> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fingerprint.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Credential Stuffing

> Learn how to protect your application from credential stuffing attacks

## Overview

This tutorial walks through implementing Fingerprint to prevent credential stuffing, where attackers use bots to rapidly test stolen or guessed usernames and passwords across many accounts.

You'll begin with a starter app that includes a mock login page and a basic login flow. From there, you'll add the JavaScript agent to identify each visitor and use server-side logic with Fingerprint data to detect and block automated login attempts.

By the end, you'll have a sample app that rejects credential stuffing bots and can be customized to fit your use case and business rules.

This tutorial uses just plain JavaScript and a Node server with SQLite on the backend. For language- or framework-specific setups, see the quickstarts.

> Estimated time: \< 15 minutes

<iframe className="w-full aspect-video rounded-md" src="https://www.youtube.com/embed/rba-Lt2E0GU" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen />

<Note>
  This tutorial requires the Bot Detection Smart Signal, which is only available on paid plans.
</Note>

## Prerequisites

Before you begin, make sure you have the following:

* A copy of the [starter repository](https://github.com/fingerprintjs/use-case-tutorials) (clone with Git or download as a ZIP)
* [Node.js](https://nodejs.org/) (v20 or later) and npm installed
* Your favorite code editor
* Basic knowledge of JavaScript

## 1. Create a Fingerprint account and get your API keys

1. [Sign up](https://dashboard.fingerprint.com/signup) for a free Fingerprint trial, or log in if you already have an account.
2. After signing in, go to the [**API keys**](https://dashboard.fingerprint.com/api-keys) page in the dashboard.
3. Save your **public API key**, which you'll use to initialize the JavaScript agent.
4. Create and securely store a **secret API key** for your server. Never expose it on the client side. You'll use this key on the backend to retrieve full visitor information through the Fingerprint Server API.

## 2. Set up your project

1. Clone or download the [starter repository](https://github.com/fingerprintjs/use-case-tutorials) and open it in your editor.

```bash Terminal theme={"theme":"github-dark-dimmed"}
git clone https://github.com/fingerprintjs/use-case-tutorials.git
```

2. This tutorial will be using the `credential-stuffing` folder. The project is organized as follows:

<Tree>
  <Tree.Folder name="public" defaultOpen>
    <Tree.File name="index.html - Login page" />

    <Tree.File name="index.js - Front-end logic to handle login" />
  </Tree.Folder>

  <Tree.Folder name="server" defaultOpen>
    <Tree.File name="server.js - Serves static files and login endpoint" />

    <Tree.File name="db.js - SQLite database connection" />

    <Tree.File name="accounts.js - Credential stuffing prevention logic" />
  </Tree.Folder>

  <Tree.File name=".env.example - Example environment variables" />
</Tree>

3. Install dependencies:

```bash Terminal theme={"theme":"github-dark-dimmed"}
npm install
```

4. Copy or rename `.env.example` to `.env`, then add your Fingerprint API keys:

```bash Terminal theme={"theme":"github-dark-dimmed"}
FP_PUBLIC_API_KEY=your-public-key
FP_SECRET_API_KEY=your-secret-key
```

5. Start the server:

```bash Terminal theme={"theme":"github-dark-dimmed"}
npm run dev
```

6. Visit [http://localhost:3000](http://localhost:3000) to view the mock login page from the starter app. You can test the basic login form using the included test account (`demo@example.com` / `password123`) and clicking **Log in**.
7. Then try to log in using the included headless bot test script `test-bot.js`. While the app is running, execute `node test-bot.js` and observe that the automated script logs in successfully. By default, the server does not distinguish between bots and real users.

```bash Terminal theme={"theme":"github-dark-dimmed"}
node test-bot.js
```

## 3. Add Fingerprint to the frontend

In this step, you'll load the JavaScript agent when the page loads and trigger identification when the user clicks **Log in**. The JavaScript agent returns both a `visitorId` and a `requestId`. Instead of relying on the `visitorId` from the browser, you'll send the `requestId` to your server along with the login payload. The server will then call the [Fingerprint Events API](/reference/v3/server-api-get-event) to securely retrieve the full identification details, including bot detection and other signals.

1. At the top of `public/index.js`, load the JavaScript agent:

```javascript public/index.js theme={"theme":"github-dark-dimmed"}
const fpPromise = import(`https://fpjscdn.net/v3/${window.FP_PUBLIC_API_KEY}`).then(
  (FingerprintJS) => FingerprintJS.load({ region: "us" }),
);
```

2. Make sure to change `region` to match your workspace region (e.g., `eu` for Europe, `ap` for Asia, `us` for Global (default)).
3. Near the bottom of `public/index.js`, the **Log in** button already has an event handler for submitting the credentials. Inside this handler, request visitor identification from Fingerprint using the `get()` method and include the returned `requestId` when sending the login request to the server:

```javascript public/index.js theme={"theme":"github-dark-dimmed"}
loginBtn.addEventListener("click", async () => {
  // ...

  const fp = await fpPromise;
  const { requestId } = await fp.get();

  try {
    const res = await fetch("/api/login", {
      method: "POST",
      headers: { "Content-Type": "application/json" },
	    body: JSON.stringify({ email, password, requestId }),
    });
    const data = await res.json();

    // ...
  }
});
```

The `get()` method sends signals collected from the browser to Fingerprint servers, where they are analyzed to identify the visitor. The returned `requestId` acts as a reference to this specific identification event, which your server can later use to fetch the full visitor details.

For lower latency in production, use [Sealed Client Results](/docs/v3/sealed-client-results) to return full identification details as an encrypted payload from the `get()` method.

## 4. Receive and use the request ID to get visitor insights

Next, pass the `requestId` through to your login logic, initialize the [Fingerprint Node Server SDK](/reference/node-server-sdk), and fetch the full visitor identification event so you can access the trusted `visitorId` and Bot Detection [Smart Signal](https://fingerprint.com/products/smart-signals/).

1. In the backend, the `server/server.js` file defines the API routes for the app. Update the `/api/login` route there to also extract `requestId` from the request body and pass it into the `attemptLogin` function.

```javascript server/server.js theme={"theme":"github-dark-dimmed"}
app.post("/api/login", async (req, reply) => {
  const { email, password, requestId } = req.body || {};
  const result = await attemptLogin({ email, password, requestId });
  return reply.send(result);
});
```

2. The `server/accounts.js` file contains the logic for handling logins. Start by importing and initializing the Fingerprint Node Server SDK there, and load your environment variables with `dotenv`.

```javascript server/accounts.js theme={"theme":"github-dark-dimmed"}
import { db } from "./db.js";
import { config } from "dotenv";
import { FingerprintJsServerApiClient, Region } from "@fingerprintjs/fingerprintjs-pro-server-api";

config();

const fpServerApiClient = new FingerprintJsServerApiClient({
  apiKey: process.env.FP_SECRET_API_KEY,
  region: Region.Global,
});
```

3. Make sure to change `region` to match your workspace region (e.g., `EU` for Europe, `AP` for Asia, `Global` for Global (default)).
4. Update the `attemptLogin` function to accept `requestId` and use it to fetch the full identification event details from Fingerprint:

```javascript server/accounts.js theme={"theme":"github-dark-dimmed"}
export async function attemptLogin({ email, password, requestId }) {
  if (!email || !password) {
    console.error("Missing credentials.");
    return { success: false, error: "Login failed." };
  }

  if (!requestId) {
    console.error("Missing requestId.");
    return { success: false, error: "Login failed." };
  }

  const event = await fpServerApiClient.getEvent(requestId);

  const user = findAccountByEmail(email);
  if (!user || user.password !== password) {
    console.error("Invalid credentials");
    return { success: false, error: "Login failed." };
  }

  return { success: true };
}
```

Using the `requestId`, the getEvent will retrieve the full data for the visitor identification request. The returned object will contain the visitor ID, IP address, device, and browser details, and Smart Signals like bot detection, browser tampering detection, VPN detection, and more.

You can see a full example of the event structure and test it with your own device in the [demo playground](https://demo.fingerprint.com/playground).

For additional checks to ensure the validity of the data coming from your frontend, view [how to protect from client-side tampering and replay attacks](/docs/v3/protecting-from-client-side-tampering).

## 5. Block credential stuffing bots

Credential stuffing attacks rely heavily on automated login attempts, so rejecting bots outright can stop the abuse. Fingerprint returns `notDetected` if no bot activity is found, `good` for known bots, like search engines, and `bad` for other automation tools. Any visitor identification that does not return `notDetected` can be blocked from logging in.

1. Continuing in the `attemptLogin` function in `server/accounts.js`, check the bot signal returned in the `event` object and block bots:

```javascript server/accounts.js theme={"theme":"github-dark-dimmed"}
export async function attemptLogin({ email, password, requestId }) {
  // ...

  const event = await fpServerApiClient.getEvent(requestId);

  const botDetected = event.products?.botd?.data?.bot?.result !== "notDetected";
  if (botDetected) {
    console.error("Bot detected.");
    return { success: false, error: "Bot detected. Login failed." };
  }

  // ...
}
```

You can also add [Suspect Score](/docs/v3/suspect-score) as a secondary layer. The Suspect Score is a weighted representation of all Smart Signals present in the identification payload, helping to identify suspicious activity. While you wouldn't normally block logins based only on a high risk score, you could flag them for review, modify rate-limits, or add step-up authentication.

2. Below the bot detection check, add a condition that reads the Suspect Score from the `event` object and blocks the login if it exceeds a chosen threshold (for example, 20):

```javascript server/accounts.js theme={"theme":"github-dark-dimmed"}
export async function attemptLogin({ email, password, requestId }) {
  // ...

  const botDetected = event.products?.botd?.data?.bot?.result !== "notDetected";
  if (botDetected) {
    console.error("Bot detected.");
    return { success: false, error: "Bot detected. Login failed." };
  }

  const suspectScore = event.products?.suspectScore?.data?.result || 0;
  if (suspectScore > 20) {
    console.error(`High Suspect Score detected: ${suspectScore}`);
    return { success: false, error: "Login failed." };
  }

  // ...
}
```

## 6. Recognize repeat offenders by visitor ID

As a secondary measure, you can log the `visitorId` from failed login attempts to spot repeat attackers. This way, even if they change accounts or rotate IPs, you can recognize and block the same device when it comes back or tries other actions on your site.

Note: The starter app includes a SQLite database with these tables already created for you:

```text SQLite database tables theme={"theme":"github-dark-dimmed"}
accounts - Stores login credentials for test accounts
  email TEXT PRIMARY KEY
  password TEXT NOT NULL

failed_logins - Logs visitorIds tied to repeated failed attempts
  id INTEGER PRIMARY KEY AUTOINCREMENT
  visitorId TEXT NOT NULL
  createdAt INTEGER NOT NULL
```

1. Add some helper functions to the bottom of the `server/accounts.js` file to record and check failed attempts:

```javascript server/accounts.js theme={"theme":"github-dark-dimmed"}
// Log a failed login attempt
function logFailedAttempt(visitorId) {
  db.prepare(`INSERT INTO failed_logins (visitorId, createdAt) VALUES (?, ?)`).run(
    visitorId,
    Date.now(),
  );
}

// Get the number of recent failed login attempts
function getRecentFailedAttempts(visitorId) {
  const since = Date.now() - 24 * 60 * 60 * 1000; // 24 hours ago
  const row = db
    .prepare(
      `SELECT COUNT(*) as count 
       FROM failed_logins 
       WHERE visitorId = ? AND createdAt >= ?`,
    )
    .get(visitorId, since);
  return row.count;
}
```

2. Update `attemptLogin` to retrieve the `visitorId`, log failed attempts, and block repeat offenders:

```javascript server/accounts.js theme={"theme":"github-dark-dimmed"}
export async function attemptLogin({ email, password, requestId }) {
  if (!email || !password) {
    console.error("Missing email or password.");
    return { success: false, error: "Login failed." };
  }

  if (!requestId) {
    console.error("Missing requestId.");
    return { success: false, error: "Login failed." };
  }

  const event = await fpServerApiClient.getEvent(requestId);
  const visitorId = event.products.identification.data.visitorId;

  const botDetected = event.products?.botd?.data?.bot?.result !== "notDetected";
  if (botDetected) {
    logFailedAttempt(visitorId);
    console.error("Bot detected.");
    return { success: false, error: "Bot detected. Login failed." };
  }

  const suspectScore = event.products?.suspectScore?.data?.result || 0;
  if (suspectScore > 20) {
    logFailedAttempt(visitorId);
    console.error(`High Suspect Score detected: ${suspectScore}`);
    return { success: false, error: "Login failed." };
  }

  if (getRecentFailedAttempts(visitorId) >= 3) {
    logFailedAttempt(visitorId);
    console.error("Too many failed login attempts.");
    return { success: false, error: "Too many failed login attempts." };
  }

  const user = findAccountByEmail(email);
  if (!user || user.password !== password) {
    logFailedAttempt(visitorId);
    console.error("Invalid credentials");
    return { success: false, error: "Login failed." };
  }

  return { success: true };
}
```

Together with the bot detection Smart Signal, this allows you to protect your logins and prevent credential stuffing. You can extend it by analyzing additional signals, changing rate limit thresholds, varying your response, etc.

<Info>
  This is a minimal example to show how to implement Fingerprint. In a real application, make sure
  to implement proper security practices, error checking, and password handling that align with your
  production standards.
</Info>

## 7. Test your implementation

Now that everything is wired up, you can test the full protected login flow.

1. Start your server if it isn't already running and open [http://localhost:3000](http://localhost:3000):

```bash Terminal theme={"theme":"github-dark-dimmed"}
npm run dev
```

2. Try logging in with the valid test account (`demo@example.com` / `password123`). You should see a success response.
3. Now try a few failed login attempts using the wrong password. After 3 repeated failures, additional attempts from the same device will be blocked based on the failed login check.
4. Next, run the included headless bot test script from the `credential-stuffing` folder. This will attempt to log in using a headless browser, which will be flagged by the Bot Detection signal and rejected:

```bash Terminal theme={"theme":"github-dark-dimmed"}
node test-bot.js
```

*Note: If you encounter errors launching the automated browser, make sure you have the testing browser installed:*

```bash Terminal theme={"theme":"github-dark-dimmed"}
npx puppeteer browsers install chrome
```

## Next steps

You now have a working login flow that blocks credential stuffing bots with Fingerprint. From here, you can expand the logic with more [Smart Signals](/docs/v3/smart-signals-reference), fine-tune rules based on your business policies, or layer in additional defenses, such as rate limiting with multi-factor authentication.

To dive deeper, explore the other use case tutorials for more step-by-step examples.

Check out these related resources:

* [Node SDK Reference](https://github.com/fingerprintjs/fingerprintjs-pro-server-api-node-sdk)
* [Vue frontend quickstart](/docs/v3/vue-quickstart)
* [React frontend quickstart](/docs/v3/react-quickstart)
* [API reference for the Events endpoint](/reference/v3/server-api-get-event)
* [Use case tutorial: Detecting new account fraud](/docs/v3/new-account-fraud-use-case-tutorial)
* [Low-latency identification with Sealed Client Results](/docs/v3/sealed-client-results)