Rapid7 had 14 patents in cybersecurity during Q1 2024. Rapid7 Inc has filed patents for systems and methods to implement a bounded group by query system for computing approximate time-sliced statistics, as well as techniques for associating and verifying correctness of associations between assets related to events detected in computer networks using machine learning models and locality sensitive hashing techniques. GlobalData’s report on Rapid7 gives a 360-degree view of the company including its patenting strategy. Buy the report here.

Rapid7 grant share with cybersecurity as a theme is 50% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Event monitoring service providing approximate event data querying (Patent ID: US20240104076A1)

The patent filed by Rapid7 Inc. discloses a system and method for implementing a bounded group by query system that computes approximate time-sliced statistics for groups of records in a dataset based on a group by query. The system performs a single pass scan of the dataset to accumulate exact results for a maximum number of groups in a result grouping structure (RGS) and approximate results for additional groups in an approximate result grouping structure (ARGS). These structures are accumulated by accumulator nodes and provided to an aggregator node, which combines them to generate exact or approximate statistical results for at least a subset of the groups in the dataset. This approach allows for the production of approximate results for some groups in a single pass of the dataset using size-bounded data structures, without needing to predetermine the actual number of groups in the dataset.

The method and system described in the patent involve creating a time-sliced approximate data structure (TSADS) for events in an event log repository, utilizing a counts matrix and a statistics matrix to store approximate statistics for different groups of timestamped datapoints in various time slices. The system can respond to retrieve requests for approximate statistics for a group of datapoints in the time slices by selecting cells in the count-min sketch in the counts matrix based on the group key and time slice, determining the best approximate count and statistic for the group in the time slice, and returning a time series of the best approximate statistics for each time slice. Additionally, the system can be configured to detect security incidents in the remote network based on the returned time series, generate alerts on a graphical user interface, and monitor events for incidents related to malware, phishing, or intrusion.

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