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How Score-based CAPTCHA systems like reCAPTCHA v3 work

Score-based CAPTCHA systems, like Google's reCAPTCHA v3, work by assigning a score to each interaction on your website. This score represents the likelihood that the interaction is legitimate (from a human user) or potentially abusive (from a bot). Unlike traditional CAPTCHA systems that require users to solve a challenge, score-based CAPTCHAs operate in the background, providing a frictionless user experience. Here’s how it works in detail:

How Score-Based CAPTCHA Systems Work

Integration and Setup:
- You need to integrate reCAPTCHA v3 on your website by including the reCAPTCHA library and setting up your site and secret keys in the Google reCAPTCHA admin console.
- Add the reCAPTCHA script to your HTML and set up the reCAPTCHA client-side code to obtain the token.
Token Generation:
- When a user interacts with your website (e.g., loading a page, submitting a form), reCAPTCHA v3 generates a token for that interaction.
- The reCAPTCHA client-side script collects data about the interaction and the user's behavior on the page.
Scoring:
- The token, along with the collected data, is sent to Google's reCAPTCHA servers.
- Google's machine learning models analyze the data to determine the likelihood that the interaction is legitimate. Factors considered include mouse movements, typing patterns, and other behavior signals.
- A score between 0.0 and 1.0 is returned, where 1.0 indicates a high likelihood of a human user, and 0.0 indicates a high likelihood of a bot.
Backend Validation:
- The token and the score are sent to your server for validation.
- Your server sends a request to the reCAPTCHA verification API with the token and your secret key to validate the token and get the score.
Action Based on Score:
- Based on the returned score, you can decide how to handle the interaction. Common actions include:
  - Allowing the interaction if the score is above a certain threshold.
  - Requiring additional verification (e.g., two-factor authentication) if the score is borderline.
  - Blocking the interaction if the score is very low.
  - Logging the score for analytics or further review.

Example Integration of reCAPTCHA v3

Client-Side Code (HTML + JavaScript)

<!DOCTYPE html>
<html>
<head>
  <title>reCAPTCHA v3 Example</title>
  <script src="https://www.google.com/recaptcha/api.js?render=your_site_key"></script>
</head>
<body>
  <form id="demo-form" action="/submit" method="POST">
    <!-- Your form fields here -->
    <button type="submit">Submit</button>
  </form>

  <script>
    grecaptcha.ready(function() {
      grecaptcha.execute('your_site_key', { action: 'submit' }).then(function(token) {
        var form = document.getElementById('demo-form');
        var input = document.createElement('input');
        input.type = 'hidden';
        input.name = 'recaptcha_token';
        input.value = token;
        form.appendChild(input);
      });
    });
  </script>
</body>
</html>

Server-Side Code (Node.js/Express)

const express = require('express');
const bodyParser = require('body-parser');
const axios = require('axios');

const app = express();
app.use(bodyParser.urlencoded({ extended: true }));

app.post('/submit', async (req, res) => {
  const token = req.body.recaptcha_token;
  const secretKey = 'your_secret_key';

  try {
    const response = await axios.post(`https://www.google.com/recaptcha/api/siteverify`, null, {
      params: {
        secret: secretKey,
        response: token
      }
    });

    const score = response.data.score;

    if (score >= 0.5) {
      // Allow the submission
      res.send('Success!');
    } else {
      // Reject the submission or ask for further verification
      res.status(403).send('Are you a bot?');
    }
  } catch (error) {
    res.status(500).send('Error verifying reCAPTCHA');
  }
});

app.listen(3000, () => {
  console.log('Server is running on port 3000');
});

Advantages of Score-Based CAPTCHA Systems

User Experience:
- Users do not need to solve challenges, making the experience seamless and less intrusive.
Security:
- Advanced machine learning algorithms analyze behavior patterns, making it difficult for bots to mimic human actions.
Flexibility:
- Allows for a range of responses based on the confidence score, enabling more nuanced handling of interactions.

Published on: Jul 13, 2024, 04:37 AM