Replay Attack in Feathersjs

Replay attacks in Feathersjs applications typically exploit the framework's real-time communication layer and RESTful API endpoints. Since Feathersjs uses Socket.io for real-time features, attackers can capture valid authentication tokens or session data and reuse them to impersonate legitimate users.

The most common replay attack vector in Feathersjs occurs through the authentication service. When a user authenticates via app.service('authentication').create(), Feathersjs returns a JWT token that remains valid until expiration. If this token is intercepted through network sniffing or XSS, an attacker can replay the same token to gain unauthorized access.

Feathersjs's event-driven architecture creates additional replay opportunities. Real-time events transmitted over websockets can be captured and replayed to trigger actions multiple times. For example, a legitimate created event for a financial transaction could be captured and resent to duplicate the transaction.

REST API endpoints in Feathersjs are also vulnerable when they lack proper nonce or timestamp validation. Consider this typical Feathersjs service method:

class PaymentsService {
  async create(data, params) {
    // No replay protection - same data can be submitted repeatedly
    return this._super(data, params);
  }
}

Without replay protection, an attacker who captures a successful payment request can resend it, potentially causing duplicate charges. Feathersjs's default service methods don't implement any built-in replay detection, making this a common vulnerability.

The framework's hooks system, while powerful for adding business logic, doesn't automatically prevent replay attacks. A hook like this might process requests without considering whether they're duplicates:

const { authenticate } = require('@feathersjs/authentication').hooks;

const processPayment = async (context) => {
};

Real-time channels in Feathersjs create another attack surface. When clients connect to channels using authentication data, captured channel authentication parameters can be replayed to gain persistent access to protected data streams.

Detecting replay attacks in Feathersjs requires monitoring both the authentication flow and service method calls. middleBrick's black-box scanning approach is particularly effective for Feathersjs applications since it tests the actual running API without requiring source code access.

For authentication replay detection, middleBrick scans Feathersjs authentication endpoints by submitting valid credentials and capturing the returned JWT tokens. It then attempts to reuse these tokens within their validity window to verify if the application properly validates token freshness or implements replay protection mechanisms.

The scanner specifically tests Feathersjs's Socket.io integration by establishing a websocket connection, capturing the authentication handshake, and attempting to replay the same authentication sequence. This reveals whether the real-time layer has adequate replay protection.

middleBrick's OpenAPI spec analysis is especially valuable for Feathersjs applications since the framework automatically generates REST API specifications. The scanner cross-references the spec with actual runtime behavior, identifying endpoints that lack proper replay protection based on their HTTP method semantics. For example, it flags POST endpoints that should be idempotent but aren't protected against duplicate submissions.

The LLM/AI security module in middleBrick can detect if your Feathersjs application uses AI services that might be vulnerable to replay attacks through prompt injection. Some Feathersjs applications integrate with AI services for content generation or analysis, creating new replay attack vectors.

middleBrick tests for replay vulnerabilities by:

• Capturing and replaying authentication tokens
• Resending successful API requests to check for duplicate processing
• Testing websocket authentication handshakes
• Analyzing service method implementations for replay protection gaps
• Checking for proper nonce or timestamp validation in request processing

The scanner provides a security score specific to replay attack vulnerabilities, along with detailed findings that show exactly which Feathersjs endpoints are vulnerable and what remediation steps are needed.

Remediating replay attacks in Feathersjs requires implementing proper request validation and state tracking. The most effective approach combines nonce generation, timestamp validation, and idempotency keys.

For authentication replay protection, implement token binding to specific client characteristics:

const { AuthenticationBase } = require('@feathersjs/authentication');

class ReplayProtectedAuthentication extends AuthenticationBase {
  async create(data, params) {
}

For service methods that must be protected against replay, implement nonce validation using Feathersjs hooks:

const { BadRequest } = require('@feathersjs/errors');

const preventReplay = async (context) => {
};

Apply this hook to vulnerable service methods:

const paymentsService = {

app.service('payments').hooks({

For websocket connections, implement connection-specific authentication that prevents token replay:

const socketAuth = async (connectionParams, { app }) => {
};

Implement idempotency keys for critical operations using Feathersjs's before hooks:

const idempotencyKey = async (context) => {
};

For comprehensive replay protection, combine multiple strategies: bind authentication tokens to client characteristics, implement nonce validation for state-changing operations, use idempotency keys for critical transactions, and validate request timestamps. middleBrick's Pro plan can continuously monitor your Feathersjs application to ensure these protections remain effective as your codebase evolves.