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Lack of data validation

Need​

Implementation of proper data validation and sanitization

Context​

  • Usage of C# 7.0 for modern language features and enhancements
  • Usage of Microsoft.AspNetCore.Mvc for building web applications with ASP.NET Core
  • Usage of Microsoft.EntityFrameworkCore for database access and management in .NET applications

Description​

Non compliant code​

[HttpPost]
public async Task<IActionResult> UpdateUser(string id, [FromBody]User user)
{
    // Fetch the user from the database
    var currentUser = await _context.Users.FindAsync(id);

    if(currentUser == null)
    {
        return NotFound();
    }

    // Update user fields
    currentUser.Name = user.Name;
    currentUser.Email = user.Email;

    // Save changes
    await _context.SaveChangesAsync();

    return Ok(currentUser);
}

In the above code, a HTTP POST request is being made to update a user's details. The method UpdateUser takes in a string id and a user object from the request body.

The vulnerability lies in the fact that there is no validation on the id parameter. This parameter is used directly to find the user in the database. If the id is composed of invalid data, such as a string of letters, the FindAsync method may fail or produce unexpected results.

Moreover, the user object from the request body is used directly to update the currentUser object, without any validation of the data it contains. This can lead to potential security vulnerabilities, such as data tampering or injection attacks. For example, an attacker can modify the Email field to an invalid or malicious value, which can then be saved to the database.

In summary, the lack of data validation on both the id parameter and the user object from the request body can lead to potential security vulnerabilities.

Steps​

  • Implement server-side data validation to ensure that the input data is valid and meets the required criteria.
  • Validate the 'id' parameter to ensure that it is in the correct format and matches the expected data type.
  • Validate the 'user' object to ensure that the fields contain valid data, such as checking for the presence of required fields and validating the format of email addresses.
  • Use appropriate validation techniques, such as regular expressions or built-in validation attributes, to enforce data validation rules.
  • Handle validation errors gracefully by returning appropriate error responses to the client, indicating the specific validation failures.
  • Consider implementing input sanitization techniques to prevent potential security vulnerabilities, such as cross-site scripting (XSS) attacks.
  • Regularly update and review the data validation logic to adapt to changing requirements and potential new vulnerabilities.

Compliant code​

[HttpPost]
public async Task<IActionResult> UpdateUser(string id, [FromBody]User user)
{
    // Validate ID
    if (string.IsNullOrEmpty(id) || !Regex.IsMatch(id, @"^[0-9]+$"))
    {
        return BadRequest("Invalid ID format");
    }

    // Validate User object
    if (user == null || string.IsNullOrEmpty(user.Name) || string.IsNullOrEmpty(user.Email) || !Regex.IsMatch(user.Email, @"^[\\w-]+(\\.[\\w-]+)*@([\\w-]+\\.)+[a-zA-Z]{2,7}$"))
    {
        return BadRequest("Invalid User data");
    }

    // Fetch the user from the database
    var currentUser = await _context.Users.FindAsync(id);

    if(currentUser == null)
    {
        return NotFound();
    }

    // Update user fields
    currentUser.Name = user.Name;
    currentUser.Email = user.Email;

    // Save changes
    await _context.SaveChangesAsync();

    return Ok(currentUser);
}

The updated code now includes server-side data validation for both the 'id' parameter and the 'user' object.

  • The 'id' parameter is validated to ensure it is not null or empty and that it only contains numeric characters. This is done using the IsNullOrEmpty method and a regular expression match.

  • The 'user' object is validated to ensure it is not null and that the 'Name' and 'Email' fields are not null or empty. The 'Email' field is also validated to ensure it is in the correct format using a regular expression match.

  • If any of these validation checks fail, a 'BadRequest' response is returned with a message indicating the nature of the validation failure.

  • If the validation checks pass, the code proceeds as before, fetching the user from the database, updating the user fields, saving the changes, and returning the updated user.

This updated code helps to ensure that only valid data is used in the application, reducing the risk of potential security vulnerabilities and data integrity issues.

References​

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