Abstract: A computer-implemented method is disclosed for dynamically controlling operations of computing resources in an environment using artificial intelligence. A large language model (LLM) analyzes data associated with the computing resources, each governed by a default directive controlling their functional behavior. The LLM identifies suspicious usage patterns within the analyzed data. In response to such detection, the system generates an ephemeral machine-executable directive tailored to address the specific suspicious activity. This ephemeral directive temporarily supersedes the default directive and is enforced to gate or modify the resource's function, thereby mitigating potentially harmful or unauthorized operations. The approach enables responsive, automated, and context-aware modification of system behavior, leveraging AI-based detection and just-in-time directive generation to enhance operational security and adaptability.

Abstract: A directive management system may receive a source directive from a source cloud-native application protection platform (CNAPP). The source directive defines an ephemeral condition in applying the source directive. The system may create a common intermediate representation (CIR) that includes the ephemeral condition normalized as a parameter in the CIR. The system may translate the CIR into a default machine-executable directive that is executable by a target CNAPP. The system may receive an event trigger that matches the ephemeral condition stored in the CIR. The system may create, responsive to receiving the event trigger that matches the ephemeral condition, an ephemeral machine-executable directive from the CIR. The ephemeral machine-executable directive is used to supersede the default machine-executable directive at least temporarily. The system may transmit the ephemeral machine-executable directive to the target CNAPP.

Abstract: A server computer obtains, from a client computer, technical feature data representing a technical feature associated with the client computer. The server computer determines whether the technical feature data satisfies a first criterion. If the server computer determines that the technical feature data satisfies the first criterion, the server computer sends, to the client computer, data indicating that the technical feature data satisfies the first criterion.

Abstract: Computer automated system for selected, tracking and rating workers. One embodiment of the present invention provides, to a first user, a plurality of outputs representing a plurality of questions relating to the first user's technical skill. A plurality of inputs representing a plurality of answers to the plurality of questions is received from the first user. A technical comfort score representing the first user's comfort with technology is identified based on the plurality of answers. A determination is then made whether the technical comfort score satisfies a first criterion.