원래 이름 기록: Salesforce, Inc.

Techniques may generate realistic synthetic data by programmatically generating a configuration file object type and relationship data. This configuration file may be used to retrieve source data matching the object type(s) and/or specific records indicated by the configuration file. The techniques may detect and anonymize private/proprietary information and may determine statistical characteristic(s) of the source data. A batch of prompt(s) may be generated using the source data, the statistical characteristic(s), and the configuration file and may be transmitted to one or more instances of a transformer-based machine-learned model. Sets of synthetic data received from the model instance(s) may be de-duplicated, checked for similarity to the source data (e.g., via embedding the synthetic data and the source data), and may be used to generate synthetic object(s) using the relationship(s) and/or other data indicated by the configuration file. These synthetic object(s) may then be deployed in a software environment.

Methods, systems, apparatuses, and computer program products are described. A data processing system may ingest asset service action history data from data sources of different data organization models via clicks from a user, generate at least an asset service action training data set from the ingested data, and train an asset management model to predict future asset service actions using the asset service action training data set. The different data organization models may include data objects including cases, work orders, asset identifiers, and products. The data processing system may transform the ingested asset history into the asset service action training data set according to a configurable unified data model. The future asset service action predictions may be based on a binary classification system, and may indicate a likelihood of performing a second asset service action type on an asset type based on an inputted first asset service action type.

Apparatus and method for predictive protection of cloud-based applications and services. For example, a web application firewall (WAF) detects vulnerabilities in the data traffic and collects relevant information including, for example, the payload type, structure, and specific vulnerability information. For certain vulnerabilities associated with views, the view document object model (DOM) and history of views may be collected. For vulnerabilities related to API calls, the corresponding the API path and history of API calls may be retrieved. The WAF includes a signature controller which decodes the payload (e.g., the JavaScript Object Notation (JSON) structure) and creates a signature of the vulnerability based on the relevant information including, but not limited to, the API path, the web application domain, and/or the URL path. The WAF distributes collected and generated vulnerability information to web browser extensions of the web application which perform mitigations such as generating notifications when a vulnerability is encountered.

A computer services environment may include web servers providing access domains and a network ingress paths receiving application-layer request messages. The application-layer request messages may each be received from a respective source via a respective ingress path and may be directed to a domain. The computing services environment may also include an orchestration engine configured to determine and implement mitigation policies corresponding with the ingress paths based on a classification of a subset of the plurality of application-layer request messages as being sent from a subset of the sources associated with a distributed denial of service attack. The mitigation policies may include rules to prevent a subset of subsequent application-layer request messages from the subset of the sources from reaching one or more components of the computing services environment.

A computing services environment may provide computing services to a plurality of recipients via the Internet. The computing services environment may include application gateways receiving application-layer request messages from various sources. The computing services environment may also include an orchestration engine determining mitigation policies corresponding with the application gateways based on a classification of a subset of the application-layer request messages as being sent from sources associated with a distributed denial of service attack. The computing services environment may also include application-layer web application firewalls corresponding to the application gateways and being configured to transition from a deactivated state to an activated state upon receipt of an instruction from the orchestration engine. The activated application-layer web application firewalls may implement the mitigation policies prevent a subset of subsequent application-layer request messages from the subset of the sources from reaching one or more components of the computing services environment.

A computing services environment may include application gateways receiving application-layer request messages from various sources. The computing services environment may also include an autonomous agent platform configured to instantiate and execute an autonomous agent to evaluate network traffic associated with a portion of the computing services environment. The computing services environment may also include an orchestration engine configured to determine one or more mitigation policies corresponding with one or more of the application gateways based on identification of the application-layer distributed denial of service attack by the autonomous agent. The computing services environment may also include application-layer web application firewalls corresponding to the plurality of application gateways and implementing the one or more mitigation policies to prevent a subset of subsequent application-layer request messages from the subset of the sources from reaching one or more components of the computing services environment.

A computing services environment may include application gateways receiving application-layer request messages from a plurality of sources. The computing services environment may also include an orchestration engine configured to identify an application-layer distributed denial of service attack based on input data characterizing network traffic received at the application gateways and to determine a mitigation plan update to address the application-layer distributed denial of service attack. The computing services environment may also include an autonomous AI agent platform configured to instantiate and execute an autonomous AI agent instance configured to determine whether to approve or reject the mitigation plan update by evaluating the mitigation plan update via a generative language model. The computing services environment may also include application-layer web application firewalls corresponding to application gateways. The orchestration engine may instruct the application-layer web application firewalls to implement the mitigation plan update upon approval by the autonomous AI agent instance.