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Overview

This tutorial walks through implementing Fingerprint to prevent web scraping, where bots attempt to extract proprietary or sensitive data from your website automatically. You’ll begin with a starter app that includes a mock flight search page and a basic querying flow. From there, you’ll add the Fingerprint JavaScript agent to identify each visitor and use server-side logic with Fingerprint data to detect and block automated scraping attempts. By the end, you’ll have a sample app that blocks bot-driven data scraping and can be customized to fit your use case and access control policies. This tutorial uses just plain JavaScript and a Node server with SQLite on the back end. For language- or framework-specific setups, see our quickstarts.
Estimated time: < 15 minutes
This tutorial requires the Bot Detection Smart Signal, which is only available on paid plans.

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Prerequisites

Before you begin, make sure you have the following:
  • A copy of the starter repository (clone with Git or download as a ZIP)
  • Node.js (v20 or later) and npm installed
  • Your favorite code editor
  • Basic knowledge of JavaScript

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1. Create a Fingerprint account and get your API keys

  1. Sign up for a free Fingerprint trial, or log in if you already have an account.
  2. After signing in, go to the API keys page in the dashboard.
  3. Save your public API key, which you’ll use to initialize the Fingerprint 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.

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2. Set up your project

  1. Clone or download the starter repository and open it in your editor.
Terminal
git clone https://github.com/fingerprintjs/use-case-tutorials.git
  1. This tutorial will be using the web-scraping folder. The project is organized as follows:
Project structure
.
├── public/
│   ├── index.html    # Flight search page
│   └── index.js      # Front-end logic to handle flight searches
├── server/
│   ├── db.js         # Initializes SQLite and exports a database connection
│   ├── flights.js    # Flight search and bot detection logic
│   └── server.js     # Serves static files and search endpoint
└── .env.example      # Example environment variables
  1. Install dependencies:
Terminal
npm install
  1. Copy or rename .env.example to .env, then add your Fingerprint API keys:
Terminal
FP_PUBLIC_API_KEY=your-public-key
FP_SECRET_API_KEY=your-secret-key
  1. Start the server:
Terminal
npm run dev
  1. Visit http://localhost:3000 to view the mock flight search page from the starter app. Try a sample query (for example, SFO to MIA) and click Search.
  2. Then try to search for flights 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 search request returns all results. By default, the server does not distinguish between bots and real users.
Terminal
node test-bot.js

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3. Add Fingerprint to the front end

In this step, you’ll load the Fingerprint client when the page loads and trigger identification when the user clicks Search. The client returns a requestId associated with the identification request. You’ll send the requestId to your server along with the search inputs. Your server will then call the Fingerprint Events API to securely retrieve the full identification details, including bot detection and other signals.
  1. At the top of public/index.js, load the Fingerprint JavaScript agent:
public/index.js
const fpPromise = import(
  `https://fpjscdn.net/v3/${window.FP_PUBLIC_API_KEY}`
).then((FingerprintJS) => FingerprintJS.load({ region: "us" }));
  1. Make sure to change region to match your workspace region (e.g., eu for Europe, ap for Asia, us for Global (default)).
  2. Near the bottom of public/index.js, the Search button already has an event handler for submitting the query. Inside this handler, request visitor identification using get() and include the returned requestId when sending the search request to the server:
public/index.js
searchBtn.addEventListener("click", async () => {
  // ...

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

  try {
    const res = await fetch("/api/fetch-flights", {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify({ from, to, departDate, passengers, 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 and determine if they are a bot. 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, check out our documentation on using Sealed Client Results to return full identification details as an encrypted payload from the get() method.

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

Next, pass the requestId through to your flight search logic, initialize the Fingerprint Server API client, and fetch the full visitor identification event so you can access the Bot Detection Smart Signal.
  1. In the back end, the server/server.js file already defines API routes for the app. Notice that the /api/fetch-flights route simply passes the request body to a fetchFlights function that is defined in the server/flights.js file.
server/server.js
app.post("/api/fetch-flights", async (req, reply) => {
  const result = await fetchFlights(req.body);
  return reply.send(result);
});
  1. The server/flights.js file contains the logic for handling flight searches. Start by importing and initializing the Fingerprint Server API client there, and load your environment variables with dotenv.
server/flights.js
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,
});
  1. Make sure to change region to match your workspace region (e.g., EU for Europe, AP for Asia, Global for Global (default)).
  2. Update the fetchFlights function to accept the requestId and use it to fetch the full identification event details from Fingerprint:
server/flights.js
export async function fetchFlights({ from, to, departDate, requestId }) {
  if (!from || !to || !departDate || !requestId) {
    console.error("Missing required fields.");
    return { success: false, message: "Missing required fields." };
  }

  const event = await fpServerApiClient.getEvent(requestId);

  // ...
}
Using the requestId, the Fingerprint server client will retrieve the full data for the visitor identification request. The returned object will contain the visitor ID, IP address, device, and browser details, as well as Smart Signals, including 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 our demo playground. For additional checks to ensure the validity of the data coming from your front end, view how to protect from client-side tampering and replay attacks in our documentation.

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5. Block content scraping bots

Web scraping relies on automated requests, so rejecting bots outright helps protect proprietary data. 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 retrieving flight data.
  1. Continuing in the fetchFlights function in server/flights.js, check the bot signal returned in the event object and block bots:
server/flights.js
export async function fetchFlights({ from, to, departDate, requestId }) {
  // ...

  const event = await fpServerApiClient.getEvent(requestId);

  const botDetected = event.products?.botd?.data?.bot?.result !== "notDetected";

  if (botDetected) {
    console.error("Bot detected.");
    return { flights: [] };
  }

  // ...
}
You can also add Suspect Score as a secondary defense layer. The Suspect Score is a weighted representation of all Smart Signals present in the identification payload, helping to identify suspicious or automated activity. You likely wouldn’t block searches based only on a high risk score, but you can use it to change how you respond, such as by adding a rate limit or requiring additional verification.
  1. Below the bot detection check, add a condition that reads the Suspect Score from the event object and blocks the search if it exceeds a chosen threshold (for example, 20):
server/flights.js
export async function fetchFlights({ from, to, departDate, requestId }) {
  // ...

  const botDetected = event.products?.botd?.data?.bot?.result !== "notDetected";

  if (botDetected) {
    console.error("Bot detected.");
    return { flights: [] };
  }

  const suspectScore = event.products?.suspectScore?.data?.result || 0;

  if (suspectScore > 20) {
    console.error(`High Suspect Score detected: ${suspectScore}`);
    return { flights: [] };
  }

  // ...
}
Smart Signals allow you to protect your site and prevent web scraping. You can extend this by analyzing additional signals, adjusting rate limits, varying responses for suspicious traffic, and more.
This is a minimal example to show how to implement Fingerprint. In a real application, make sure to implement proper security practices, error handling, and access controls that align with your production standards.

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7. Test your implementation

Now that everything is wired up, you can test the full protected search flow.
  1. Start your server if it isn’t already running and open http://localhost:3000:
Terminal
npm run dev
  1. Try a normal search (for example, SFO to JFK). You should get matching flights returned.
  2. Next, run the included headless bot test script. While the app is running, execute node test-bot.js and observe that the automated search requests do not return any results and the bot’s access is blocked.
Terminal
node test-bot.js
Note: If you encounter errors launching the automated browser, make sure you have the testing browser installed:
Terminal
npx puppeteer browsers install chrome

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Next steps

You now have a working flight search flow that blocks scraping bots with Fingerprint. From here, you can expand the logic with more Smart Signals, fine-tune rules based on your business policies, or layer in additional defenses, such as rate limiting or dynamic content obfuscation. To dive deeper, explore our other use case tutorials for more step-by-step examples. Check out these related resources: