Abstract: An application server may receive user input indicating a plurality of provisioning parameters for provisioning resources on a cloud substrate. The application server may transmit, to a first artificial intelligence (AI) model, the plurality of provisioning parameters and a request to generate, based on the plurality of provisioning parameters, provisioning code associated with the cloud substrate. The application server may transmit, to one or more second AI models, the provisioning code generated by the first AI model, the plurality of provisioning parameters, and a request to analyze the provisioning code based on the plurality of provisioning parameters. The application server may update respective reputation values associated with the first AI model and the one or more second AI models based on one or more analysis results associated with output of the one or more second AI models.

Abstract: A device may include a communication interface configured to receive a plurality of application-layer request messages directed to a domain accessible via the computing services environment. A device may include a fingerprint database storing a plurality of predetermined filter fingerprint values. A device may include a fingerprint engine configured to determine fingerprint information based on an application-layer request message of the plurality of application-layer request messages, the fingerprint information including a locality-based fingerprint determined based on a locality-sensitive hashing function that maps similar input values to similar output values, the fingerprint information including a entropy-based fingerprint sensitive to an amount of information stored in data.

Abstract: A device may determine a plurality of training data observations corresponding to a plurality of application-layer request messages received at the computing system, the plurality of training data observations including a plurality of fingerprint values determined based on content associated with the plurality of application-layer request messages, a first subset of the plurality of application-layer request messages being classified as malicious, a second subset of the plurality of application-layer request messages being classified as legitimate. A device may determine a classical support vector machine based on a quantum kernel, the quantum kernel being determined based on a quantum feature map and a plurality of quantum states, the quantum feature map embedding the plurality of fingerprint values into a quantum space corresponding to the quantum states. A device may determine a fingerprint value for an application-layer request message received at an application gateway within the computing system.

Abstract: Application servers may provide computing services to entities. A network ingress may receive application-level request messages and forward some or all of the request messages to an application server. A data aggregator may determine data buckets based on the application-level request messages. A data bucket may include information characterizing one or more features. The information may be determined based on a subset of the application-level request messages received during a respective period of time. A request analyzer may determine one or more of the data buckets and one or more of the features for analyzing an application-level request message and may determine a synthetic indicator for the request based on the one or more data buckets and the one or more features. A web application firewall may block the application-level request message upon determining that the synthetic indicator indicates that the request is illegitimate.

Abstract: 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.

Abstract: 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.

Abstract: A system may receive a natural language description of a desired output to be generated by one or more artificial intelligence (AI) models. The system may generate, using at least one of the AI models and based on the natural language description, multiple generation plans, each containing a first set of instructions for generating the desired output. The system may rank these generation plans using at least one of the AI models to select a potential generation plan. The system may generate, using at least one of the AI models and following the instructions in the selected plan, multiple outputs. The system may rank these outputs using at least one of the AI models to select a potential output. The system may validate the selected output based on validation parameters associated with the desired output.

Abstract: An application server may receive user input indicating a plurality of provisioning parameters for provisioning resources on a cloud substrate. The application server may transmit, to a first artificial intelligence (AI) model, the plurality of provisioning parameters and a request to generate, based on the plurality of provisioning parameters, provisioning code associated with the cloud substrate. The application server may transmit, to one or more second AI models, the provisioning code generated by the first AI model, the plurality of provisioning parameters, and a request to analyze the provisioning code based on the plurality of provisioning parameters. The application server may update respective reputation values associated with the first AI model and the one or more second AI models based on one or more analysis results associated with output of the one or more second AI models.