest('hex');
}

app.service('authentication').hooks({
  before: {
    create: [context => {
      const { identifier, password, signature } = context.data;
      const expected = signPayload(identifier + password, process.env.HMAC_SECRET);
      if (signature !== expected) {
        throw new Error('Invalid signature');
      }
      // Proceed without per request nonce or timestamp binding
      return context;
    }]
  }
});

In this example, the signature is derived from the concatenation of identifier and password using a static secret. If an attacker obtains or guesses one valid signature, they may reuse it across accounts if the server does not enforce per request variability. Additionally, without a timestamp or nonce, there is no mechanism to reject replayed requests, which is especially dangerous in credential stuffing campaigns where the same credentials are tried across many accounts.

Remediation focuses on ensuring that each signed request is unique, non‑replayable, and bound to the user’s authentication context. This involves incorporating a nonce or timestamp, tying the signature to a per‑user secret derived from a strong password hash, and enforcing strict rate limits and monitoring. The goal is to make credential stuffing impractical by requiring fresh, user‑specific signing material for each authentication attempt.

First, include a server‑generated nonce or timestamp in the signed payload and validate it on the server with a short window of acceptance. This prevents replay of captured signatures. Second, derive a per‑user signing secret from the user’s password hash (or a server‑side secret combined with the user identifier) rather than using a global static secret. This ensures that even if one signature is compromised, it cannot be reused across accounts or sessions.

Below is a concrete, secure example of Hmac Signatures implementation in Feathersjs that incorporates these protections. It uses a timestamp, a per‑user secret derived via PBKDF2, and validates freshness to mitigate credential stuffing and replay risks.

// Secure Hmac signing in Feathersjs (post‑remediation)
const crypto = require('crypto');

function deriveUserSecret(userId, passwordHash) {
  // Derive a per‑user secret using a slow KDF and server side pepper
  return crypto.pbkdf2Sync(userId, passwordHash, 100000, 32, 'sha256');
}

function buildSignedPayload(identifier, timestamp, nonce) {
  return `${identifier}:${timestamp}:${nonce}`;
}

function signPayload(data, secret) {
  return crypto.createHmac('sha256', secret).update(data).digest('hex');
}

// In your Feathers service hook
app.service('authentication').hooks({
  before: {
    create: [async context => {
      const { identifier, password, timestamp, nonce, signature } = context.data;
      // Retrieve user record to obtain passwordHash and userId
      const user = await app.service('users').get(identifier);
      if (!user) {
        throw new Error('Invalid credentials');
      }
      const userSecret = deriveUserSecret(user.userId, user.passwordHash);
      const expectedPayload = buildSignedPayload(identifier, timestamp, nonce);
      const expected = signPayload(expectedPayload, userSecret);

      // Validate timestamp freshness (e.g., 5 minutes window)
      const now = Date.now();
      if (Math.abs(now - Number(timestamp)) > 5 * 60 * 1000) {
        throw new Error('Request expired');
      }

      // Validate nonce uniqueness (store recently used nonces in a short‑lived cache)
      // pseudo: if seenNonce(nonce) throw Error('Replay detected');

      if (signature !== expected) {
        throw new Error('Invalid signature');
      }

      // Proceed with authentication logic
      return context;
    }]
  }
});

In this revised flow, the client must include timestamp and nonce fields, and the server derives a per‑user secret using a key‑stretching function. The server validates that the timestamp is recent and that the nonce has not been seen recently, effectively neutralizing replay and credential stuffing attempts that rely on signature reuse. Coupled with rate limiting at the framework or infrastructure level and monitoring for anomalous authentication patterns, this approach significantly raises the bar against automated credential stuffing while preserving the utility of Hmac based authentication in Feathersjs.

Additionally, integrating middleBrick scans into your workflow helps validate these protections. Using the CLI you can run middlebrick scan <url> to verify that your endpoints do not leak authentication differences or accept replayed Hmac signed requests. Teams using CI/CD can add the GitHub Action to fail builds when risk scores degrade, while the Web Dashboard allows tracking security scores over time to ensure ongoing resilience against credential abuse.