757 results about "Executable" patented technology

The invention discloses a chip verification method and device, equipment, a storage medium and a program product. The method comprises the steps that a first executable file of a C model is obtained, the first executable file comprises an original code and a target code which are designed based on a verified function in a chip, and the verified function comprises a plurality of algorithm steps; running the first executable file based on the input signal to obtain running data of each algorithm step; extracting simulation data of each algorithm step from the simulation waveform file with the verified function; and respectively comparing the operation data and the simulation data of each algorithm step to determine an abnormal algorithm step in which the operation data and the simulation data are inconsistent. Therefore, by automatically comparing the operation data and the simulation data of each algorithm step, the abnormal algorithm step with the problem can be quickly determined, and the manual inspection and analysis time is shortened.

The invention discloses a Direct3D deep cutting behavior compatible method based on an atomization shader, which comprises the following steps: establishing a scene combination metadata table in a DXVK compiling stage, constructing a shader template library containing atomization components and variants, and generating an executable file of the DXVK; after the DXVK is started, deep processing API calling of the D3D application is intercepted, parameters are extracted to generate an atomization parameter set, and scene combination metadata are matched or newly added in a scene combination metadata table to obtain a recommendation strategy and shader component combination; a conversion mode is adaptively selected according to scene metadata to calculate a Vulkan depth value, and a depth comparison operation is adapted to generate a Vulkan depth conversion parameter; the DXVK maps the parameters into DRM depth control parameters irrelevant to hardware and transmits the DRM depth control parameters to a kernel, the DRM packages the DRM depth control parameters and converts the DRM depth control parameters into hardware instructions matched with the GPU, the DXVK loads a shader template and binds the parameters, original logic is spliced to generate a Vulkan shader module, a Vulkan command stream containing the hardware instructions is generated and submitted to the GPU after a pipeline is bound, and finally the GPU executes the Vulkan command stream to obtain a depth rendering result conforming to D3D native logic.

A system and method for data compaction with adaptive codebook statistical estimates. Training data sets determine sourceblock frequencies while a dynamic mismatch probability system continuously refines estimates based on observed patterns. Context-aware handling selects appropriate secondary encoding methods for different data types (text, binary, image, executable). Machine learning models predict optimal mismatch probabilities from extracted features. Edge-optimized training enables codebook development on resource-constrained devices with intelligent resource management. Differential updates transmit only changes between codebook versions, minimizing bandwidth usage. Federated learning enables multiple devices to contribute to shared codebooks while maintaining data privacy. A secure synchronization protocol with authentication and verification ensures codebook consistency. The distributed maintenance method provides systematic validation, conflict resolution, and optimization across device networks, enabling efficient encoding across heterogeneous systems.

The invention discloses a lightweight cross-platform PLC (Programmable Logic Controller) multi-language code generation method, which relates to the field of industrial process control, and firstly provides a unified intermediate data model, and on the basis, a module for converting each PLC language into the unified intermediate data model is realized; on the basis of a standardized JSON data structure, a modularized unified intermediate language conversion chain is further supported, an analyzer and a generator communicate through a JSON interface, a cross-platform conversion path is supported, and unified intermediate language conversion from PLC to JSON to XML to ST to C is completed; the method comprises the following steps of: integrating an open source compiler and runtime, constructing an open and pluggable automatic execution framework, compiling a generated C code into a platform executable file by using an adaptive GCC tool chain aiming at different target platforms, and deploying a program generated by compiling to a soft PLC runtime system supporting multiple platforms. According to the method, a JSON intermediate data structure which is light in weight, unrelated to languages and uniform in structure and a matched conversion framework of the JSON intermediate data structure are constructed.

The invention provides a method and a system for exporting Allegro file packages in batches based on Python. The method comprises the following steps: configuring an Allegro executable file path and a pre-recorded Skill script path; selecting a target export directory through a graphical interface, and updating export path parameters in the Skill script; selecting Allegro PCB files to be processed in batches through a graphical interface; verifying the file list and the export path, and starting batch processing after confirmation; traversing the file list, and executing the following steps on each Allegro PCB file to be processed: calling an Allegro command line tool, and opening the PCB file in a batch processing mode; automatically loading a pre-recorded Skill script to execute a packaging and exporting operation; and capturing and feeding back a command line execution state. The efficiency can be improved, multi-file batch automatic processing is supported, and manual operation is reduced; human errors are avoided through automatic path configuration and an exception capture mechanism; the interaction is friendly, and the operation threshold is reduced while the operation steps are simplified.

This invention discloses a full lifecycle management system and method for scientific computing programs. The system includes a build environment subsystem and a production environment subsystem. The former provides computer resources for the build process of the scientific computing program throughout its lifecycle, while the latter provides computer resources for the testing and deployment processes. This invention, through a full lifecycle management method for scientific computing programs, operates on corresponding computing resources, encompassing a series of steps including querying, triggering scheduling, build execution, result distribution, and test deployment. It automatically generates the executable file of the scientific computing program and configures its runtime dependencies. Simultaneously, it automatically generates a corresponding description file recording the entire lifecycle process. Furthermore, based on version management of these description files and their sets, it achieves full lifecycle traceability and cross-platform migration and deployment of scientific computing programs in a high-performance computing environment.

The invention discloses a reconfigurable AI chip-oriented neural network reasoning deployment method, which comprises the following steps of: exporting a trained model into an ONNX format by using an ONNX library corresponding to a deep learning framework, and analyzing the ONNX format model to obtain a network topology structure, operator information and general control information; dividing each operator according to the operator information to obtain a division result; assembling and splicing operator division results in combination with a network topology structure to obtain task information, and the like. Hardware resources of the reconfigurable AI chip are fully utilized. And finally, organizing general control information and task information of all operators into a final executable file, and efficiently completing reasoning deployment of the neural network model on the reconfigurable AI chip. According to the method and the device, the technical problems of high development threshold and low efficiency of the existing specific AI chip architecture compiler can be solved, and the technical problem that the existing automatic code generation method possibly cannot fully utilize the chip performance can be solved.

An automated system attempts to characterize code as safe or unsafe. For intermediate code samples not placed with sufficient confidence in either category, human-readable analysis is automatically generated to assist a human reviewer in reaching a final disposition. For example, a random forest over human-interpretable features may be created and used to identify suspicious features in a manner that is understandable to, and actionable by, a human reviewer. Similarly, a k-nearest neighbor algorithm may be used to identify similar samples of known safe and unsafe code based on a model for, e.g., a file path, a URL, an executable, and so forth. Similar code may then be displayed (with other information) to a user for evaluation in a user interface. This comparative information can improve the speed and accuracy of human interventions by providing richer context for human review of potential threats.

The invention provides a VTCU controller task allocation method and device based on AUTOSAR and electronic equipment, and the method comprises the steps: dividing an application layer into a plurality of software components according to the functional characteristics of the application layer, and generating an application layer code; importing the application layer code into a configuration tool of the runtime environment to configure related modules of the runtime environment, and generating a runtime environment code; according to the functional characteristics of the running entity of each software component, a periodic task and related modules of the periodic task are configured through a configuration tool of a real-time automobile operating system, and a real-time automobile operating system code is generated; integrating an application layer code, a runtime environment code and a real-time automobile operating system code into a Tasking project, and generating an executable file; and downloading the executable file into a whole vehicle and a gearbox controller through the UDE, and running the executable file. According to the scheme, the load rate of the CPU is effectively reduced, and the running efficiency of the VTCU controller software driving program is improved.

Apparatuses, systems, and techniques to detect potential security risks using application program interface (API) scanners. In at least one embodiment, software is scanned to identify one or more APIs of different categories and the position of the APIs and associated code in an executable file may be altered to reduce one or more potential risks.

The invention provides a file uploading method and a file processing system, and relates to the technical field of data transmission. The method comprises the steps that front-end equipment obtains a to-be-uploaded resource file input by a user, a target distribution package is called based on a preset interface, the target distribution package comprises a portable compiling file, and the portable compiling file is an executable file obtained by compiling and packaging a target logic code; the portable compiling file is used for generating a hash value, the target logic code is compiled based on a target programming language, the front-end equipment runs the target distribution packet to obtain the hash value of the resource file, and the front-end equipment uploads the resource file to a file server according to the hash value of the resource file. According to the method, the portable compiling file written based on the target programming language is introduced, a traditional Hash calculation mode is replaced by original compiling code execution with better performance, the Hash value generation efficiency of the large-size resource file is remarkably improved, and then the file uploading efficiency is improved.

A system connects a 5G telecommunications network to a smart device equipped with a camera. The smart device uses a discriminative model to create a textual description of the scene describing recognized objects and locally converts the textual description to textual data. The system receives the textual data from the smart device over the 5G network. After receiving the file, the system causes the smart device to delete the video. The system inputs the textual data into a remotely located large language model (LLM) and analyzes the textual data based on the textual description of the scene. The system generates a proposed workflow as an executable file based on the LLM's analysis, where the proposed workflow corresponds to commands for the smart device. The system transfers the executable file over the 5G network to the smart device and causes the smart device to execute the executable file.

DLL hooks are protected by mapping the starting address of the new executable to a sample of the former executable. Attempts to read the starting address are responded to with the sample of the former executable. Attempts to write to the starting address are responded to with confirmation of success without actually writing data. Debuggers are detected upon launch or by evaluating an operating system. A component executing in the kernel denies debugging privileges to prevent inspection and modification of DLL hooks.

An automated system attempts to characterize code as safe or unsafe. For intermediate code samples not placed with sufficient confidence in either category, human-readable analysis is automatically generated to assist a human reviewer in reaching a final disposition. For example, a random forest over human-interpretable features may be created and used to identify suspicious features in a manner that is understandable to, and actionable by, a human reviewer. Similarly, a k-nearest neighbor algorithm may be used to identify similar samples of known safe and unsafe code based on a model for, e.g., a file path, a URL, an executable, and so forth. Similar code may then be displayed (with other information) to a user for evaluation in a user interface. This comparative information can improve the speed and accuracy of human interventions by providing richer context for human review of potential threats.

The invention provides a method and a device for verifying and debugging a chip algorithm module. The consistency of a C language reference model and a simulation waveform can be automatically compared and tracked. The method comprises the following steps: constructing a verification environment and generating an fsdb waveform and a C language reference model executable file with debugging information; generating a GDB command and an fsdbreport command based on the configuration information, extracting a variable value and a signal value, and performing consistency comparison; if the comparison is consistent, ending, otherwise, entering signal tracking; in signal tracking, a PyNPI interface is called to forward track a driving signal and analyze a signal value matching condition in a clock period; and if the corresponding value is not matched, generating a new configuration file and circularly executing the debugging process. According to the technical scheme provided by the invention, the root of the problem can be automatically tracked and quickly positioned at the initial verification stage of the algorithm module, the dynamic addition of comparison nodes is supported, and the manual debugging cost is reduced.

In some embodiments, a computer-implemented method for preventing credential passing attacks may include receiving an input; determining whether the input is a credential access command, wherein the determination includes searching for occurrences of references to executables related to adding, reading, copying, or performing actions with respect to a credential, if the input is determined to be a credential access command, performing anomaly detection, wherein performing the anomaly detection includes evaluating whether a user is a valid domain user, whether an elapsed time of the credential is greater than a maximum lifetime of the credential, and whether a privilege attribute certificate of the credential is valid, determining that an anomaly exists if the command was generated by an invalid domain user; an elapsed time of a credential is greater than a maximum lifetime, or the privilege attribute certificate of the credential is invalid, and performing mitigation of the anomaly.

Aspects of the present disclosure relate to threat detection of executable files. A plurality of static data points may be extracted from an executable file without decrypting or unpacking the executable file. The executable file may then be analyzed without decrypting or unpacking the executable file. Analysis of the executable file may comprise applying a classifier to the plurality of extracted static data points. The classifier may be trained from data comprising known malicious executable files, known benign executable files and known unwanted executable files. Based upon analysis of the executable file, a determination can be made as to whether the executable file is harmful.

The invention discloses an instruction stream feature recognition-based instruction conversion memory access conflict optimization method, which comprises the following steps of: in a process of pre-executing an executable file in an ARM (Advanced RISC Machines) many-core system in a dynamic instruction conversion manner, determining shared memories among processes by adopting instruction stream analysis to form a first shared memory list, and on the basis, determining the memory access conflict among the processes; the executable file is loaded and executed again, the memory access type to-be-converted instruction with the memory address located in the first shared memory list is converted into an instruction sequence composed of a locking instruction sequence, a second ARM instruction sequence and an unlocking instruction sequence, and meanwhile conversion execution of the executable file is completed based on a cache consistency protocol. The memory access conflict of the x86 program on the ARM many-core system is obviously reduced, and powerful support is provided for realizing high-performance dynamic instruction conversion.

A cyber threat information processing method including generating stack trace information of a reader program of an operating system executing a non-executable file at a hooking point of a system call of the operating system when the reader program performs the system call, obtaining a calling function for calling the system call and a variable corresponding to the calling function from the generated stack trace information, and providing description information about the obtained calling function and the variable corresponding to the calling function.

A method for fuzzing constituted of: continuously generating units of data; inputting each of the generated units of data into a tested device; and adding each of one or more hooks to a respective one of one or more predetermined points of interest in a binary executable file running on the tested device, wherein responsive to the input units of data, each hook outputs information associated with the respective point of interest, the output information comprising data stored in a respective address of a memory associated with the respective point of interest, wherein the generation of the units of data is responsive to the output information associated with the respective points of interest.

The invention discloses an executable file burning method, an executable file running method, an executable file burning device, executable file running equipment and a medium, and relates to the technical field of computers. Burning a second executable file in the compiled executable file to a Flash memory based on an on-chip execution mode; wherein the first executable file is configured with a target jump address, and the target jump address is a storage head address corresponding to a second executable file in the Flash memory, so that in the process of running the compiled executable file by the preset embedded processor, when the preset embedded processor runs to a code line where the target jump address in the first executable file is located, the target jump address in the first executable file is located; and skipping from the block random access memory to the Flash memory to read and run the second executable file. According to the application, the Flash memory and the block random access memory are used for jointly storing the compiled executable file, so that the running memory space is expanded.

The invention provides a method for verifying cache consistency of a multi-core processor, electronic equipment and a storage medium, and the method comprises the steps: generating a model compiled by a target language according to an obtained first conversion rule between any two states of a cache line of the multi-core processor, analyzing the model, and verifying the cache consistency of the multi-core processor; therefore, at least one path of state transition of the cache line is obtained. By generating the excitation corresponding to the at least one path, the excitation is compiled into an executable file, so that the cache consistency of the multi-core processor is verified by running the executable file. Therefore, the generated model written by the target language can automatically generate the incentives for verifying the cache consistency, so that more incentives can be generated, more test scenes can be covered as much as possible, and the cache consistency verification of the multi-core processor is more comprehensive.

Systems and methods are provided for providing a vulnerability applicability module, wherein a context detector, a context detection output interpreter module and / or an executable may be included in a catalog of known vulnerabilities. An IHS remote access controller may detect publication of a catalog of known vulnerabilities and execute the context detector, the context detection output interpreter module and / or the executable included in the catalog. This causes the remote controller to identify configurations for one or more of the plurality of hardware components of the IHS, determine whether any of the one or more of the hardware component configurations are identified as vulnerable in the catalog of known vulnerabilities, and generate comprehensive applicability determination module, which upon execution by the IHS, determines configuration vulnerabilities in the catalog of known vulnerabilities that are present on the IHS for remediation.

The disclosed embodiments disclose techniques for decrypting an encrypted file. During operation, a recovery system receives an encryption key and a program executable that were previously used to encrypt an encrypted file using an unknown encryption technique. The program executable is executed in a sandbox environment that includes a known file containing a known pattern; the executing program generates a subsequent key and encrypts the known file. The subsequent key is extracted, and then characteristics of the known file, subsequent key, and the encrypted known file are compared to patterns determined for a set of standard encryption techniques to identify the specific encryption technique that was used. Knowledge of the identified encryption technique can then be used in combination with the original encryption key to decrypt the original encrypted file.

Embodiments of the present application relate to the technical field of network security, and provide a USB key-based identity verification method and device for software, and a storage medium. The method comprises: obtaining a license and a USB key, obtaining a first hash value, a license generation time, and a license expiration time on the basis of the license, and obtaining a second hash value on the basis of the USB key; if the first hash value is the same as the second hash value, calling a USB key executable file to obtain a third hash value, a one-time token, and a USB key time; if the USB key time does not exceed the license expiration time, integrating a USB key product code, a USB key user account, a USB key hardware code, a random number, and the one-time token to obtain a fourth hash value; and if the third hash value is the same as the fourth hash value, returning a Verification Passed result. Embodiments of the present application can enhance the software operation security, and ensure that software only runs in an authorized environment, thereby protecting the rights and interests of genuine software.

The invention relates to the technical field of computers, in particular to a hotfix loading method and device, electronic equipment and a storage medium so as to determine the offset of a TLS variable. Comprising the steps of compiling a patch function into a dynamic link library; obtaining a target offset of a thread local storage TLS variable in the patch function from the static link executable file, and obtaining relocation information of the TLS variable from the dynamic link library; after the patch file containing the patch function is dynamically loaded, a target memory address in the dynamic link library is determined based on the relocation information, and the target offset is stored in the target memory address; and when the to-be-repaired process is loaded to the to-be-repaired function, skipping to the patch function, and when the patch function is loaded, obtaining the target offset from the target memory address, and accessing the TLS variable of the patch function according to the target offset.

A computing system comprising one or more computing devices can access a file comprising documentation that includes a textual description and a source code snippet written to comply with a programming language syntax. The computing system can identify the source code snippet. The computing system can generate an executable based on the source code snippet. The computing system can initiate a test process that accesses the executable, the test process causing the executable to cause an event. The computing system can determine that the event is a valid event or an invalid event.

The invention relates to a PyGDBMI-based model simulation debugging method, and belongs to the field of model simulation. According to the method, C codes are compiled and constructed, codes consistent with models are compiled into executable files, mapping.xml files are read at the same time, and model information and the mapping relation between the models and the codes are stored in a dictionary in the form of key value pairs; a GdbController in a pygdbmi library is imported, a gdb process is started, and interaction with a GDB is achieved through an MI command; simulation operation of the executable file on the model and variable value setting are achieved through an MI command; stepping and variable obtaining in simulation debugging are achieved through an MI command, meanwhile, the obtained variables are stored in a dictionary list mode, and variable management, namely global data management, is achieved; simulation stopping in simulation debugging is achieved through an MI command. According to the method, multiple MI commands are designed through a PyGDBMI library, and operation, stepping, variable setting, variable obtaining and simulation stopping of model simulation debugging are achieved.

The invention relates to the technical field of software adaptation, in particular to a Beidou communication software development cross-platform adaptation method and system. The method comprises the following steps: defining an interface function library; constructing a virtual hardware logic module; linking the to-be-tested software, the interface function library and the virtual hardware logic module by utilizing a link rule, and determining an executable file of a single process; in the process of performing adaptation on the to-be-tested software by using the executable file of the single process, setting a simulation state of the virtual hardware logic module in response to calling of the state control interface by the test code, and setting a simulation state of the virtual hardware logic module in response to function calling of the native interface function by the to-be-tested software. And calling the virtual hardware logic module through an interface function library so as to carry out adaptation processing on the to-be-tested software. The invention aims to solve the problem that cross-platform adaptation cannot be realized due to the fact that all behavior characteristics of native hardware interfaces of different operating systems cannot be accurately reproduced in a virtual environment in the prior art.

The invention belongs to the field of software testing, and relates to a debugger testing method based on a large language model. The method comprises the steps that firstly, a random function protocol is generated, the random function protocol is constructed by a statement template and semantic constraints, the generated random function protocol serves as a cue word to be input into a large language model, and a function template meeting description of the random function protocol is generated; thirdly, compiling the generated function template, and if compiling of the function template fails, regenerating a function protocol and performing iterative correction until codes meet grammar and semantic constraint requirements; and if the function template is successfully compiled, reserving the function template for subsequent use. And secondly, performing grammar variation on the successfully compiled function template, and outputting a source file after the grammar variation. And combining and compiling the source file output after variation with the corresponding header file and the test case. And generating an executable file after combination and compilation. And finally, inputting the executable file into a debugger for execution, and detecting whether a bug exists or not.