Rapid7 had 11 patents in artificial intelligence 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, detect anomalous network activity in a cloud-based compute environment, and obtain the location of a document on a computer network based on a document property. These innovations aim to enhance security and efficiency in network operations. 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 artificial intelligence as a theme is 72% 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 found. 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 also includes features such as 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. This system aims to provide a comprehensive solution for detecting and mitigating the leakage of user credentials in a computer network, utilizing machine learning algorithms and neural networks for efficient and accurate identification of potential leaks.

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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.