Distributed Denial Of Service in Feathersjs with Hmac Signatures

FeathersJS does not include built-in HMAC validation; HMAC verification is typically implemented via hooks that inspect an authentication header, compute a signature, and compare it to the value provided by the client. When HMAC is used for authentication, a DDoS vector can emerge if the verification logic is computationally expensive or applied indiscriminately to every incoming request. An attacker can send a high volume of requests with valid HTTP structure but invalid or random HMAC signatures, forcing the server to perform cryptographic computation for each request. This consumes CPU cycles and can exhaust thread or event-loop capacity, leading to degraded response times or service unavailability for legitimate users. The risk is higher when the HMAC includes large payloads or complex key derivation, and when rate limiting is absent or misconfigured.

Another DDoS scenario specific to the combination of FeathersJS and HMAC involves resource exhaustion through repeated authentication failures. If the HMAC verification hook does not fail early—for example, by checking required headers before performing expensive string normalization or hashing—an attacker can craft requests that trigger heavy processing. In clustered or serverless deployments, this can amplify resource usage across instances. Additionally, if the HMAC secret is inadvertently exposed or if replay protections like nonces and timestamps are not enforced, an attacker may reuse intercepted requests to generate repeated load. Because FeathersJS applications often expose multiple service routes, an unauthenticated endpoint that still processes HMAC logic becomes a target for volumetric attacks that do not require valid credentials, only a high request rate.

OpenAPI/Swagger analysis can highlight endpoints that invoke HMAC verification, but it cannot infer runtime CPU cost or deployment topology. A scan using a tool like middleBrick can test the unauthenticated attack surface of a FeathersJS API and surface findings related to rate limiting, input validation, and authentication robustness, helping teams identify endpoints where HMAC checks could be abused to trigger denial of service. The scan runs black-box tests, exercising the routes as they are exposed, and can reveal whether HMAC validation is applied uniformly and whether costly operations are deferred until after basic sanity checks.

To mitigate DDoS risks when using HMAC signatures in FeathersJS, implement early validation and efficient cryptographic checks within hooks. Ensure that lightweight header presence and format checks occur before any heavy signature computation. Use constant-time comparison to avoid timing-based side channels that could be exploited indirectly. Below is a concrete example of a FeathersJS before hook that validates HMAC efficiently.

const crypto = require('node:crypto');

function verifyHmac(secret) {
  return context => {
    const { headers, body } = context.params;
    const received = headers['x-hmac-signature'];
    const timestamp = headers['x-request-timestamp'];
    if (!received || !timestamp) {
      throw new Error('Missing HMAC or timestamp');
    }
    // Prevent replay: reject old timestamps (e.g., >2 minutes)
    const now = Date.now();
    if (Math.abs(now - Number(timestamp)) > 120000) {
      throw new Error('Request expired');
    }
    const payload = typeof body === 'string' ? body : JSON.stringify(body);
    const computed = crypto.createHmac('sha256', secret)
      .update(timestamp + payload)
      .digest('hex');
    // Constant-time comparison to avoid timing leaks
    let valid = 0;
    for (let i = 0; i < computed.length; i++) {
      valid |= computed.charCodeAt(i) ^ (received.charCodeAt(i) || 0);
    }
    if (valid !== 0) {
      throw new Error('Invalid HMAC');
    }
    return context;
  };
}

// Apply in your FeathersJS app setup
const app = require('@feathersjs/feathers')();
app.configure(require('@feathersjs/express').rest());
app.use('/api/secure', verifyHmac(process.env.HMAC_SECRET));

In this example, the hook first checks for the presence of required headers and enforces a timestamp window to mitigate replay-driven amplification attacks. It then computes the HMAC only after these lightweight checks, reducing unnecessary CPU load. The constant-time loop prevents attackers from inferring correctness through timing differences. For production, combine this with HTTP-level rate limiting and monitoring to detect abnormal request patterns that may indicate an ongoing DDoS attempt.

Another remediation approach is to move heavy HMAC validation behind an API gateway or edge layer that can absorb volumetric traffic before it reaches the FeathersJS application. If you use the middleBrick CLI to scan your API with middlebrick scan <url>, you can validate that HMAC verification is not applied to public, unauthenticated endpoints and that rate limiting headers are present. The dashboard can help track changes over time, while the GitHub Action can enforce that new routes include appropriate authentication and rate-limiting configurations before merging. These practices reduce the surface that an attacker can use to amplify load through HMAC processing.