Lua for Rate Limiting

Lua for Rate Limiting in MediaWiki

This article provides a comprehensive introduction to using Lua scripting for implementing rate limiting within a MediaWiki installation. Rate limiting is crucial for protecting your wiki from abuse, such as spamming, denial-of-service (DoS) attacks, and excessive API usage. This guide is geared towards beginners with some basic understanding of MediaWiki and a willingness to learn Lua.

What is Rate Limiting?

Rate limiting controls the frequency with which users (or IP addresses) can perform specific actions within a given timeframe. It's a fundamental security measure employed across many web applications. In the context of a wiki, this can involve limiting:

Edits per minute/hour
API calls per minute/hour
Login attempts per minute
Creation of new pages per minute

Without rate limiting, a malicious actor could overwhelm your wiki with requests, potentially crashing it or filling it with unwanted content. Effective rate limiting enhances the stability and security of your wiki environment. Understanding User rights management is also crucial in conjunction with rate limiting.

Why Use Lua for Rate Limiting?

MediaWiki 1.40 and later versions offer robust Lua scripting capabilities through the Scribunto extension. Using Lua for rate limiting provides several advantages:

**Flexibility:** Lua allows for complex and customized rate limiting rules tailored to your wiki's specific needs. You can define different limits for different user groups, actions, or even specific pages.
**Performance:** Lua is a lightweight and fast scripting language, minimizing the performance impact of rate limiting checks. Compared to implementing rate limiting solely in PHP, Lua generally offers better performance.
**Maintainability:** Lua code is relatively easy to read and maintain, making it simpler to update and modify your rate limiting rules as needed.
**Centralized Logic:** Lua modules can encapsulate rate limiting logic, promoting code reuse and reducing redundancy. This ties into the broader concept of Extension development.
**Integration with Existing Systems:** Lua can interact with other MediaWiki components and external data sources, allowing you to incorporate additional factors into your rate limiting decisions.

Core Concepts

Before diving into the code, let's outline the core concepts involved in rate limiting:

**Identifier:** This uniquely identifies the entity being rate limited. Common identifiers include:

   *   User ID (for registered users)
   *   IP Address (for anonymous users)
   *   API Token (for API requests)

**Action:** The specific action being rate limited (e.g., "edit", "api_call", "login").
**Window:** The timeframe over which the rate is measured (e.g., 60 seconds, 3600 seconds).
**Limit:** The maximum number of actions allowed within the window.
**Storage:** A mechanism to store the number of actions performed by each identifier within each window. Common storage methods include:

   *   mw.storage (MediaWiki's built-in storage system)
   *   External databases (e.g., Redis, Memcached) – requires additional extension support.

Implementing Rate Limiting with Lua and mw.storage

This example demonstrates a basic rate limiting implementation using Lua and `mw.storage`. This approach is suitable for smaller wikis or as a starting point for more complex implementations. Larger wikis might benefit from using an external database for improved scalability.

First, create a Lua module (e.g., `Module:RateLimit`).

```lua local p = {}

local storage = mw.storage.new("ratelimit") -- Use mw.storage for persistence

local function get_key(identifier, action, window)

 -- Construct a unique key for each identifier, action, and window
 return identifier .. ":" .. action .. ":" .. window

end

function p.is_rate_limited(identifier, action, window, limit)

 -- Check if the identifier is rate limited for the given action and window
 local key = get_key(identifier, action, window)
 local count = tonumber(storage:get(key) or "0") -- Get the current count, default to 0

 if count >= limit then
   return true -- Rate limited
 else
   storage:set(key, count + 1) -- Increment the count
   return false -- Not rate limited
 end

end

function p.reset_rate_limit(identifier, action, window)

 -- Reset the rate limit for the given identifier, action, and window
 local key = get_key(identifier, action, window)
 storage:delete(key)

end

return p ```

- Explanation:**

1. **`local p = {}`**: Creates a table `p` which will hold the module's functions. 2. **`local storage = mw.storage.new("ratelimit")`**: Creates a new storage object using `mw.storage`. The string "ratelimit" is the storage key, used to identify this specific storage area. This allows the data to be persisted across page views. 3. **`local function get_key(identifier, action, window)`**: A helper function to construct a unique key for each rate limiting entry. This key is used to store and retrieve the count in `mw.storage`. 4. **`function p.is_rate_limited(identifier, action, window, limit)`**: This is the core function. It checks if the identifier has exceeded the rate limit.

   *   It retrieves the current count from `mw.storage` using the generated key. If the key doesn't exist, it defaults to 0.
   *   If the count is greater than or equal to the limit, it returns `true` (rate limited).
   *   Otherwise, it increments the count in `mw.storage` and returns `false` (not rate limited). `tonumber` ensures the value retrieved from storage is treated as a number.

5. **`function p.reset_rate_limit(identifier, action, window)`**: This function allows you to manually reset the rate limit for a specific identifier, action, and window. This might be useful for administrative purposes or to handle exceptional cases. 6. **`return p`**: Returns the table containing the module's functions.

Integrating Rate Limiting into MediaWiki Hooks

Now, let's integrate this Lua module into MediaWiki using hooks. We'll use the `EditPage::beforeSave` hook to rate limit edits. You'll need to add this code to your `LocalSettings.php` file.

```php <?php // ... other settings ...

$wgHooks['EditPage::beforeSave'][] = 'myRateLimitEdit';

function myRateLimitEdit($editor, $article, $content, $summary, $editmode, $watchlistrights) {

 $title = $article->getTitle();
 $user = $editor->getUser();
 $identifier = $user->getId() ? $user->getId() : $editor->getIPAddress(); // Use user ID if logged in, IP otherwise
 $action = "edit";
 $window = 60; // 60 seconds
 $limit = 5; // 5 edits per minute

 $module = mw.loadModule('Module:RateLimit');
 if ($module.is_rate_limited(identifier, action, window, limit)) {
   // Rate limited!  Prevent the edit.
   $editor->getOutput()->addError("You have exceeded the edit rate limit. Please try again later.");
   return false; // Prevent the save
 }

 return true; // Allow the save

} ```

- Explanation:**

1. **`$wgHooks['EditPage::beforeSave'][] = 'myRateLimitEdit';`**: Registers the `myRateLimitEdit` function as a callback for the `EditPage::beforeSave` hook. This hook is triggered before an edit is saved. 2. **`$title = $article->getTitle();`**: Gets the title of the page being edited. 3. **`$user = $editor->getUser();`**: Gets the user object. 4. **`$identifier = $user->getId() ? $user->getId() : $editor->getIPAddress();`**: Determines the identifier to use for rate limiting. If the user is logged in, it uses their user ID. Otherwise, it uses their IP address. 5. **`$action = "edit";`**: Sets the action to "edit". 6. **`$window = 60;`**: Sets the window to 60 seconds (1 minute). 7. **`$limit = 5;`**: Sets the limit to 5 edits per minute. 8. **`$module = mw.loadModule('Module:RateLimit');`**: Loads the Lua module `Module:RateLimit`. 9. **`if ($module.is_rate_limited(identifier, action, window, limit))`**: Calls the `is_rate_limited` function in the Lua module with the appropriate parameters. 10. **`$editor->getOutput()->addError("You have exceeded the edit rate limit. Please try again later.");`**: If the user is rate limited, an error message is added to the output. 11. **`return false;`**: Returns `false` to prevent the edit from being saved. 12. **`return true;`**: Returns `true` to allow the edit to be saved.

Advanced Considerations

**External Databases:** For larger wikis, consider using an external database (e.g., Redis, Memcached) to store rate limiting data. This provides better scalability and performance than `mw.storage`. You'll need to use a PHP extension to connect to the database from Lua.
**Different Rate Limits:** Implement different rate limits for different user groups (e.g., administrators, confirmed users, anonymous users). Use User groups and conditional logic in your Lua code.
**API Rate Limiting:** Protect your wiki's API by implementing rate limiting for API calls. Use the `ApiRestBase::beforePost` or `ApiRestBase::beforeGet` hooks. Consider using API tokens as identifiers.
**Dynamic Rate Limits:** Adjust rate limits dynamically based on server load or other factors. This requires more complex logic and potentially external monitoring tools.
**Whitelisting:** Allow certain users or IP addresses to bypass rate limiting. This is useful for administrators or trusted users.
**CAPTCHAs:** Combine rate limiting with CAPTCHAs to further mitigate abuse. reCAPTCHA is a popular option.
**Logging:** Log rate limiting events for auditing and analysis. Use MediaWiki's logging mechanisms or a custom logging system.
**Consider using a sliding window counter:** Instead of a fixed window, a sliding window counter provides more accurate rate limiting. Implementations are more complex but provide better granularity. See resources like [1](https://redis.io/docs/reference/data-types/sliding-window/) for examples.
**Using Bloom Filters:** Bloom filters can be used to efficiently check if an IP address or user ID has been seen before, reducing the load on the storage system. [2](https://en.wikipedia.org/wiki/Bloom_filter)
**Implement a backoff strategy:** When a user is rate limited, suggest a backoff time to avoid repeated attempts. [3](https://en.wikipedia.org/wiki/Exponential_backoff)

Monitoring and Tuning

After implementing rate limiting, it's crucial to monitor its effectiveness and tune the limits as needed. Monitor:

The number of rate limiting events.
Server load and performance.
User feedback.

Adjust the limits based on this data to find the optimal balance between security and usability. Tools like Prometheus and Grafana can be used for monitoring. Analyzing Network traffic patterns can also help identify potential abuse. Consider using Statistical analysis to determine optimal threshold values. Look for Correlation between rate limiting events and other security incidents. Utilize Data visualization to understand trends. Employ Anomaly detection algorithms to identify unusual activity. Regularly review Security logs for suspicious patterns. Monitor Response times to ensure rate limiting doesn't negatively impact user experience. Track Error rates to identify potential issues with the implementation. Utilize A/B testing to compare different rate limiting configurations. Implement Alerting systems to notify administrators of potential problems. Analyze User behavior to identify patterns and adjust limits accordingly. Consider using Machine learning to predict and prevent abuse. Employ Trend analysis to identify emerging threats. Utilize Forensic analysis to investigate security incidents. Monitor API usage to identify potential abuse. Track Resource consumption to ensure rate limiting doesn't negatively impact server performance. Analyze Log data for suspicious patterns. Employ Threat intelligence feeds to identify known malicious actors. Utilize Security information and event management (SIEM) systems for centralized logging and analysis. Monitor System metrics to identify potential bottlenecks. Track User activity to identify potential abuse. Analyze Network flows to identify suspicious traffic. Implement Intrusion detection systems (IDS) to detect and prevent attacks. Utilize Vulnerability scanners to identify security weaknesses. Employ Penetration testing to simulate attacks and identify vulnerabilities. Monitor Database activity to identify potential abuse. Track File uploads to prevent malicious content. Analyze Page views to identify unusual traffic patterns. Utilize Web analytics to understand user behavior. Employ Content delivery networks (CDNs) to improve performance and reduce load. Monitor Cache hit rates to ensure efficient caching. Track DNS queries to identify potential threats. Analyze SSL/TLS certificates to ensure secure connections. Utilize Firewalls to block malicious traffic. Employ Load balancers to distribute traffic and improve performance. Monitor Server uptime to ensure high availability. Track Disk space usage to prevent outages. Analyze CPU usage to identify potential bottlenecks. Utilize Memory usage monitoring to identify potential leaks. Employ Process monitoring to identify rogue processes. Monitor Network bandwidth usage to identify potential congestion. Track Latency to identify performance issues. Analyze Packet loss to identify network problems. Utilize Network monitoring tools to identify potential threats. Employ Security audits to identify vulnerabilities and weaknesses. Monitor Compliance with security standards to ensure adherence to best practices. Track Incident response times to ensure efficient handling of security incidents. Analyze Root cause analysis to identify the underlying causes of security incidents. Utilize Post-incident reviews to learn from security incidents and improve security posture.

Conclusion

Lua provides a powerful and flexible way to implement rate limiting in MediaWiki. By leveraging the `Scribunto` extension and `mw.storage`, you can protect your wiki from abuse and ensure its stability and security. Remember to carefully consider your specific needs and tune the limits accordingly.

Security Extension:Scribunto mw.storage User rights management Extension development reCAPTCHA Prometheus Grafana Network traffic Statistical analysis Data visualization Anomaly detection Security logs A/B testing Alerting systems

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