137 results about "Control flow" patented technology

The invention relates to the technical field of software security, and discloses a variational inference-based micropatch repair path adaptive optimization method, system, device and medium, and the method comprises the steps: constructing a joint control flow diagram and a data flow diagram of a to-be-analyzed program, and forming a program structure diagram; based on the program structure diagram, modeling and sampling potential variables of the repair paths through variational inference, and generating a plurality of candidate repair paths; for each candidate repair path, generating a micropatch statement according to context semantics of each node in the path, and inserting the micropatch statement into a corresponding instrumentation position in the source code; and performing multi-dimensional scoring and sorting on the candidate repair paths, and selecting an optimal repair path for deployment according to a scoring result. According to the method, the structural breakthrough of the whole process is realized in the aspects of path identification, patch generation, strategy optimization, engineering deployment and the like, and a technical support is provided for constructing a software vulnerability repair system with autonomous generation, semantic understanding and controllable deployment capabilities.

The invention discloses an intelligent contract vulnerability detection method and system based on semantic comprehension and program path analysis, and belongs to the technical field of network security. The method comprises the following steps: firstly, analyzing an intelligent contract code by using a large language model, and reasoning to generate a structured security rule for defining a taint source, a taint sink and a purifier; secondly, guiding a taint analysis engine by using a security rule, and tracking on a data flow and a control flow diagram of a program so as to efficiently screen out a high-risk taint path; then, carrying out reachability verification on the high-risk path by adopting a symbolic execution technology; and finally, performing final context review on the verified vulnerability path by using the large language model again to generate a vulnerability report. According to the method, the semantic comprehension ability of the large language model and the preciseness of traditional program analysis are subjected to multi-stage cooperation, so that the detection precision and efficiency of the intelligent contract logic vulnerability can be remarkably improved, the interpretability of a report result is greatly enhanced, and the method has important application value.

The invention discloses a compiling method for compiling a C language source code into an RISC-V assembly code. The method comprises the following steps: acquiring a C language source code; performing lexical analysis on the C language source code to generate a mark flow; performing syntactic analysis on the mark flow, and constructing an abstract syntax tree; performing semantic analysis on the abstract syntax tree to generate a target abstract syntax tree; constructing a runtime environment of the RISC-V assembly code; generating an intermediate code and a control flow diagram corresponding to the intermediate code according to a rule in the runtime environment and the target abstract syntax tree; generating a target code by using the intermediate code and the control flow diagram corresponding to the intermediate code; according to the technical scheme, the intermediate representation more adaptive to RISC-V custom instruction mapping can be generated, so that the execution efficiency of assembly codes is improved; and meanwhile, by designing a lightweight runtime environment, the performance overhead is further reduced.

The invention belongs to the technical field of power supply control, and particularly discloses a digital power supply graphical programming method based on flow driving, which comprises the following steps of: constructing a power supply control Flow component library which comprises a plurality of Flow nodes, and storing the nodes in a script file form, the script file comprises basic code snippets required by node function implementation and describes data terminals, logic terminals and node attribute parameters of input and output reserved by nodes; constructing a graphical programming module, and providing a graphical programming interface to receive a setting operation of a user so as to form a graphical program logic description file; generating a graphical program script file according to the description file and each Flow node script file; and generating a power supply control code based on the graphical program script file and the chip peripheral drive script file, and compiling and burning the power supply control code into an embedded controller of the digital power supply. According to the method, low-code / code-free development can be realized, and the development difficulty is effectively reduced.

The invention discloses a malicious code control flow feature extraction method based on a graph neural network. The method comprises the following steps: constructing a control flow graph, a data flow graph and a function call graph; designing a drawing neural network architecture; training a graph-level classifier; performing graph interpretation by using a GNNExplainer algorithm, attention mechanism analysis and a gradient analysis method; converting the extracted control flow mode into a structured detection signature, and mapping the structured detection signature to an original binary code; and integrating with a static analysis tool through a standardized interface. The invention further discloses a malicious code control flow feature extraction system based on the graph neural network. Multi-level graph structure representation is constructed, important information such as a control flow structure and a data dependency relationship is fully reserved, the deep structure similarity of malicious codes can be recognized, the deformation resistance is higher, and therefore the malicious code detection precision is improved; according to the method, key sub-graphs can be recognized, graph structure features are converted into detection rules, then the detection rules are integrated with existing static analysis tools, and practicability is improved.

The invention provides a code detection and protection method, system and device and a medium, and belongs to the technical field of malicious code detection.The method specifically comprises the steps that WASM byte codes are obtained; converting the byte code into a WAT text and an intermediate representation, and analyzing meta-information; respectively constructing control flow diagrams and program dependency diagrams of the JS and the WASM based on the AST and the intermediate representation, and fusing the control flow diagrams and the program dependency diagrams into a unified dependency diagram through cross-language interface nodes; matching the dependency graph by using a preset malicious rule base, and marking a suspicious level; if not, WASM is injected into a Unikernel mirror image to be executed in an isolation environment, and behavior fingerprints during operation are collected; and outputting a malicious and non-malicious conclusion by combining the static analysis result with dynamic feature rating such as resource consumption and abnormal events. Through cross-language dependency graph fusion and dynamic and static combination analysis, malicious behaviors in WASM and JS interaction are captured, execution and behavior collection are isolated, the misjudgment risk is reduced, the detection accuracy is improved, and efficient and accurate WebAssembly module protection is achieved.

The application discloses a kind of multilingual code generation methods based on self-supervised pre-training, comprising the following steps: obtaining and cleaning multilingual code data, forming training corpus;Code data is represented as abstract syntax tree, the control flow graph and data flow graph of code data are extracted, and unified semantic representation is obtained by combining graph encoder and sequence encoder;Self-supervised pre-training task is designed, and the semantic representation is pre-trained based on the training corpus;Multilingual pre-training model is constructed based on the recursive neural tensor network and multilingual embedding matrix improved in structure;When natural language is input by user, the multilingual pre-training model is used to generate target language code;Target language code is corrected by routine function test and syntax check.The application realizes accurate generation and executable improvement of cross-language code by combining self-supervised pre-training with multichannel recursive combination and hierarchical recursive development mechanism.

The invention provides a binary program vulnerability mining method, device and system based on symbolic execution and taint analysis and a medium, and the method comprises the steps: disassembling a target program, extracting a control flow graph (CFG) and a data flow graph (DFG), recording a node state through a hash table, and generating a feature representation through nonlinear transformation; performing simulation execution based on CFG, DFG and feature representation, recording variable symbol values to obtain path conditions, and recursively solving constraints to generate path mapping; marking input as taint data, recursively calculating a propagation path to generate a taint flow diagram, and determining a taint state after sensitive operation; checking whether the stains are subjected to sensitive operation or not, and if the influence of integral formula calculation exceeds a threshold value, judging that potential vulnerabilities generate a candidate set; and calculating grades through a risk assessment formula, and generating a report containing positions, types, grades and repair suggestions. The method combines symbolic execution and taint analysis, can comprehensively and accurately detect vulnerabilities, has remarkable precision and efficiency advantages, and is suitable for complex program security analysis.

The application relates to an automatic code auditing method and device, computer equipment and a storage medium, comprising the following steps: obtaining the syntax structure, control flow and data flow of a code to be audited; constructing a context graph of the code to be audited according to the syntax structure, control flow and data flow of the code to be audited; obtaining a multi-modal collaborative vulnerability detection method, wherein the multi-modal collaborative vulnerability detection method comprises a static analysis method based on rule matching, a symbolic execution method based on a code path and a large model reasoning method based on semantic understanding, and the weights of the methods; and identifying one or more code vulnerabilities, the vulnerability types of the code vulnerabilities and the confidence according to the context graph of the code to be audited and the multi-modal collaborative vulnerability detection method. The method can improve the code auditing efficiency and process auditing codes of various vulnerability types.

The invention discloses a static analysis tool test case generation method based on a program slicing technology, which comprises the following steps: step 1) according to a defect report of a static analysis tool, collecting and extracting variable information related to generation of a specific defect in a program as a slicing criterion; 2) through control flow analysis and data flow analysis, recording data and a control dependency relationship between statements, constructing a program dependency graph, and calculating a statement set having a dependency relationship with a slicing criterion; 3) positioning nodes corresponding to the statement set in the abstract syntax tree of the source code through a depth-first search algorithm, and deleting other nodes; the method comprises the following steps of (1) collecting a user-defined type or an external function declaration which is used through static program analysis, and outputting the type definition and the function declaration to an independent header file, and (5) writing edited codes into a file, and clearing redundant information to serve as a test case, the method adopts two-section analysis, and the test case can be generated efficiently and precisely.

The invention relates to the technical field of attack tracing, in particular to an attack tracing method and device based on a symbolic execution engine, and the method comprises the steps: recognizing a plurality of dependent explosion functions of a pre-constructed execution unit sequence, so as to construct an independent subprogram; constructing a system call control flow diagram of a historical event processing cycle by combining static and dynamic analysis; auditing logs containing parameter values are collected in the execution period of the target program so as to construct a thread-level traceability graph; and according to the system call control flow diagram, determining whether a node of dependent explosion exists in the thread-level traceability diagram, if so, reconstructing the independent subprogram by using the node of dependent explosion, and analyzing the reconstructed independent subprogram by using a symbolic execution engine to reconstruct an attack path. Therefore, the problem that a related tracing attack method needs to carry out instrumentation on a system, or depends on static analysis, or depends on an unreliable application log, or needs to use additional auxiliary hardware to realize tracking is solved.

The invention discloses a method for evaluating vulnerabilities by combining vulnerability codes and vulnerability description texts and using a cross-task attention mechanism. The method comprises the following steps: firstly, for a vulnerability code part, converting the vulnerability code part into a control flow diagram, and generating a plurality of execution paths from the control flow diagram; for the vulnerability description text part, some key vulnerability elements are extracted from the vulnerability description text part; then, considering that seven evaluation tasks have certain relevance, when feature representation of codes and texts is learned, a cross-task attention mechanism is introduced to capture relevance features among the tasks; and finally, carrying out weighted summation on the probability predicted by the classifiers at the code level and the text level to obtain a prediction result of final vulnerability assessment.

This invention relates to a reliable translation method for synchronous dataflow languages ​​based on the 8114 criterion, belonging to the field of code generation. The invention obtains the abstract syntax tree of the Ctemp intermediate language through lexical and syntactic analysis and translation of Lustre source code; it traverses the Ctemp abstract syntax tree and designs translation methods for control flow statements and assignment statements within the tree structure; it traverses expressions within statements and designs translation methods that add type casting to ensure that statements are semantically correct while avoiding implicit type conversions; it extends the theorem on type relations in Cltype for verifying type operations; and it extends the theorem on type casting and binary operations in Ctemp semantics to achieve semantic formal verification. This invention significantly improves the compliance of C code generated by code generation tools with the GJB 8114 specification.

The invention provides an evidence-driven large language model MISRA C rule review method and system for aviation safety. According to the method, formalized feature extraction is carried out from four aspects of grammar structure features, semantic structure features, logic analysis features and preprocessing behavior features for target codes according to various rules of MISRA C forcing class rules, and diagnosis information is diagnosed in combination with an industrial-grade compiler; generating a structured evidence set comprising abstract syntax tree node statistical features, code context structure features, control flow graph features, function internal data flow analysis features, symbol and type table features and macro definition analysis features; and based on the structured evidence set and the large language model, executing evidence tracing, rule matching and logical reasoning according to a preset thinking chain process, and outputting a structured judgment result containing illegal rule numbers, evidence description and code positions. According to the method, the false alarm rate can be remarkably reduced while the high rule coverage rate and the detection accuracy are kept.

Embodiments of the present application disclose a method, device, equipment, medium and program product for generating an adversarial sample. The method comprises: obtaining a preset code file; determining a non-conditional jump instruction in the preset code file; modifying the non-conditional jump instruction into a reconstructed jump instruction according to a preset instruction modification rule; performing control flow flattening processing on a basic block of the preset code file; based on a result of the control flow flattening processing, inserting a preset application programming interface (API) sequence into the preset code file according to a preset rule to obtain a target code file containing a malicious code feature; inserting noise into the target code file to obtain an initial sample; and performing iteration on the initial sample according to a preset evolution algorithm to obtain an adversarial sample. The embodiments of the present application can generate a large number of malicious code adversarial samples that can evade antivirus software and sandboxes.

This invention provides a method for generating complex functions on a low-code platform based on large model code interpretation and generation. By capturing and standardizing user input, a structured intent graph containing business entities, operational relationships, parameter constraints, and control flow topology is constructed as a unified semantic anchor. Combined with a pre-defined domain rule base, a semantic alignment validator is designed to achieve multi-dimensional semantic comparison and conflict detection between code and requirements. Code snippets are generated in parallel by multiple models and verified in real time, and semantic conflicts are resolved through local regeneration. By fusing the results of multiple models to construct a joint abstract syntax tree, lightweight symbolic execution is used to simulate the correctness of cross-model code, locate and correct core logical conflicts. This invention significantly improves the consistency, accuracy, and automatic correction capabilities of low-code platform code generation.

The application discloses a large language model weight compression method, an inference operation method, a system and a medium, and belongs to the technical field of large language model weight compression and inference operation optimization. The method comprises the following steps: acquiring a weight matrix of a large language model and constructing an exponential high-frequency window and a benchmark value, classifying and encoding each weight data into a fixed-length code word and splitting the fixed-length code word into an independent bitmap, synchronously generating a compact value stream and a rollback value stream, and packing the compact value stream and the rollback value stream into weight compression data; loading the weight compression data, generating a state mask and a channel prefix mask in a register based on the bitmap, calculating a reading offset by using a population count instruction, reading a compressed data segment from a corresponding data stream, reconstructing weight data in the register in combination with the code word, and finally directly inputting the weight data into a matrix multiplication unit for operation; therefore, by implementing the application, the problem of efficiency reduction caused by control flow divergence and redundant memory access in GPU inference of existing variable-length encoding can be solved, and the model inference efficiency under lossless compression can be improved.

A method of detecting malicious behavior in a malicious behavior detection apparatus that detects malicious behavior by analyzing the code of a program, comprises generating a first control flow graph (CFG) by performing dynamic analysis on the program, generating a second CFG by extracting a code block that is likely to be executed by a conditional branch instruction included in the program, and comparing the first CFG and the second CFG to detect hidden code included in the program, and detecting a malicious behavior of the program by determining whether the detected hidden code is a malicious code. According to the constitutions, the time it takes to discover and respond to new types of malicious code can be shorten by extracting hidden code related to the malicious behavior and detecting malicious behavior.

Described are techniques for reducing overhead controls. A loop tree is constructed from a program, such as a structured control flow program. Structured control flow refers to a programming concept where the flow of control to a block or region is based on single entry and single-exist methodology (SESE). A loop tree refers to a tree-like data structure that graphically represents loop(s) and / or an if-condition(s) in a program, such as a structured control flow program. A loop splitting operation or a loop unrolling operation may then be performed in connection with the node of the loop tree that is identified as having the highest benefit (ratio of execution cycles gained to the increase in code size) representing an if-condition or a loop, respectively, provided that the resultant code fits in the instruction buffer.

The invention relates to the technical field of computers, in particular to a metamorphic relation identification method based on program dependency graph features. The method comprises the following steps: obtaining a control flow graph (CFG) of a target program, and obtaining a control dependency graph according to the control flow graph and a forward dominating tree; obtaining a program dependency graph according to the control dependency graph and the data dependency relationship; according to a program analysis requirement slicing criterion C = (N, V) of a target program, graph traversal is conducted on the program dependency graph, program slicing features are obtained, N represents instructions in the target program, and V represents a variable set; and inputting the program slice features into a target prediction model for identification, and obtaining a prediction result corresponding to the metamorphic relationship of the target program. By the adoption of the method and device, the metamorphic relation obtaining accuracy can be improved, the situation that the metamorphic relation cannot be obtained is reduced, program testing convenience can be improved, and software quality is improved.

The application discloses a code verification method and device based on path traversal, a medium and equipment. The method finds all paths from the program entrance to the target statement with a path length not exceeding K in a control flow graph through a loop body step decomposition manner, and forms a path set. Then, the paths are traversed, and reachability verification is performed on the traversed paths. When the paths are subjected to reachability verification, array variables are simplified into array elements through expression simplification calculation, and operations related to the array variables are expanded into SMT constraint expressions related to the array elements in combination with variable constraint replacement, so that the SMT constraint solving can process variables related to arrays, the complexity of the SMT constraint solving is reduced, the solving and analysis of unreachable path segments are avoided, and the analysis efficiency is improved.

The application relates to the technical field of software test automation, and provides a requirement-driven test case automatic generation method and system based on a semantic test graph, which comprises the following steps: performing multidimensional static analysis on source code, respectively constructing an abstract syntax tree, a control flow graph and a function call graph, and extracting function call relations and data flow dependency relations; constructing a semantic test graph by taking functions as nodes, taking function call relations as main edges and taking data flow dependency relations as auxiliary edges, and aggregating function nodes in the semantic test graph into several function modules; obtaining several test requirement nodes, calculating semantic similarity between the test requirement nodes and the function modules, establishing a mapping relationship from the test requirement nodes to the function modules, and forming a requirement-program structure association graph; and based on the requirement-program structure association graph, generating a test intention for each test requirement node, and converting the test intention into an executable test case. The highly corresponding relationship between the generated test case and the business requirement is ensured.

The invention provides a test case generation method and device, and belongs to the technical field of computer software testing and validing.The test case generation method comprises the steps that a control flow and a data dependency relationship in a to-be-tested software code are converted into a logic equivalence model; determining at least one input condition for activating a fault effect value corresponding to a current fault site in the logic equivalence model and propagating the fault effect value to the observation point; and generating a test case corresponding to the current fault site based on the at least one input condition. The test case for carrying out deterministic detection on null pointer dereference defects in software codes can be generated.

The present disclosure provides a method and device for restoring obfuscation of an Android string, a computer device and a medium, comprising: converting intermediate bytecode of an Android application installation package data into a first representation file and a second representation file; performing semantic understanding on the second representation file to obtain a control flow graph corresponding to a target method body; identifying obfuscation points based on the control flow graph corresponding to the target method body to obtain a plurality of target candidate sentences; generating a corresponding slice standard representation for each target candidate sentence; reversely constructing a program dependency chain based on the plurality of target candidate sentences to obtain a data flow graph structure; determining a minimum code subset based on the data flow graph structure and the slice standard representation corresponding to each target candidate sentence; performing a reorganization operation on the minimum code subset to generate a subprogram; embedding the subprogram into a class file to obtain a target class file; and executing the target class file through the first representation file to obtain a decrypted string. Thus, the success rate of string decryption is improved.

The application relates to a code vulnerability detection method and relates to the technical field of computers.The method comprises the following steps: obtaining to-be-detected code; performing preprocessing on the to-be-detected code to obtain a normalized source code representation; constructing an abstract syntax tree based on the source code representation; constructing an intermediate representation based on the abstract syntax tree; wherein the intermediate representation comprises a core expression set, a target control flow graph and a target function call graph; constructing a target value dependency graph based on the target control flow graph and the target function call graph; performing constraint extraction based on the target value dependency graph and the target control flow graph to obtain a target constraint expression; and inputting the target constraint expression into a constraint solver to obtain a vulnerability detection result.The code vulnerability detection method can realize high-precision, low-false-alarm and strong-context-aware code vulnerability detection, and is more suitable for scenes with strict security requirements.

The application discloses a neural machine translation Internet of Things remote proof method for data flow attacks, which comprises an offline stage and a runtime verification stage. In the offline stage, a verifier and a prover first complete the negotiation of a symmetric key for subsequent remote proof, and at the same time, complete static plugging for a target program. A program control flow dataset is pre-constructed through fuzzy testing, a neural machine translation model is trained to establish the mapping of program input to an execution path, and a control flow graph is embedded to provide a structured prior for decoder attention. In the runtime verification stage, the verifier initiates a proof challenge to the prover, the prover provides the program input and the control flow path of the last execution, the verifier predicts a benign path from the program input by the neural machine translation model, and the difference between the benign predicted path and the actual path is used to judge the legitimacy of the prover. The application realizes accurate modeling of the program execution path, and shows effective detection capability for the abnormal path triggered by malicious input containing real vulnerabilities, and a good balance is achieved between detection coverage and running overhead.

The application discloses a source code processing method and device and electronic equipment. The method comprises the following steps: obtaining source code and configuration information of a project; performing syntax analysis processing on the source code based on the configuration information, and generating an abstract syntax tree of the source code; determining a target node of a correlation function in the abstract syntax tree, performing analysis processing on the target node, and obtaining an analysis processing result of the target node; performing code block division based on the analysis processing result of the target node, obtaining a code block division result of the target node, performing control flow analysis based on the code block division result of the target node, and generating a control flow graph of the target node; and performing dependency analysis based on the control flow graph of the target node, and obtaining dependency information of the target node. In combination with common static code analysis technology and a dependency information extraction method, the dependency relationship of each function is extracted, code understanding and code transplantation are facilitated, and the problem of how to extract dependency information in the code when software testing is performed on the source code is solved.

This invention provides a method and system for inter-process taint analysis of binary programs. The method includes the following steps: analyzing the binary program using a preset static decompilation tool to obtain corresponding binary program information; determining the function call relationships in the binary program based on the binary program information and constructing a call relationship graph; marking the calling functions of taint source functions from the functions in the call relationship graph based on a preset taint information database; identifying the starting analysis position in the call relationship graph based on the calling functions of the taint source functions; determining the inter-process control flow graph based on the call relationship graph with the identified starting analysis position; and determining whether the taint information generated by the taint source functions in the inter-process control flow graph is passed to a specified position in the sink function. If so, it is recorded as a system vulnerability. This solution reduces the computational load and improves analysis efficiency in the final vulnerability analysis by identifying the starting analysis position in the call relationship graph.

The application provides an embedding generation method and device of a binary function, electronic equipment and a medium, and relates to the technical field of computers. The method comprises the following steps: inputting a target binary function into a pre-trained control flow semantic learning model to obtain a control flow semantic embedding, wherein the control flow semantic learning model is used for converting a relationship control flow graph corresponding to the binary function into a vector and outputting; inputting the target binary function into a pre-trained global sequential semantic learning model to obtain a global sequential semantic embedding, wherein the global sequential semantic learning model is used for converting machine code corresponding to the binary function into a vector and outputting; and integrating the control flow semantic embedding and the global sequential semantic embedding, and taking the integration result as an embedding corresponding to the target binary function. The scheme of the application can make the embedding of the binary function retain code information to the greatest extent, has good generalization performance, and improves the quality of the binary function embedding.