Red Hat Patente

A system and method of an anomaly detection and correction system for benevolent adversarial attacks. The method includes receiving a request to provide an input dataset to a machine learning (ML) model, trained using a training data distribution, to generate predictions based on input data. The method includes calculating, based on model traits of the model and the input dataset, an anomaly score indicating an accuracy of the model associated with generating a prediction output. The method includes adjusting, by a processing device based on the anomaly score, the input dataset to generate a modified input dataset. The method includes increasing a likelihood of an accurate prediction by the ML model when generating a prediction output by providing the modified input dataset to the model instead of the input dataset.

A quantum computing system receives a first qubit reservation request from a first quantum service, the first qubit reservation request identifying a first quantity of qubits. A first set of qubits equal in number to the first quantity of qubits is determined based on a qubit data structure that identifies a first plurality of qubits. The qubit data structure is altered to reserve the first set of qubits for the first quantum service. Qubit reservation information that identifies the first set of qubits is sent to the first quantum service.

A service executing on a first quantum computing system (QCS) receives an indication that a process executing on the first QCS desires to communicate with a second QCS. The service accesses QCS type information that identifies the second QCS as a first QCS type of a plurality of different QCS types. The service initiates a first external QCS agent on the first QCS that is operable to communicate with the second QCS based on a first QCS configuration of a plurality of QCS configurations, the first QCS configuration corresponding to the first QCS type.

A virtual machine including a security module is initialized, wherein the virtual machine utilizes a boot process configuration that is to be utilized by a computing device. The computing device accesses a configuration value derived by the security module within the virtual machine. The configuration value is associated with a decryption key that is operable to decrypt data stored on a storage device. A boot process action of the computing device is implemented based on the configuration value.

A computing system obtains a set of instructions configured to execute on a classical computing system. The set of instructions are evaluated to identify a cryptographic algorithm having a cryptographic algorithm type implemented by the set of instructions. Based on the cryptographic algorithm type, a candidate quantum algorithm comprising quantum instructions operable to attempt to breach the cryptographic algorithm is selected from a plurality of quantum algorithms. The set of instructions are translated into cryptographic quantum instructions that implement the cryptographic algorithm. Based on the cryptographic quantum instructions and the quantum instructions, a quantum instruction file is generated that, when executed, attempts to breach the cryptographic algorithm.

A method, a system, and a non-transitory computer-readable medium are provided. The method includes receiving a data object at a node of a datagrid system. The method includes generating a first association between the data object and a key that identifies the node in the datagrid system. The method includes storing the first association in a first cache of the node. The method includes converting the data object to an embedding object. The method includes generating a second association between the embedding object and the key. The method includes storing the second association in a second cache of the node.

A quantum system can obtain a quantum instruction set. The quantum system can classify a quantum algorithm type of the quantum instruction set. The quantum system can evaluate an optimization factor of the quantum instruction set based on the quantum algorithm type. The quantum system can rank a plurality of candidate quantum computing systems based on the optimization factor and metadata associated with the plurality of candidate quantum computing systems. The metadata can be descriptive of performance characteristics of the plurality of candidate quantum computing systems respective to the optimization factor. The quantum system can schedule the quantum instruction set on a selected quantum computing system of the plurality of candidate quantum computing systems based on ranking the plurality of candidate quantum computing systems.

This disclosure provides devices, systems, methods, and techniques for booting up an operating system with an initial scalable filesystem. An example method includes loading, from a non-transitory and non-volatile memory, a bootloader into a random access memory (RAM). The method includes loading, by the bootloader, a kernel into the RAM. The method includes initializing, by the kernel, an initial filesystem to load storage drivers relevant to the hardware resources for starting essential storage components. The method includes, when the initial filesystem is initialized, mounting, by a processing device, an overlay filesystem onto the initial filesystem of the RAM. The method further includes transitioning, upon completion of system initialization tasks in the overlay filesystem, from the overlay filesystem to a target root filesystem.

A Custom Resource (CR) is generated within a code repository of a legacy application based on intercepted Application Programming Interface (API) calls to an imperative API of the legacy application. The intercepted API calls relate to a particular type of entity. The CR is defined by a Custom Resource Definition (CRD) associated with the particular type of entity. The CR is one of a plurality of CRs of the code repository that collectively define a correct state of the legacy application. Responsive to a difference between a current state of the legacy application and the correct state of the legacy application, an automated operator makes an imperative API call to the imperative API of the legacy application that modifies the current state of the legacy application to match the correct state of the legacy application.

An authority-based training process for a large language model is provided. The process can involve generating corresponding sets of data quality metrics for each sample in a training dataset. The training dataset can encompass a group of topics. The process can also involve generating a corresponding set of authority scores for each sample based on the corresponding sets of data quality metrics. Each authority score can indicate a respective authority level of the sample in relation to a particular topic of the group of topics. The process can further involve training the large language model using a loss function that includes a set of weights. During training, the set of weights can be dynamically adjusted based on the corresponding set of authority scores for each sample in the training dataset. This can produce a large language model that is more accurate than may otherwise be possible.

Aspects of the present disclosure relate to optional volume associations to prevent pod failure. More specifically, a method of the present disclosure includes identifying, within a specification file, a reference to a first volume from a set of volumes or to a file associated with the first volume from the set of volumes. The method includes determining a subset of volumes from the set of volumes for execution of a workload within a pod, where the subset of volumes includes at least the first volume. The method includes determining, by a processing device, whether to boot the pod based at least on a viability of the first volume.

Aspects of the present disclosure relate to hypervisor upgrades for real-time virtual machines. More specifically, a method of the present disclosure includes initiating, at a computing device, a second instance of a management user space component of a hypervisor associated with a virtual machine, wherein a virtual processor associated with the virtual machine is operating in association with a first instance of the management user space component. The method includes initiating a migration of a state of the first instance of the management user space component to the second instance of the management user space component. The method includes attaching the second instance of the management user space component to a kernel component, wherein a state of the virtual processor is maintained by the kernel component.

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A virtual machine (VM)-based container runtime executing on a computing device receives a request to run a container from a container image that is at least partially encrypted. The VM-based container runtime causes a VM to be initiated from a VM image, the VM image including an agent operable to, during execution, obtain a plurality of decryption keys operable to decrypt blocks of the container image. The agent is operable to set up a block remapper in the VM to be invoked by a file system mounted to the VM to request a particular container image block, send a request for the particular container image block to a block obtainer component executing outside of the VM, utilize a decryption key to decrypt a container image block received from the block obtainer component to generate a decrypted container image block, and pass the decrypted container image block to the file system.

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Ransomware activity in operating systems can be mitigated by monitoring from user space. For example, a computing environment can generate an affinity score indicating a likelihood of ransomware activity associated with an operating system based on a first set of system calls detected from a user space of the operating system within a first time window. The computing environment can buffer one or more write operations from the first set of system calls during a second time window based on the affinity score. The computing environment can update the affinity score based on a second set of system calls detected from the user space of the operating system within the second time window. The computing environment can block execution of the one or more write operations based on the updated affinity score exceeding a predefined threshold.

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A device attachment request to attach a device to a container within a virtual machine is received. The virtual machine is monitored to determine whether the virtual machine is ready for a hot-plug of the device. An indication that the virtual machine is ready for the hot-plug of the device is received from the virtual machine. A device hot-plug operation is issued to cause the device to be hot-plugged to the virtual machine.

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A kernel monitor can be used to mitigate ransomware activity of a host system. In some aspects, a computing system can use the kernel monitor to monitor a set of system calls generated by the host system within a time window to perform a functionality. The kernel monitor can include a respective kernel program monitoring each system call in the set of system calls. The set of system calls can be filtered by the kernel monitor to identify a subset of system calls associated with encrypting a filesystem of the host system. The computing system can determine that the subset of system calls is indicative of ransomware activity associated with the host system based on the subset of system calls exceeding a predefined threshold. Subsequently, the computing system can perform a mitigation operation to mitigate the ransomware activity.

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