🚧 Bypassing CAPTCHA Security

Introduction

In this lab, we will explore the concept of CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) security and its significance in web applications. CAPTCHA is designed to prevent automated programs (bots) from exploiting web applications by distinguishing between human users and computer programs. The objective of this lab is to understand the vulnerabilities associated with CAPTCHAs and learn techniques to bypass them.

Understanding CAPTCHA Security

In this step, we will gain insights into the purpose and importance of CAPTCHA security.

CAPTCHA was introduced to mitigate various security threats, such as brute-force attacks, automated registrations, and denial-of-service attacks. By presenting a challenge that is relatively easy for humans but difficult for computers to solve, CAPTCHAs aim to verify that the user is indeed a human and not an automated program.

However, as with any security mechanism, CAPTCHAs are not foolproof, and attackers have developed techniques to bypass or break them. In this lab, we will explore two main approaches to bypass CAPTCHA security:

1. Circumventing CAPTCHA: This approach involves exploiting vulnerabilities in the application's code or logic, enabling an attacker to skip the CAPTCHA validation step altogether.

2. CAPTCHA Recognition: This approach involves developing algorithms or techniques to automatically recognize and solve the CAPTCHA challenge, effectively defeating the purpose of the CAPTCHA.

## No code or commands are required for this step.

Circumventing CAPTCHA

In this step, we will learn how to circumvent CAPTCHA validation by exploiting vulnerabilities in the application's code or logic.

Consider a web application that implements a two-step process for changing a user's password:

1. Step 1: The user enters the new password, confirms it, and solves the CAPTCHA challenge.
2. Step 2: The user confirms the password change.

The application's code might look like this:

<?php
if (isset($_POST['Change']) && $_POST['step'] == '1') {
    // Hide the CAPTCHA form
    $hide_form = true;

    // Get input
    $pass_new = $_POST['password_new'];
    $pass_conf = $_POST['password_conf'];

    // Check CAPTCHA
    // ... (code omitted for brevity)

    if ($pass_new == $pass_conf) {
        // Show next stage for the user
        echo "
            <pre><br />You passed the CAPTCHA! Click the button to confirm your changes.<br /></pre>
            <form action=\"#\" method=\"POST\">
                <input type=\"hidden\" name=\"step\" value=\"2\" />
                <input type=\"hidden\" name=\"password_new\" value=\"{$pass_new}\" />
                <input type=\"hidden\" name=\"password_conf\" value=\"{$pass_conf}\" />
                <input type=\"submit\" name=\"Change\" value=\"Change\" />
            </form>";
    }
}

if (isset($_POST['Change']) && $_POST['step'] == '2') {
    // Hide the CAPTCHA form
    $hide_form = true;

    // Get input
    $pass_new = $_POST['password_new'];
    $pass_conf = $_POST['password_conf'];

    // Check if passwords match
    if ($pass_new == $pass_conf) {
        // Update database
        // ... (code omitted for brevity)
    }
}
?>

In this code, we can observe that in step 2, the application does not validate the CAPTCHA again. This allows an attacker to bypass the CAPTCHA validation by directly submitting the request with step=2.

To demonstrate this, follow these steps:

1. Open your web browser and navigate to the application's "Change Password" page.
2. Enter the new password you want to set in the "New Password" and "Confirm Password" fields.
3. Right-click on the page and select "Inspect Element" or "Inspect" to open the browser's developer tools.
4. Go to the "Network" tab and filter for the POST request made when you click the "Change" button.
5. Right-click on the POST request and select "Edit and Resend" or a similar option (depending on your browser).
6. In the request body, change the step parameter from 1 to 2.
7. Click the "Send" button to submit the modified request.

You should now see a message indicating that the password has been successfully changed, even though you did not solve the CAPTCHA challenge.

## No code or commands are required for this step.

CAPTCHA Recognition

In this step, we will explore techniques for recognizing and solving CAPTCHAs automatically, effectively defeating their purpose.

One common approach to CAPTCHA recognition is through image processing and machine learning techniques. Here's a high-level overview of the process:

1. Preprocessing: The CAPTCHA image is preprocessed to remove noise, normalize brightness and contrast, and convert it to a suitable format for further processing.

2. Segmentation: The preprocessed image is segmented to separate the individual characters or symbols present in the CAPTCHA.

3. Feature Extraction: Relevant features are extracted from the segmented characters or symbols, such as their shapes, pixel distributions, or other characteristics.

4. Classification: Using a trained machine learning model, the extracted features are classified to identify the individual characters or symbols present in the CAPTCHA.

5. Post-processing: The recognized characters or symbols are combined to form the final solution to the CAPTCHA challenge.

While implementing a complete CAPTCHA recognition system is beyond the scope of this lab, you can explore open-source libraries and tools that provide such functionality, such as pytesseract (Python), tesseract-ocr (C++), or online CAPTCHA solving services.

## No code or commands are required for this step.

Summary

In this lab, we explored the concept of CAPTCHA security and its vulnerabilities. We learned two main approaches to bypass CAPTCHA validation: circumventing CAPTCHA by exploiting vulnerabilities in the application's code or logic, and CAPTCHA recognition through image processing and machine learning techniques. By understanding these vulnerabilities and techniques, developers can design more robust CAPTCHA implementations and security professionals can better assess and mitigate potential risks associated with CAPTCHA security.