System and method for updating a non-persistent collector deployed in a compute environment

    公开(公告)号:US12298874B2

    公开(公告)日:2025-05-13

    申请号:US18456738

    申请日:2023-08-28

    Abstract: A system and method for updating a non-persistent collector deployed in a compute environment includes scheduling a collector to collect data from a workload, performing a check to determine if a version of an executable collector application present thereon is a current version, upon determining the application version is not the current version, updating the collector version to the current version, executing the current version to collect data from the workload, and removing the collector from the workload upon completion of the operation by the collector.

    Method and Apparatus for Data Synchronization and Persistence Between Computing Devices

    公开(公告)号:US20250138923A1

    公开(公告)日:2025-05-01

    申请号:US18383791

    申请日:2023-10-25

    Abstract: A computing system includes a first computing device that executes an object-oriented software application which maintain objects, for example, in a heap data structure, in memory. The object-oriented software application includes an API to convert between objects in the memory and data in a relational database and transmit requests to perform one or more operations involving the data in the relational database corresponding to the objects in the memory. A decorator layer in communication with the API identifies the objects in the memory corresponding to the transmitted requests to perform one or more operations involving the data in the relational database. A local object storage API transfers copies of the identified objects to a local data store. A persistence API, in communication with the decorator layer and the object storage API, synchronizes the copied objects in the local data store with the data involved in the requests to perform the one or more operations with the relational database.

    SECURE CODE CLUSTERING THROUGH LLM-BASED SEMANTIC ANALYSIS

    公开(公告)号:US20250138819A1

    公开(公告)日:2025-05-01

    申请号:US18496722

    申请日:2023-10-27

    Abstract: An approach is provided that provides a plurality of source code samples to an artificial intelligence model (AIM) trained to describe source code based on performing semantic analysis on the source code. The approach produces, using the AIM, a plurality of semantic descriptions that describe the plurality of source code samples. Then, the approach converts the plurality of semantic descriptions into a plurality of semantic embeddings. In turn, the approach creates a plurality of clusters from the plurality of semantic embeddings, wherein each one of the plurality of clusters corresponds to two or more of the plurality of source code samples.

    Localization middleware
    5.
    发明授权

    公开(公告)号:US12265836B1

    公开(公告)日:2025-04-01

    申请号:US18592104

    申请日:2024-02-29

    Inventor: Vince Jones-Muth

    Abstract: A system and method of a localization middleware for localizing datasets using textual replacement techniques. The method includes receiving a request for a particular dataset that is stored in a data store, the particular dataset includes a plurality of textual strings in a non-regional version. The method includes determining a regional version for the particular dataset based on the request. The method includes identifying a library of translations associated with the non-regional version and the regional version. The method includes performing, by a processing device based on the library of translations and the particular dataset, a string replacement procedure to generate a localized dataset including one or more textual strings in the regional version.

    Hypervisor-based redirection of system calls and interrupt-based task offloading

    公开(公告)号:US12248560B2

    公开(公告)日:2025-03-11

    申请号:US17062237

    申请日:2020-10-02

    Abstract: A security agent configured to initiate a security agent component as a hypervisor for a computing device is described herein. The security agent component may change a value of a processor configuration register, such as a Model Specific Register (MSR), in order to cause system calls to be redirected to the security agent, and may set an intercept for instructions for performing read operations on the processor configuration register so that a process, thread, or component different from the processor of the computing device may receive the original value of the processor configuration register instead of an updated value of the processor configuration register. The security agent component may also be configured to generate interrupts to offload task execution from the hypervisor to a security agent executing as a kernel-level component.

    Counter Adversary Large Language Models

    公开(公告)号:US20250039234A1

    公开(公告)日:2025-01-30

    申请号:US18397820

    申请日:2023-12-27

    Abstract: A system and method of using generative AI to maintain conversations with attacking devices to discover their adversary techniques and tactics. The method includes receiving an initial message originating from an attacking device and directed to a target device. The method includes generating, using one or more classification models, a maliciousness score for the initial message indicating that the initial message is associated with one or more types of malicious activity. The method includes providing, by a processing device, the initial message to a predictive model trained to maintain conversations with attacking devices by predicting responses to malicious messages. The method includes generating, using the predictive model, two or more responses based on the initial message and at least one subsequent message, wherein each response of the two or more responses causes the attacking device to send a respective subsequent message to the predictive model.

    LARGE LANGUAGE MODEL ASSISTED CYBERSECURITY PLATFORM

    公开(公告)号:US20250036773A1

    公开(公告)日:2025-01-30

    申请号:US18425973

    申请日:2024-01-29

    Abstract: A system and method of using generative AI to convert NL queries to database commands for accessing one or more databases. The method includes receiving a natural language (NL) request for information associated with a private network. The method includes providing the NL request to an artificial intelligence (AI) model trained to identify, from a plurality of access objects associated with a plurality of databases and a plurality of event types, a particular access object that provides access to one or more event datasets associated with the NL request. The method includes generating, by a processing device and using the AI model, a database request associated with the particular access object based on the NL request.

    Nodal work assignments in cloud computing

    公开(公告)号:US12184723B1

    公开(公告)日:2024-12-31

    申请号:US18358994

    申请日:2023-07-26

    Abstract: Nodal work assignments efficiently distribute server work items, such as storing redundant copies of electronic data. A cloud computing network establishes a policy that governs how and where the redundant copies are stored cloud computing nodes (such as by region, zone, and cluster targets). The cloud computing network repeatedly or continuously re-evaluates the work assignments based on replication assignment skews and/or leadership penalties. The nodal work assignments thus minimize hardware and software operations, network traffic, and electrical energy consumption.

    INCREMENTAL SOLVES USING LLMS FOR API CALLS

    公开(公告)号:US20240427631A1

    公开(公告)日:2024-12-26

    申请号:US18475058

    申请日:2023-09-26

    Abstract: Systems and methods for incremental solves using LLMs for API calls is presented. The systems and methods produce, by a first large learning model (LLM), a processing plan based on a first prompt, wherein the processing plan includes a plurality of tasks corresponding to a plurality of services. The systems and methods send a plurality of messages corresponding to the plurality of tasks to a plurality of service agents, wherein the plurality of service agents correspond to the plurality of services and comprise a plurality of second LLMs that produce a plurality of agent responses. The systems and methods then generate a query response based on the plurality of agent responses.

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