11 Jul 2025 • 10 min read
11 Jul 2025 • 10 min read
Why do login systems across industries face waves of automated attacks attempting millions of credential combinations? One of the key tools enabling such large-scale activity is OpenBullet.
OpenBullet is an open-source web testing suite originally designed for legitimate use cases such as penetration testing, scraping, and QA automation. However, its modular design, scripting flexibility, and support for proxies and multithreading have led to its widespread abuse in the cybercrime ecosystem. Today, OpenBullet is a core component in credential stuffing, account takeover (ATO), and other forms of automated web exploitation.
Unlike traditional brute-force tools, OpenBullet enables attackers to replicate real user behavior through customizable configs, evade basic security defenses, and launch distributed attacks using large volumes of compromised credentials. Its efficiency and accessibility have made it a staple in underground forums and dark web marketplaces.
This article provides a deep dive into how OpenBullet works, how it's weaponized in real-world attacks, and what businesses can do to detect and mitigate the risks it presents.
OpenBullet is a powerful open-source automation framework primarily used for web testing and data parsing. With over 1.8K GitHub stars as of January 2025, it’s a leading tool in cybersecurity workflows. While it was initially intended for developers and penetration testers to conduct lawful QA and security assessments, OpenBullet has become widely associated with malicious automation, especially in credential stuffing and account takeover (ATO) attacks.
At its core, OpenBullet enables users to create and run custom scripts known as configs, which define how the tool should interact with a specific web application or API. These configs can replicate complex sequences of browser-like behavior, such as sending HTTP requests, handling cookies and tokens, parsing server responses, and identifying login success conditions—all without a browser.
Key components that define OpenBullet’s functionality include:
OpenBullet, launched in May 2019 by Ruri under the MIT License on GitHub, debuted as a user-friendly automation tool for penetration testers, using LoliScript and a visual editor. By December 2019, cybercriminals exploited it for credential stuffing and data scraping. The COVID-19 pandemic in 2020 saw a surge in its misuse, targeting video conferencing platforms. OpenBullet 2, released in 2020 on .NET Core 2.2+, added cross-platform support, multithreading, and Selenium integration, earning over 1.8K GitHub stars by July 2025. Despite law enforcement efforts, its active community fuels ongoing misuse, though Ruri emphasizes ethical use.
At its core, OpenBullet relies on config files—user-defined scripts that tell the tool how to interact with a specific target. These configs determine how to send HTTP requests, handle cookies, parse responses, and identify success or failure states.
Here’s how the typical process works:
OpenBullet’s powerful automation capabilities, while designed for ethical web testing, have made it a favored tool among cybercriminals for malicious activities. Below is an outline of how it is misused, based on its features and documented trends:
Credential stuffing remains one of the most common attack vectors facilitated by OpenBullet. Cybercriminals acquire massive databases of leaked usernames and passwords from previous data breaches and use OpenBullet to systematically test these combinations against login portals of targeted websites.
By leveraging configurable "configs," proxy rotation, and multithreading, OpenBullet enables attackers to automate tens of thousands of login attempts per minute. These attacks are typically silent and distributed, making them difficult to detect using traditional monitoring tools. When valid credentials are identified, the attacker gains unauthorized access to user accounts, which can then be monetized through resale, fraud, or further exploitation.
2. Account Takeover and Fraud
Once an account is successfully accessed, OpenBullet can be used to perform scripted actions within the session, such as retrieving stored payment credentials, viewing order history, redeeming loyalty points, or accessing restricted content.
In high-value sectors like e-commerce, streaming, gaming, and finance, these compromised accounts may contain sensitive data or digital assets that can be sold or abused. Attackers often automate post-login behavior through OpenBullet to extract maximum value from each compromised account, including conducting unauthorized transactions or registering malicious devices.
3. Targeted Config Creation
Configs are the foundation of OpenBullet’s automation capabilities. A config defines how to structure HTTP requests, handle authentication flows, parse server responses, and determine success conditions. Cybercriminals often develop custom configs tailored to specific websites, particularly those with valuable user accounts or weak defenses.
These configs are actively traded on underground markets, often bundled with combo lists and proxy services as part of ready-to-deploy attack kits. Skilled config creators reverse-engineer websites by analyzing JavaScript, encryption schemes, anti-CSRF mechanisms, and token lifecycles to accurately mimic legitimate user behavior and bypass defensive controls.
4. Scraping and Data Harvesting
In addition to account-based attacks, OpenBullet is frequently used for automated data extraction. When paired with valid credentials or public endpoints, the tool can systematically scrape product catalogs, pricing structures, user profiles, or even business intelligence data.
This activity is particularly damaging for platforms with proprietary data, dynamic pricing models, or intellectual property exposure. The harvested data is often resold on black markets, used for competitor monitoring, or fed into training sets for developing new bot attacks.
5. Bypassing Basic Security Controls
OpenBullet is specifically engineered to overcome standard application-layer defenses. Through customizable request headers, dynamic variables, cookie and session handling, and support for JavaScript execution, attackers can craft traffic that closely resembles legitimate user behavior.
Combined with large-scale proxy rotation, OpenBullet traffic can evade:
Many default security configurations fail to detect this type of behavior, especially if they rely solely on superficial indicators like request frequency or IP origin.
6. Scaling Attacks through Automation
OpenBullet’s design makes it ideal for horizontal scaling across multiple targets. Threat actors deploy the tool on cloud-based infrastructure or virtual private servers (VPS), allowing them to run persistent, high-throughput attack campaigns.
Attackers often integrate OpenBullet into automated pipelines that include:
These automated ecosystems enable threat actors to launch large-scale attacks continuously, often in parallel across dozens or even hundreds of services, with minimal manual oversight.
Credential stuffing attacks represent a major threat to online security. Attackers use automated tools to test large numbers of stolen username and password pairs across multiple websites. Unlike brute force attacks, which guess passwords, credential stuffing relies on credentials obtained from previous data breaches. Attackers exploit the fact that many people reuse passwords for different accounts.
OpenBullet plays a central role in enabling credential stuffing. The tool provides a visual interface for launching credential stuffing campaigns. Attackers load configuration files that define request logic, success conditions, and parsing rules. Built-in proxy rotation and retry logic help attackers avoid detection. Plugins for CAPTCHA solving and fingerprint spoofing make these attacks even more effective. Attackers often download shared configs from forums or Telegram channels, allowing them to target specific sites with minimal effort.
The 'Anatomy of Account Takeovers' report highlights how credential stuffing attacks are predominantly automated using bad bots and tools like OpenBullet. Attackers use configuration files to generate sequenced API calls and browser automation, often leveraging proxies and synthetic identities. This ecosystem allows attackers to evade detection and cash out stolen credentials, fueling a surge in account takeover attacks.
OpenBullet’s misuse by cybercriminals poses significant threats across various industries, exploiting vulnerabilities to achieve financial gain, data theft, or unauthorized access. Below is an overview of its impact on key sectors.
OpenBullet has become a preferred tool among cybercriminals not by chance, but due to a combination of technical advantages and ecosystem support that align perfectly with the needs of automated attacks. Key reasons include:
Spot Suspicious Traffic Patterns: OpenBullet’s automated attacks, like credential stuffing, produce distinct request patterns unlike human behavior. Monitor for rapid login attempts, repeated credential tries from one IP, or unusual request sequences. Tools like SIEM systems (e.g., Splunk) can flag these anomalies in real-time, enabling quick action to block OpenBullet’s high-volume requests.
Signature- and Fingerprint-Based Detection: OpenBullet leverages automation frameworks like Requests, Selenium, and Puppeteer to execute attacks such as credential stuffing. Requests enable simple HTTP requests with forged headers, often paired with CAPTCHA-solving services, but struggle against robust defenses. Selenium mimics user actions like form filling, masking bots as human users, while Puppeteer, a lightweight Node.js library, supports faster parallel requests on Chromium browsers. By detecting these frameworks’ signatures (e.g., specific headers, request patterns, or JavaScript execution), to stop attacks at their source.
Implement Multi-Factor Authentication (MFA): Implementing Multi-Factor Authentication (MFA) is one of the most effective defenses against OpenBullet attacks, particularly those involving credential stuffing. By requiring users to verify their identity through two or more distinct factors—such as a password (something they know), a device or token (something they have), or a biometric scan (something they are)—MFA ensures that stolen or reused credentials alone are not enough to gain access. This additional layer of security effectively blocks automated login attempts, raises the difficulty for attackers, and significantly reduces the risk of account takeovers, even when valid credentials are exposed.
Behavioral Detection: OpenBullet’s default configurations rarely mimic human behavior, though advanced users can add JavaScript to simulate actions. Behavioral analysis counters this by monitoring client-side signals (e.g., mouse movements, typing speed) via JavaScript or mobile SDKs, and server-side signals like request frequency, URL navigation patterns, or IP/user-agent changes. Suspicious patterns, such as rapid requests or multiple accounts from one IP, expose OpenBullet’s automation. Tools like GeeTest analyze these signals to detect and block bots effectively.
Though OpenBullet itself doesn’t provide sophisticated evasion features, it serves as a gateway for widespread abuse on underprotected platforms. Its modularity, ease of configuration, and open-source nature have helped it gain traction within criminal forums and botnet operations. Meanwhile, more advanced attackers continue to rely on the raw frameworks beneath OpenBullet to craft fully custom, evasive bots.
As attackers continue to evolve, so must your defenses. Understanding how OpenBullet works is the first step; deploying smarter, behavior-driven protection is the one that truly counts.
For more info about how GeeTest stops advanced bots like OpenBullet before they reach your website, app, or API, start a free trial or book a personalized demo today.
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