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Database

Improper control of interaction frequency

Need

Enforcement of rate limiting to control user interaction frequency, including limits on password change requests

Context

• Usage of Java for building cross-platform applications

• Usage of javax.servlet for Java web application development

• Usage of javax.servlet.http for handling HTTP requests and responses in Java web applications

• Usage of java.io.IOException for handling input/output errors in Java programming

Description

1. Non compliant code

// --- Rate limiting ---
import javax.servlet.*;
import javax.servlet.http.*;

public class NoRateLimitServlet extends HttpServlet {

    protected void doPost(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException {
        String userContent = request.getParameter("userContent");...

**Rate limiting:** The above Java servlet code is vulnerable to DDoS attacks because it doesn't implement any rate limiting mechanism. The `doPost` method reads the "userContent" parameter from the request and processes it without checking the frequency of the requests from a particular user or IP address. This means that an attacker can send a large number of requests in a short period of time, leading to a Denial of Service (DoS) attack. This can cause the server to become overwhelmed with requests, leading to slow response times for other users, or in severe cases, causing the server to crash. In addition, this could also be exploited to perform a Brute Force attack, where an attacker attempts to guess a user's password by systematically trying every possible combination until finding the correct one. Without rate limiting, an attacker could make an unlimited number of attempts in a very short period of time. Therefore, it's crucial to implement a rate limiting mechanism to protect the system from such attacks. **Password change limit:** In the above code, `ChangePasswordServlet` is a servlet that handles password change requests. It takes in three parameters from the client - "username", "oldPassword", and "newPassword". It first retrieves the user from the database using the username. If the user exists and the old password matches the current password of the user, it updates the password in the database with the new password. The vulnerability here is that there is no limit on the number of password change requests a user can make in a day. An attacker could potentially exploit this by repeatedly changing the password and causing a denial of service or even potentially guessing the password if there are no other security measures in place like account lockouts or captcha.

2. Steps

• Implement rate limiting mechanism to restrict the number of requests a user can make within a certain time period.

• Identify the appropriate rate limit threshold based on the system's requirements and expected user behavior.

• Use a reliable and efficient algorithm to track and enforce the rate limit, such as token bucket algorithm or sliding window algorithm.

• Store the rate limit information for each user, such as the number of requests made and the timestamp of the last request, in a persistent storage.

• Check the rate limit for each incoming request and compare it with the user's rate limit information stored in the persistent storage.

• If the user has exceeded the rate limit, return an appropriate error response (e.g., HTTP 429 Too Many Requests) and prevent further processing of the request.

• Consider implementing different rate limits for different types of requests or user roles, if necessary.

• Monitor and log rate limit violations for analysis and troubleshooting purposes.

• Regularly review and adjust the rate limit thresholds based on system performance and user behavior patterns.

• Implement a password change limit policy

• Track the number of password change requests made by a user

• Set a maximum limit for password change requests within a specific time period

• Enforce the password change limit by checking the number of requests made by a user

• Return an error message or block the password change request if the limit is exceeded

3. Secure code example

// --- Rate limiting ---
import javax.servlet.*;
import javax.servlet.http.*;
import java.util.concurrent.TimeUnit;
import com.google.common.util.concurrent.RateLimiter;

public class RateLimitServlet extends HttpServlet {
...

**Rate limiting:** The above code implements a rate limiting mechanism using Google's Guava library, which provides a RateLimiter class that uses the token bucket algorithm. The `RateLimiter.create(5.0)` creates a RateLimiter that allows 5 requests per second. In the `doPost` method, `rateLimiter.tryAcquire(1, TimeUnit.SECONDS)` is used to try to acquire a permit. If a permit is not available (i.e., the rate limit has been exceeded), it returns false immediately. In this case, the servlet responds with an HTTP 429 Too Many Requests status code and returns without processing the request. If a permit is available, the method returns true and the servlet continues to process the request. This approach effectively limits the rate at which a user can make requests to the servlet, mitigating the risk of denial-of-service attacks and ensuring fair usage of resources. Please note that this is a simple implementation and may need to be adjusted based on your specific requirements. For example, you might want to implement different rate limits for different types of requests or user roles, or store the rate limit information in a persistent storage to enforce the rate limit across multiple instances of the servlet. **Password change limit:** The updated code now includes a password change limit policy. This policy is enforced by tracking the number of password change requests made by each user. A `HashMap` named `passwordChangeCounter` is used to store the number of password change requests made by each user. The key is the username and the value is the number of password change requests. When a password change request is made, the code first checks if the user exists and if the old password is correct. If these conditions are met, the code then checks the `passwordChangeCounter` to see how many password change requests the user has made. If the user has made more than or equal to the maximum number of password changes allowed per day (`MAX_PASSWORD_CHANGES_PER_DAY`), the code returns an error message and does not allow the password change. If the user has not exceeded the limit, the password is changed, the user's password change count is incremented in the `passwordChangeCounter`, and a success message is returned. This policy helps to prevent abuse of the password change feature and enhances the security of the application.