201 results about "Call graph" patented technology

The invention discloses a vulnerability hidden danger intelligent detection method based on a large model, and the method comprises the steps: firstly carrying out the global static analysis of a source code set, constructing a complete call graph and a complete data flow graph of a program, and forming a structured code knowledge graph; and then, aiming at the identified candidate vulnerability slices, based on the maps, carrying out accurate context retrieval and enhancement, converting key information such as a call chain and a data traceability path which are strongly related to the vulnerability slices into natural language description which can be understood by a large language model, and injecting the natural language description into cue words, so that missing global context information is provided for the model. And the defect of complex code analysis capability is overcome. In this way, the problem that an attention mechanism loses efficacy in remote code association is solved, and the accuracy and reliability of vulnerability detection are remarkably improved.

The invention belongs to the technical field of computers, and particularly relates to a software fault repairing method and system fused with intelligent analysis, which comprises the steps of collecting a multi-level running log and performing structured preprocessing, constructing a dynamic calling graph through a time sequence encoder and a graph neural network, inferring a fault root cause in combination with a Bayesian causal inference model, and repairing a fault fault according to the fault root cause. And matching the repair strategy to generate an atomization instruction sequence, and deploying the atomization instruction sequence to a production system after sandbox environment verification. The system comprises a log acquisition module, a feature coding module, a graph construction module, a causal reasoning module, a strategy matching module, an instruction generation module, a sandbox verification module, a deployment feedback module and the like. Through end-to-end intelligent analysis and a closed loop verification mechanism, the fault positioning precision and the repair safety are remarkably improved, system self-evolution is supported, and operation and maintenance are promoted to be transformed from passive response to active autonomy.

The embodiment of the invention provides a multi-round dialogue security defense method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of data security. According to the method, dialogue semantic graphs capable of representing multi-round dialogue semantic evolution, intention circulation and entity association are constructed by obtaining multi-round dialogue content and a tool calling sequence; the method comprises the following steps of: respectively inputting user input information into two types of maps according to a tool calling graph representing a tool calling time sequence relationship and an interaction relationship to extract double risk feature vectors based on multi-round contexts and tool calling logic, and carrying out collaborative risk judgment in combination with a preset judgment rule; according to the invention, rapid integration of multi-round context information and accurate identification of attack risks are realized, so that a protection strategy can adapt to dynamic interaction requirements of an intelligent dialogue system in time, and the technical problem of low defense efficiency in the prior art is effectively solved.

According to the incremental defect detection method and system based on the function abstract, a function abstract design step, an SEG-based path condition storage method and a virtual node-based side effect abstract technology are adopted, a complete function call graph is constructed and stored as the function abstract, and the analysis precision and expandability are effectively improved; in the code change detection step, aiming at the differential detection requirement of the program, efficient identification of program version change is realized through an IR structured comparison method; an increment influence analysis step: based on the difference information, identifying an influence range brought by the change, and ensuring high efficiency and accuracy of increment analysis; and an incremental analysis step: recovering a path condition based on the behavior of the function abstract, recovering the complete program of the influenced program, designing a defect detection algorithm based on an SMT solver and the persistent function abstract, and realizing automatic detection and verification of potential defects of the program.

The invention is applicable to the technical field of code development, and provides a code modification method based on a CURD scene, which comprises the following steps: acquiring a business demand of code modification, and acquiring a data model required by code modification according to the business demand; based on the data model, obtaining a code file related to a CURD scene during code modification; analyzing a calling relationship among functions related to the CURD scene in the code file, and constructing a function calling graph; on the basis of the service requirements and the data model, service code snippets are generated, the service code snippets are combined and modified to the code file, code modification of the service requirements can be processed, and development efficiency and code quality are further improved.

The invention provides an automatic test generation platform and method for an operating system kernel derived function. The method comprises the following steps: (1) intelligent symbol extraction and analysis; (2) generating an LLM-driven test code; (3) performing automatic compiling and virtualization testing; and (4) intelligent error diagnosis and repair. According to the method, the test coverage degree is greatly improved, through the multi-level symbol context extraction technology, single function information is extracted, the dependency relationship of related functions in the same element is analyzed, a function call graph and data flow analysis are constructed, rich context information is provided for LLM, and the problem that traditional manual test case writing is incomplete in coverage is solved.

The invention provides a micro-service isolation operation method, medium and system for a productivity middle platform, belongs to the technical field of electric digital data processing, and provides the micro-service isolation operation method for the productivity middle platform, which realizes accurate scheduling of micro-service resources through multi-dimensional dynamic analysis. The method comprises the following steps: firstly, acquiring micro-service operation indexes including a processor occupancy rate, a memory occupancy rate, network throughput and the like, and generating a micro-service priority index; carrying out decomposition operation on the operation indexes, and constructing a reference and dynamic resource matrix; further calculating instantaneous and persistent competition indexes, and establishing a micro-service calling atlas; determining a resource allocation scheme by constructing a resource allocation equation set; determining a resource use threshold value by adopting an optimized dichotomy algorithm; and finally, the load of the resource unit is monitored in real time, when the load exceeds a threshold value, the migration cost is calculated, and the micro-service isolation operation is executed, so that the technical problem that a micro-service resource allocation and isolation mechanism cannot be accurately and dynamically adjusted in the prior art is solved.

An apparatus and method for improving ray tracing efficiency. For example, one embodiment of an apparatus comprises: An apparatus comprising: a binary instrumentation engine to perform binary instrumentation of ray tracing shaders and to trace execution of the ray tracing shaders to generate execution metrics; call graph construction logic to construct a shader call graph based on the execution metrics; shader source mapping logic to map the shader call graph to shader source code to generate a source code map; efficiency analysis logic to determine inefficiencies in ray tracing shader execution based on the source code map; and optimization logic to identify optimization actions based on the inefficiencies.

The invention relates to the field of interface component control, in particular to an interface component control method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a calling relationship of all interface components, and constructing a component calling graph based on the calling relationship; constructing a main function of the interface component according to the component call graph; when the obtained control command is a starting instruction of a to-be-started interface component, starting of the to-be-started interface component is controlled according to the starting command and a main function of the to-be-started interface component; when the obtained control instruction is a closing instruction of a to-be-closed interface component, closing of the to-be-closed interface component is controlled according to the closing instruction, the component calling graph and a main function of the to-be-closed interface component. According to the method, the multi-level interface component can be accurately controlled, and the display observability and logic control accuracy of the interface component are improved.

The invention discloses a security detection method and system for an interactive application in a power system, a medium and a processor, and relates to the technical field of network security, the method comprises the following steps: acquiring firmware of the interactive application in the power system, and unpacking to extract a target code file function; performing static stain analysis on the extracted target code file, and constructing a pollution propagation call graph; on the basis of a graph search algorithm, traversing the pollution propagation call graph, and detecting whether potential security vulnerabilities exist or not; and classifying and evaluating the detected security vulnerabilities, and outputting a detection result. According to the method, pollution propagation analysis among different programming languages is realized, and the accuracy and range of vulnerability detection are improved.

The invention provides a code review method and system based on a multi-dimensional knowledge graph and electronic equipment. The method comprises the following steps: constructing a business knowledge graph, a method calling graph and a code review knowledge graph; code data are obtained, a target code in the code data is determined based on the code review request, and the target code comprises code change content; generating a large model cue word in combination with the business knowledge graph, the method calling graph and the code review knowledge graph; and according to the big model cue word, calling an AI big model to perform joint review on the code change content, and generating a review report which at least comprises a repair suggestion. According to the method, multi-dimensional knowledge of business, code calling and code review is integrated, a more comprehensive and closely associated knowledge system is formed, the generated cue word can accurately guide the AI large model to review code change in combination with multi-field knowledge, blindness of the large model during review is avoided, and review efficiency and accuracy are improved.

The invention discloses a software supply chain vulnerability verification code generation method based on guiding fuzzy testing. The method comprises the steps that s1, a tripartite library dependency graph with a binary program as a starting node is generated; s2, performing static component analysis on the target application software component to form a component dependency graph; analyzing the component dependency graph layer by layer, and constructing an overall function call graph; s3, matching all vulnerability functions existing in the three-party component based on CVE information, calculating vulnerability function layer distance according to an overall function call graph, and performing directed utility calculation on a prepositioned function and a function priority for fuzzy test energy distribution; s4, performing key node identification and vulnerability distance calculation on a tripartite library critical function in the overall function call graph; and s5: transmitting binary static analysis results of s1 to s4 to a fuzzy test tool for directional fuzzy test. The method has the advantages of being simple in principle, easy to implement, higher in testing capacity, better in applicability and the like.

The invention provides a redundant code identification method and system based on a data flow diagram. The problem that multiple types of redundant codes cannot be comprehensively identified in the prior art is solved. Identifying a waste interface set through set operation processing of an interface access log, a total station scanning result and code warehouse information; performing dynamic call detection and data flow analysis based on a static analysis tool and the abstract syntax tree, and identifying an internal useless code set; identifying and combining a waste script set and a waste consumer set to form a waste component set through state check and log analysis of consumer operation states, script execution records and task scheduling configuration; constructing a whole system call graph to perform reverse reachability analysis, and identifying a cascade waste code set; and finally, generating a complete redundant code report containing statistical data, a detailed list and risk assessment based on the various sets.

An impact analysis device acquires a list of method information related to a difference between a new version of a library and an old version of the library, based on a source code of the new version of the library and a source code of the old version of the library; extracts, from the list, a first difference related to a method existing in a first call graph of software that uses the old version of the library; extracts, from the list, a second difference related to a method added to a second call graph of the software that uses the new version of the library; extracts a set of method information of a caller of a transition added to the second call graph in comparison with the first call graph; and outputs a union of the first difference, the second difference, and the set, thereby enhancing support for determining a likelihood that a library update could affect operations of software.

The invention discloses an open source component analysis method based on a static program, and relates to the technical field of software analysis. Project source codes are input and analyzed, a semantic calling graph is obtained, and hierarchical management is conducted on the semantic calling graph; carrying out topological sorting on the layered semantic calling atlas to obtain a component check sequence; and comparing the semantic call maps corresponding to the new version and the old version of the to-be-upgraded component, performing software detection operation on the to-be-upgraded component, and outputting a conflict report. According to the method, a layered semantic calling graph is constructed and contains rich context information, so that analysis can go deep into the level of whether behaviors and semantics of the method are changed or not, topological sorting is carried out on component dependency relationships, a component checking sequence is provided, the problem that a conflict is repaired in reality is solved, and the method is more practical. By means of the method, it is guaranteed that before any component is checked, all the components on which the component depends are analyzed and confirmed, and orderliness and certainty of the analysis process are guaranteed.

A computer-implemented method for trace-driven call-graph-aware proactive coordinated autoscaling of component microservices in an application includes generating performance-resource elasticity models of endpoints of the component microservices of the application. Workload levels of the endpoint of the component microservices is predicted based on user traffic observed at a front end service. A trace-level performance of the application is predicted for different microservice replica scaling based on the performance-resource elasticity models at end points, the ends points on the trace call graph and the predicted workload levels. A microservice replica scaling is recommended for each of the component microservices to meet predefined trace-level user service level objectives.

The invention discloses a malicious code detection method and device for a third-party tool, a medium and a product. The method comprises the following steps: acquiring code data of a third-party tool; static analysis is carried out on the code data of the third-party tool to obtain static features, and the static features comprise at least one of cross-language call graph features, multi-version control flow graph difference features and local entropy values; the code data of the third-party tool is dynamically analyzed, dynamic characteristics are obtained, and the dynamic characteristics comprise at least one of an API calling sequence, memory operation information and a taint propagation path; based on a pre-trained detection model, the static features and the dynamic features are detected, a detection result of the code data of the third-party tool is obtained, and the detection result is used for indicating whether the code data of the third-party tool belongs to malicious codes or not. According to the technical scheme, collaborative analysis can be carried out on the code data through the static features and the dynamic features, and the detection accuracy of malicious codes is improved.

The invention discloses an intelligent detection method for network security vulnerabilities, and relates to the technical field of network security vulnerability detection, and the method comprises the following steps: analyzing source codes to construct an abstract syntax tree, a control flow graph and a call graph, identifying sensitive operation points based on a rule base, and screening hotspot functions in combination with code indexes and the call graph; extracting a candidate path from a program entry to a sensitive operation point, encoding to generate a path context snapshot, and scoring through a pre-training model; selecting a high-risk path to execute sparse symbolic execution, simplifying constraints by using variable interval information, and dynamically feeding back and adjusting scores; poC input verification is generated for the path triggering the vulnerability constraint, a report containing the path constraint, the triggering condition and the PoC is output, program analysis and machine learning are combined, the vulnerability detection efficiency and precision are improved, and the method is suitable for code security analysis of scenes such as an embedded system.

The invention discloses a method and a device for generating a software vulnerability analysis report, and relates to the field of information security. The method comprises the following steps: acquiring auditing information of software vulnerabilities; a code feature matching rule for the software vulnerability is generated according to the auditing information through the large language model, and the code feature matching rule is used for matching a code calling mode related to the software vulnerability in the target software project; constructing a calling graph of the target software project; according to the code feature matching rule and the call graph, the correlation degree between each code snippet of the target software project and the software vulnerability is detected, and the correlation degree is used for evaluating the risk level of each code snippet of the target software project; and generating a software vulnerability analysis report of the target software project according to the association degree between each code snippet of the target software project and the software vulnerability. The technical problem that in the prior art, an open source software vulnerability detection tool cannot accurately evaluate the real influence of vulnerabilities in specific project contexts is solved.

The invention provides a binary code decompiling system based on large model multi-stage fine tuning. The method comprises two stages: a first stage: a data set acquisition and construction stage: acquiring a source code data set comprising source codes and binary file pairs from an open source project and code data set, and obtaining a high-quality decompilation data set through a data preprocessing process; the second stage is a decompilation stage based on large model fine adjustment and static analysis, decompilation is carried out after a decompilation data set is compiled, an assembly code obtained after decompilation is aligned with a source code in the decompilation data set to be used for fine adjustment of the open source large model, a function call graph analysis technology is cooperated, a program context is obtained, and the open source large model is subjected to static analysis; and obtaining a final decompilation large model. Therefore, the purpose of providing a high-quality decompilation data set and an efficient decompilation algorithm is achieved.

The invention discloses a cross-platform binary code block hierarchical semantic similarity detection method and a related device, and belongs to the field of code vulnerability detection.The cross-platform binary code block hierarchical semantic similarity detection method comprises the following steps that structural information of a binary file is analyzed, a machine instruction is analyzed through a hybrid disassembling engine, a basic block is extracted from the structural information of the binary file, and the basic block is extracted from the binary file; constructing a control flow graph, a data dependency graph and a function call graph; extracting instruction level semantics, basic block level semantics and function level semantics from the instruction sequence, the basic block, the control flow graph, the data dependency graph and the function call graph; according to the instruction-level semantics, the basic-block-level semantics and the function-level semantics, constructing instruction-level features, basic-block-level features and function-level features; and carrying out hierarchical similarity detection on the instruction-level features, the basic block-level features and the function-level features. The method and the related device can solve the problems of low detection efficiency and poor accuracy when a traditional vulnerability detection method is used for detecting vulnerabilities.

The invention discloses a fault propagation path determination method and device, a storage medium and electronic equipment, and relates to the field of Internet of Things. The method comprises the following steps: acquiring a target data set; a service calling graph is constructed according to the target data set, then strong connectivity vectors in the service calling graph are determined, and the service calling graph is used for representing a topological structure and a dependency relationship of service interaction in the distributed system; the strong connectivity vector is used for representing a connectivity component of which the bidirectional calling frequency is greater than a preset frequency and / or the data interaction strength is greater than a preset strength in the service calling graph; performing neighborhood feature aggregation on the service call graph to obtain a time sequence feature matrix; and determining a fault propagation path of the distributed system according to the strong connectivity vector and the time sequence characteristic matrix. According to the method and the device, the technical problem of poor fault propagation path prediction accuracy caused by lack of quantification of dependency relationship and topological association between services in fault propagation prediction in the prior art is solved.

The invention discloses a risk function detection method and system based on patch submission and risk propagation analysis. According to the method, static code analysis and a large language model are combined, and functions with security risk propagation possibility in patches can be identified and intelligently classified. The method comprises the following steps of: screening candidate functions, and extracting functions which are deleted, remarkably modified or quoted and changed from patches as detection objects; pruning a function call graph, and constructing an approximate Steiner sub-graph based on a call relationship to capture a key propagation path; and risk function classification: driving a large language model to complete function risk judgment by combining CVE information, a patch context and a call graph through a prompt project. According to the method, a risk function detection scheme combining the language model and call path pruning is proposed for the first time, and the method can be widely applied to scenes such as software supply chain security assessment and vulnerability repair verification and has the advantages of high accuracy, high cross-language adaptability and the like.

In some implementations, a package is selected and a set of dependencies associated with the package are determined. Individual dependencies in the set of dependencies are used to create a set of partial call graphs that are stitched together to create a complete call graph of the package. A set of upgrade candidates for a dependency is determined. For an upgrade candidate, issues associated with upgrading the package to use the upgrade candidate are determined, a state of a dependency graph associated with upgrading are determined, diamond dependencies in the dependency graph are determined, a number of vulnerabilities and a severity of the vulnerabilities addressed by upgrading to the upgrade candidate are determined, and a risk-benefit score associated with each upgrade candidate is determined. The upgrade candidates are prioritized based on the associated risk-benefit score to create prioritized upgrade candidates that are provided to a software developer.

The invention relates to the technical field of network security, and discloses a program-level code similarity analysis method and device based on semantic slicing, and the method comprises the steps: constructing a program-level target function call graph based on a target source code; matching the target function call graph with a standard function call graph to obtain a plurality of isomorphic sub-graphs; performing semantic slicing on each function node in the first sub-graph and the second sub-graph to obtain a first slicing result of the first sub-graph and a second slicing result of the second sub-graph; and evaluating the slice similarity between each function in the first slice result and each function in the second slice result, and determining the similarity of the target source code according to the slice similarity. According to the method, the user-defined function call graph for eliminating system function interference is constructed, an isomorphic sub-graph matching algorithm is combined, multi-dimensional features are comprehensively considered, the accuracy of similarity calculation is improved, effective support is provided for practical application scenes such as code reconstruction and security audit, and the guarantee of code quality and security is improved.

The invention discloses a cross-language interaction malicious behavior detection method based on a high-order function, and relates to the technical field of computer security. The method comprises the following steps: receiving a source code of a certain program, modeling a cross-language interface in the program, and identifying and marking a cross-language calling boundary; different language source codes are converted into universal intermediate representations (IR), the IR is combined, and cross-language calling points are marked; constructing a global cross-language function call graph and a control flow graph, determining a function analysis sequence by inverse topological sorting to perform dependency analysis on each function, and abstracting dependency information in the processes into a function abstract in a high-order function form; and parameter instantiation is carried out when function calling is processed, so that the dependency relationship between the cross-language APIs is obtained. According to the method, efficient analysis and transmission of the cross-language dependency relationship are realized through the high-order function abstract and the dependency matrix, the high overhead of constructing a complex system dependency graph by a traditional method is avoided, and the analysis efficiency and the detection accuracy are improved.

The embodiment of the invention provides a vulnerability analysis method based on a large model and SAST, a program product and equipment. The vulnerability analysis method based on the large model and the SAST comprises the steps that according to vulnerability information of any vulnerability in a vulnerability information base, a life cycle diagram of the vulnerability is generated; based on the life cycle diagram, obtaining a code context where the vulnerability is located from a project code; analyzing the code context by adopting a large model to obtain a vulnerability cause and an execution function of the vulnerability; backtracking and searching an entry function of the vulnerability from the execution function in a global call graph; wherein the global call graph is generated by analyzing the project code by adopting an SAST tool; outputting an analysis result of the vulnerability; wherein the analysis result comprises the vulnerability cause, the execution function and the entry function. According to the embodiment of the invention, the vulnerability availability information of various vulnerabilities in the open source project can be stably and accurately provided.

The invention provides a vulnerability reachability analysis method for a binary mode open source component and related equipment, and the method comprises the steps: determining a target open source component used in to-be-detected software in a binary form, and recognizing the version information of the target open source component; determining a target vulnerability in a vulnerability query database according to the identifier and version information of the target open source component, and extracting a vulnerability function of the target vulnerability; and based on the target vulnerability, extracting a calling relationship between an entry program of the to-be-detected software and the target open source component, and generating a first calling graph. And according to the first call graph, extracting an import function used for calling the target open source software in the to-be-detected software. And determining a source code warehouse address of a target open source component contained in the first call graph, obtaining a source code of the target open source component from the source code warehouse address, and generating a second call graph. And based on the vulnerability function, the import function and the second call graph, determining whether the vulnerability function has accessibility in the to-be-detected software.

The invention discloses an artificial intelligence-based code generation method, which comprises the following steps of: S1, performing function level analysis on a generation request input by a user, extracting a function name, a parameter, a return value, a calling relationship and a dependency relationship, and generating a function calling graph; s2, taking the generation request input in the step S1 as a query, performing retrieval in combination with the function call atlas and the external knowledge base generated in the step S1, and jointly inputting the retrieved content and the coding model to generate a structured code snippet; and S3, taking the generation request input in the S1 and the structured code snippets generated in the S2 as joint input, and generating codes meeting individuation and project specifications. Through a function graph and a retrieval mechanism, a generated result has structural consistency and semantic integrity, and the matching degree with context requirements is remarkably improved (the actual measurement Top-1 accuracy is improved by about 22%).

The invention discloses a micro-service response delay prediction method and device, equipment, a medium and a product, and relates to the technical field of cloud service responsiveness, and the method comprises the steps: obtaining an API call request of a user; the API calling request comprises a plurality of API requests; based on the directed graph processing device of the API, obtaining a micro-service calling graph of micro-service calling time sequence information corresponding to the API request; the micro-service calling graph is composed of a plurality of pieces of micro-service calling information with time dimension information; each piece of micro-service calling information is represented by a node in the micro-service calling graph; the GNN-based delay prediction device determines the prediction delay of each node, and accumulates the node delays belonging to the same micro-service to obtain the response delay of each micro-service in the micro-service call graph; and according to the response delay of each micro-service in each API request, predicting the micro-service response delay of all micro-services. The accuracy of delay prediction can be improved.