Asymmetric denial of service - PHP

Asymmetric denial of service - PHP

Need

The solution to the vulnerability of asymmetric denial of service is the need for robust resource management and request validation mechanisms.

Context

  • Usage of PHP 7.0 for server-side scripting and web development
  • Usage of Illuminate/Http for HTTP request handling in Laravel
  • Usage of Illuminate/Support for providing foundational support classes and utilities in Laravel framework

Description

Non compliant code

        all();

        // Vulnerable code: No limit on the amount of data that can be processed
        foreach ($data as $item) {
            // Simulates processing of data which could potentially consume a lot of resources
            sleep(1);
        }

        return response()->json(['status' => 'success']);
    }
}

The above code represents a controller in a Laravel application that processes incoming requests. The vulnerability lies in the processRequest method, which processes all data from the request without any limitation.

This method takes an HTTP request as input and retrieves all the data from it. For each item in the data, it simulates processing of the data by sleeping for 1 second. This could potentially consume a lot of resources if the amount of data is large.

As a result, an attacker could potentially send a single request with a large amount of data, causing the server to consume a significant amount of resources and potentially become unresponsive. This is an example of an asymmetric denial of service attack.

Furthermore, if an attacker discovers a specific data input that breaks the application, they could send a single malicious request that causes the application to crash, rendering the server unresponsive.

This code is vulnerable because it does not implement any form of rate limiting or input validation. It blindly processes all data from the request, regardless of the amount or nature of the data. This leaves the server open to potential denial of service attacks.

Steps

  • Implement a limit on the amount of data that can be processed in a single request. This can be done by checking the size of the incoming data and rejecting the request if it exceeds a certain threshold.
  • Use a rate limiting mechanism to limit the number of requests a client can make in a certain time period. This can help prevent amplification attacks.
  • Consider using a queue system for processing requests. This can help manage the load on the server and prevent it from becoming unresponsive.
  • Implement proper error handling to ensure that a single malicious request does not break the application.
  • Consider using a load balancer to distribute incoming traffic and prevent any single server from being overwhelmed.

Compliant code

        getSize() > 1000) {
            return response()->json(['status' => 'error', 'message' => 'Request size limit exceeded'], 413);
        }

        // Implement rate limiting
        if (RateLimiter::tooManyAttempts($request->ip(), 10)) {
            return response()->json(['status' => 'error', 'message' => 'Too many requests'], 429);
        }

        $data = $request->all();

        // Use a queue for processing data
        ProcessDataJob::dispatch($data);

        return response()->json(['status' => 'success']);
    }
}

The fixed code includes several measures to prevent asymmetric denial of service attacks:

1. Size Limit: The getSize() method is used to check the size of the incoming request. If the size exceeds 1000 bytes, the request is rejected with a 413 (Payload Too Large) status code.

2. Rate Limiting: The tooManyAttempts() method from Laravel's RateLimiter facade is used to limit the number of requests a client can make. In this case, if a client makes more than 10 requests, they will receive a 429 (Too Many Requests) status code.

3. Queue System: Instead of processing the data immediately in the controller, a job is dispatched to a queue for processing. This helps manage the load on the server and prevent it from becoming unresponsive.

These measures help to limit the amount of data that can be processed in a single request, limit the rate of incoming requests, and manage the load on the server, thereby mitigating the risk of asymmetric denial of service attacks.

References