Rapid7 had 21 patents in cybersecurity during Q4 2023. Rapid7 Inc filed patents in Q4 2023 for systems and methods to mitigate credential leakage in a computer network using machine learning algorithms, authenticating leaked credentials, and replacing them. Another patent focuses on detecting anomalous network activity in a cloud-based compute environment by creating profiles for virtual entities and identifying anomalies. Additionally, a patent was filed for a system and method to locate documents on a computer network based on document properties using search engines and rule-based actions. GlobalData’s report on Rapid7 gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

Rapid7 grant share with cybersecurity as a theme is 85% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Techniques for mitigating leakage of user credentials (Patent ID: US20230421547A1)

The patent filed by Rapid7 Inc. describes systems and methods for mitigating the leakage of user credentials in a computer network. The process involves monitoring external data sources, scraping data, applying machine learning algorithms, specifically neural networks, to identify potential leaked credentials, authenticating these credentials using a database of valid credentials, and replacing any leaked credentials that are identified. The method also includes training neural networks on a predetermined set of credentials to identify credentials in unstructured text, checking if leaked credentials correspond to predetermined domain names, issuing alerts to users, and filtering out irrelevant credentials.

The system described in the patent includes a non-transitory memory storing computer-executable instructions and a processor that communicates with external data sources to monitor and scrape data, identify potential leaked credentials, authenticate them using a database of valid credentials, and replace any leaked credentials. The system is also capable of training neural networks to identify credentials in unstructured text, checking for correspondence with predetermined domain names, issuing alerts to users, removing leaked credentials from data sources, and filtering out irrelevant credentials. Overall, the patent outlines a comprehensive approach to detecting and mitigating the leakage of user credentials in a computer network using advanced technologies like machine learning and neural networks.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.