Fri 01 September 2023 Updated -

At Peakhour, we're witnessing an increase in the use of automation tools that allow for simplified interaction with web platforms. While these tools serve legitimate purposes like automating tedious tasks or testing applications, they can also be exploited for nefarious activities. One such tool is OpenBullet, a web testing suite known for its utility and flexibility. Despite its original purpose, it has become a widely-used instrument for executing web attacks such as credential stuffing. This comprehensive exploration of OpenBullet uncovers its functionality, inherent dangers, and underlying libraries that it relies on for operation, as well as strategies to detect and block it.

Overview of OpenBullet

OpenBullet is an automation suite that provides capabilities for scraping and parsing data, and automated penetration testing. It is most commonly utilised by bot developers for automated attacks, such as credential stuffing. Released under the MIT open-source license on Github, it is now in its second version, OpenBullet2, which as of March 2023, had over 1.1K stars and was forked roughly 370 times.

It is particularly favoured by individuals with limited programming knowledge due to its ease of use and third party plugins. The tool comes with different configurations which guide the actions to perform on a website, which can be easily found online.

Types of Actions with OpenBullet

The possible actions that can be performed with OpenBullet are categorised based on the framework and library used. Here are the three types of actions:

Browser Actions: Open or close tabs, maximise or minimise the browser window, and more.
Page Actions: Visit a page, fetch page attributes, set or clear cookies, click on page elements, take screenshots, and so forth.
Element Actions: Set or get element attributes, click on elements, check their status, fill in text forms, and more.

The versatility of OpenBullet has made it attractive for those who prefer to share their configurations freely. Advanced configurations for tasks like scraping and credential stuffing can be found on forums and even sold.

OpenBullet Versus Other Testing Suites

One of the key advantages of OpenBullet over other testing suites or automation frameworks is its user-friendliness. It offers a visual mode, providing a simple UI instead of lines of code. However, it does come with a high-level programming language for fine-tuning operations. Although it doesn't offer the same level of configuration as direct interaction with its underlying frameworks, it can cause significant issues for websites.

Why OpenBullet is Dangerous

OpenBullet poses a threat as its simple UI allows individuals without programming skills to create automated sequences for various web attacks. Furthermore, its integration with CAPTCHA farms makes it a formidable tool against websites using traditional CAPTCHAs for bot protection.

After installing OpenBullet, an attacker needs to create or import a configuration and manage bot behaviour. They can also configure proxies to distribute attacks, concealing their real IP addresses and sidestepping traditional rate limiting techniques.

OpenBullet also facilitates attacks like credential stuffing by offering a range of integrations. Attackers can add new credentials, store valid credentials, and set the configuration to run for any duration they desire.

We can, however, counter OpenBullet by detecting and blocking the frameworks on which it relies.

OpenBullet and Its Underlying Libraries

OpenBullet relies on several well-known bot automation libraries and frameworks:

Requests: A Python module for sending HTTP requests with forged attributes. It's highly scalable and can bypass traditional CAPTCHAs using external CAPTCHA farm services. However, it struggles against highly protected sites and mobile applications.
Selenium: This is a browser automation framework initially developed for testing web applications. It can interact with a web service like a human user, helping attackers mask their bots with human-like behaviours.
Puppeteer: This node.js library controls Chromium-based browsers. It's faster and lighter than Selenium, making it capable of running more parallel requests.

OpenBullet doesn't inherently simulate human behaviour; this must be implemented by the bot developer. Based on an analysis of online configurations, most of them don't include any fake human behaviour features. However, OpenBullet supports the execution of ad hoc JavaScript code to enable this.

Detecting and Blocking OpenBullet

To detect and block OpenBullet, understanding the origin of a request is key, especially if it's from a proxy used to distribute attacks. While OpenBullet is a potent tool in the wrong hands, it's not invincible. There are methods to identify and thwart its activities, protecting your online infrastructure from potential harm.

Identifying Unusual Patterns

Most automated tools, including OpenBullet, generate patterns of requests that differ from those of typical human users. Keeping an eye on the frequency, timing, and sequence of requests can help identify potential OpenBullet attacks. For instance, a high volume of requests coming from a single IP address, or repeated requests with different login credentials, could indicate an automated attack.

Analysing User Agents

User agents can also offer valuable clues. While OpenBullet can mimic different user agents to look like a variety of browsers, it might not simulate the wide range of user agents an actual user base would generate. If an unusual number of requests come from a small set of user agents, it might be a sign of an automated attack.

Spotting IP Address Anomalies

OpenBullet, like many automated tools, uses proxies to mask its true location and appear to be many different users. However, proxies have their own characteristics that can give them away. Data centre proxies, for instance, don't behave like residential or mobile IP addresses, and they can be flagged as suspicious. Similarly, if many different user identities come from a single IP address or if the geolocation of an IP address doesn't match the purported location of the user, it might signal the use of a proxy.

OpenBullet in the Greater Cybersecurity Context

OpenBullet is a reflection of the larger cybersecurity landscape. The simplicity and power of tools like OpenBullet show why everyone — from individual users to large corporations — needs to stay vigilant about their online security. Despite its initial creation as a web testing tool, its misuse highlights the importance of cybersecurity awareness and the need to continually upgrade defences against evolving threats.

The Need for Strong Password Practices

OpenBullet's popularity for credential stuffing attacks underscores the importance of robust password practices. Encouraging users to create unique passwords for each account and to change them regularly can help mitigate the risks posed by credential stuffing.

Implementing Advanced Bot Protection Measures

To truly secure your online spaces against tools like OpenBullet, implementing advanced bot protection measures is crucial. These measures can provide a multi-layered security strategy that operates seamlessly in the background, collecting detection signals and challenging users only when necessary. It can help stop bot attacks at the first request every time, including those perpetrated by OpenBullet's automation framework.

As the digital world continues to evolve, so too do the threats that aim to exploit it. Understanding these threats, like OpenBullet, is the first step towards a safer and more secure online experience.

Advanced Rate Limiting

One of the practical defensive measures against stuffing attacks, including those made using OpenBullet, is advanced rate limiting. Unlike basic rate limiting, which simply restricts the number of requests from a particular source within a specified time frame, advanced rate limiting provides a more nuanced and dynamic approach.

A critical feature of advanced rate limiting is its ability to group or bucket requests based on several factors beyond just the source IP address. These factors could include:

Autonomous System Number (ASN): An ASN is a unique number assigned to each network on the Internet. By grouping requests by ASN, it's possible to detect an unusual number of requests from a specific network, even if those requests are spread across many different IP addresses.
Country: Grouping requests by country allows the detection of a sudden surge of traffic from a specific geographic location, which might indicate a coordinated attack.
Device Fingerprint: A device fingerprint can be constructed from a range of attributes, including the device's operating system, browser version, and more. This allows for the detection of repeated requests coming from the same device, even if other factors like the IP address or user agent are being manipulated.
Headers: By examining the headers in HTTP requests, it's possible to detect patterns or anomalies that might signify an automated attack. For instance, a high volume of requests with identical headers could indicate the use of an automation tool.

By grouping requests on these and other factors, advanced rate limiting can provide a nuanced and dynamic defense against stuffing attacks. It allows for the detection of complex attack patterns that might otherwise go unnoticed, providing a valuable layer of security for online systems.

Fingerprinting and Behavioral Analysis

Alongside advanced rate limiting, technologies like fingerprinting and behavioral analysis add another layer of protection. By creating a unique identifier for each user based on a combination of factors (such as IP address, device information, and browser settings), and tracking that user's behavior over time, these technologies can help to distinguish genuine users from automated scripts.

These mechanisms can detect anomalies, like repetitive non-human patterns, sudden changes in behavior, or usage patterns that don't match the typical profile of a human user. This level of analysis can identify and block even sophisticated bots that are designed to mimic human behavior, thereby offering an effective defense against OpenBullet and similar tools.

The accessibility and versatility of OpenBullet have made it a popular choice for conducting web attacks. Its ability to mimic human behaviour and integrate with CAPTCHA farm services, coupled with its simple UI, allows even users with limited programming skills to execute complex attacks. Despite these challenges, detecting and blocking OpenBullet is achievable by discerning the origin of requests and understanding the nature of its operation. A combination of advanced rate limiting, fingerprinting, and behavioral analysis can provide an effective defense.

OpenBullet Automation Web Testing Cybersecurity Credential Stuffing Bot Attacks