42 results about "Control flow diagram" patented technology

The invention discloses a multi-language code generation method based on self-supervised pre-training, which comprises the following steps: acquiring and cleaning multi-language code data to form a training corpus; the method comprises the following steps: representing code data as an abstract syntax tree, extracting a control flow diagram and a data flow diagram of the code data, and obtaining unified semantic representation through combination of a diagram encoder and a sequence encoder; designing a self-supervised pre-training task, and pre-training the semantic representation based on the training corpus; constructing a multi-language pre-training model based on the structure-improved recurrent neural tensor network and the multi-language embedding matrix; when a user inputs a natural language, generating a target language code by using the multi-language pre-training model; and target language code correction is carried out through conventional function testing and grammar checking. According to the method, multi-channel recursive combination and a hierarchical recursive expansion mechanism are combined with self-supervised pre-training, so that accurate generation and performability improvement of cross-language codes are realized.

The invention relates to an application user tracking detection method and device based on a dynamic and static combination technology, and the method comprises the steps: obtaining a first interprocess control flow diagram associated with a device identifier according to an application package of a target application and a configuration file containing a predefined device identifier; according to a program behavior of a target application in a running state, determining a function associated with an application programming interface of the equipment identifier and an application programming interface of network data transmission, and obtaining a second interprocess control flow diagram of data leakage according to the function; integrating the first interprocess control flow diagram and the second interprocess control flow diagram to obtain a third interprocess control flow diagram; and obtaining a leakage path of the target application to the user data according to the third interprocess control flow diagram. By adopting the method, the problems of narrow detection coverage and low detection accuracy in the aspect of tracking the user by using the device identifier through the APP can be solved.

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 static binary code taint analysis method based on a propagation action scope, and relates to the field of static binary code taint analysis, and the static binary code taint analysis method comprises the following steps: extracting a program instruction set and a control flow structure based on a disassembling result of a target binary code; calculating a value set with a source of the binary code based on the control flow graph; on the basis of the control flow diagram and the value set with the source, executing cross-function stain propagation analysis, and identifying memory positions or registers influenced by pollution in each function and propagation action ranges of the memory positions or the registers; and extracting all instruction sets using the taint data based on the taint and the propagation action range thereof. According to the method, the false alarm rate of static binary taint analysis can be reduced and the instruction set involved in the taint analysis can be reduced without increasing the analysis overhead, so that the method has important significance in improving the instrumentation efficiency and the operation efficiency of dynamic taint analysis and improving the accuracy of protocol reversion, fuzzy testing and vulnerability mining based on the taint analysis.

The invention discloses a code conversion method and a related device, and the method comprises the steps: obtaining an input code, carrying out the grammatical analysis of the input code, and generating an abstract syntax tree which comprises a plurality of nodes; coding a code text in the input code to generate a first semantic vector; encoding the structure in the abstract syntax tree to generate a second semantic vector; processing the first semantic vector, and converting the first semantic vector into a second semantic vector; generating a control flow diagram according to the abstract syntax tree, and constructing a data flow diagram; determining a plurality of semantic units according to the control flow diagram and the data flow diagram; obtaining a preset domain knowledge graph, wherein the preset domain knowledge graph comprises a plurality of concept nodes; according to the concept nodes and the semantic units, analyzing the second semantic vector to obtain a target semantic vector, decoding the target semantic vector into a target language, and generating a target code. By adopting the method and the device, code conversion expansibility and accuracy can be improved.

The embodiment of the invention provides a program problem static analysis method and device, electronic equipment, a readable storage medium and a program product, and relates to the technical field of program static analysis. The method comprises the steps that a target program is analyzed based on a rule constraint set of target syntax, and an abstract syntax tree is generated; constructing an annotation control flow graph according to the abstract syntax tree; according to the annotation control flow diagram, identifying a periodic task in the target program; and on the basis of performing loop expansion on the execution process of the periodic task, performing symbolic execution analysis on the annotation control flow diagram, and identifying the cross-period conflict problem of the periodic task. By identifying the periodic task and circularly expanding the periodic task, the analysis limitation on the program problem in the related technology is solved, the cross-period conflict problem in the program is efficiently identified, and the static guarantee capability on the program quality is improved.

In various examples, static single assignment-based control flow graph traversal analysis for uninitialized variable detection system and methods are disclosed. A pre-compiler stage of a compiler system, may reconstruct source code into an SSA form IR and detect and identify uninitialized variables based on applying a variable analysis pass that traverses a CFG corresponding to the SSA form IR. A variable analysis pass may traverse through the CFG to build a defined variable map and a Phi variable map. The maps may be used to map undefined variables to basic blocks of the CFG where the undefined variables occur. The variable analysis pass may pass uninitialized variable data to a compiler error handling process. The compiler error handling process may produce an error report that traces the basic block with undefined variables to lines of the source code to assist in efficiently debugging the source code.

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 invention relates to the technical field of computers, and discloses a method, a device, equipment and a medium for multi-thread undefined behavior detection, and the method comprises the following steps: constructing a control flow diagram and a data flow diagram based on a multi-thread program code, and creating a multi-thread execution path model based on the control flow diagram and the data flow diagram; distributing a thread fragment data set in the multi-thread execution path model to a plurality of computing nodes, and extracting an operation sequence in the distributed thread fragment data set in each computing node; performing iteration and layering processing on the operation sequence, and constructing a causal relationship graph; based on the causal relationship graph, generating an operation dependency track, mapping the operation dependency track to different memory models, performing execution sequence simulation to obtain a plurality of execution paths, and performing behavior analysis based on the execution paths to obtain a behavior analysis result. According to the method, the undefined behaviors in the multi-thread program can be systematically detected, and the stability and the safety of the system can be improved.

The invention discloses a lightweight program control flow obfuscation method, system and device and a medium, and the method comprises the steps: carrying out the static analysis of a program based on a program source code, recognizing all basic blocks, analyzing the execution sequence and jump relation of the basic blocks, and obtaining a control flow diagram of the program; a unique runtime state is distributed for the basic blocks by analyzing the dependency relationship among the basic blocks, and a conversion rule among the states is defined, so that a state transition model is obtained; the method comprises the following steps: dynamically generating an encryption key by using a state conversion relationship, and encrypting sensitive information in a control flow to obtain an encryption program code subjected to obfuscation protection; a current runtime state is read in a program execution process, a corresponding decryption key is generated, a plaintext address of sensitive information is restored, and executable implicit jump and variable access operation is obtained. Static analysis, especially control flow analysis, can be effectively resisted, so that source codes and algorithms of software are protected from being easily acquired or tampered.

The invention relates to the technical field of function name prediction, in particular to a function name prediction method and system based on bidirectional semantic transfer. The method comprises the following steps of: 1, acquiring a target function of a binary file, and extracting a function body and an interprocess control flow diagram of the target function; wherein the target function is a function with a function name to be predicted; step 2, inputting the function body of the target function into a preset bidirectional semantic transfer framework, and obtaining global information of the target function; wherein the bidirectional semantic transfer framework obtains a corresponding sub-function and a parent function according to the target function, obtains an internal semantic database, a sub-function semantic database and a parent function semantic database of the target function by utilizing a large language model, and performs semantic fusion as global information; and 3, taking the global information of the target function as input of the large language model, and generating a function name of the target function in combination with the cue word. According to the method, the function name prediction reasoning capability can be improved.

The invention provides a repeated vulnerability detection method based on multi-object type state analysis, and the method comprises the steps: employing a preset vulnerability mode description language, constructing a corresponding vulnerability mode description rule for each vulnerability, and the rule comprises a plurality of variable objects and program statements causing the vulnerabilities; translating the vulnerability mode description rule into a corresponding linear sequential logic formula; converting the formula into an automaton, wherein the automaton comprises an accepting state of the automaton and binding constraints of a plurality of variable objects of the environment in the accepting state; constructing an interprocess control flow diagram for the target program to be detected, wherein the interprocess control flow diagram comprises a plurality of program points; performing multivariable object analysis on the target program based on the graph to obtain an automaton state set of each program point and a data dependency relationship of a plurality of variable objects under each automaton state, and when an automaton state in an accepting state exists and the data dependency relationship of the plurality of variable objects meets the binding constraint, performing the multivariable object analysis on the target program; and detecting that a corresponding vulnerability exists in the target program.

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.

The invention provides an intelligent contract security vulnerability automatic detection and protection early warning method and system, and relates to the technical field of vulnerability detection, and the method comprises the steps: converting an intelligent contract code into an abstract syntax tree to construct a control flow diagram and a data flow diagram, extracting a function call chain and the like to construct a moving trajectory diagram, and employing a dual verification analysis technology to detect vulnerabilities. And generating a risk assessment report, and constructing a vulnerability verification network based on zero-knowledge proof. According to the invention, the vulnerability detection accuracy of the smart contract can be remarkably improved, early warning of security risks of the smart contract is realized, and safe and stable operation of a block chain system is ensured.

The invention provides a metamorphic relation identification method and device based on node and path characteristics, and the method comprises the steps: obtaining a plurality of objective functions which comprise a plurality of first functions with a target metamorphic relation and a plurality of second functions without the target metamorphic relation; analyzing the source code of each objective function to generate a corresponding control flow chart; feature extraction is conducted on the control flow chart to determine node features and path features, and the node features and the path features corresponding to the multiple target functions are combined to serve as training data; performing model training on the initial support vector machine model based on the training data to obtain a target support vector machine model; and based on the target support vector machine model, obtaining a target metamorphic relation identification result of the to-be-tested function. Therefore, the automation degree of the metamorphic test can be effectively improved, the dependence of testers on professional knowledge is greatly reduced, and meanwhile, the identification efficiency of the metamorphic relationship is improved.

The invention provides a binary program static analysis method based on a comprehensive control flow diagram. According to the scheme, the method comprises preprocessing, a control flow diagram generation module, a reverse control flow diagram generation module, target address ambiguity instruction recognition and a specific basic block path. The control flow diagram generation module obtains binary program information through preprocessing and generates a control flow diagram by using a breadth-first search algorithm. The reverse control flow diagram generation module initializes a reverse control flow diagram and generates a reverse edge by traversing the control flow diagram. A target address ambiguity instruction analysis module identifies a target address ambiguity jump or call instruction in the basic block. The specific basic block path analysis module uses a path search algorithm to obtain all paths of a specific basic block, and analyzes execution conditions of the paths through a symbolic execution technology. According to the method, the binary program can be comprehensively analyzed, the analysis efficiency and accuracy are improved, and powerful support is provided for software security and quality improvement.

The invention discloses a cross-architecture container mirror image compatibility verification method, which comprises the following steps of: receiving a container mirror image, analyzing an executable entity in the container mirror image, and constructing program representation data containing a control flow diagram and a symbol table; according to the method, by tracking the life cycle of a resource handle carrying state information in a program calling graph, a source architecture RSTG capable of describing program and kernel interaction logic is analyzed and constructed, an abstract resource state is used as a node, and system calling causing state change is used as an edge; performing mapping comparison on the source architecture RSTG and a preset target architecture RSTG rule set so as to identify an illegal state migration sequence in the target architecture and form an incompatible point set; and tracing the incompatible points, associating the incompatible points to specific code positions, and generating a report. According to the method, the compatibility verification is improved from stateless instruction comparison to stateful logic examination height, hidden compatibility defects can be found, and the verification depth and accuracy are remarkably improved.

The invention discloses a static binary code control flow diagram reconstruction method based on value set analysis, which relates to the field of static binary code analysis, and comprises the following steps: extracting a program instruction set and related data segment information based on a disassembling result of a target binary executable file; obtaining an original control flow diagram, and calculating a virtual function information set based on virtual table information; and constructing a function inner value set by using a work list algorithm, analyzing an indirect jump target address according to the value set, and reconstructing a control flow diagram. According to the method, the binary code can be comprehensively analyzed under reasonable overhead, the accuracy of indirect jump target address analysis is improved, the accuracy of the control flow diagram is ensured, and the method has important significance in improving the quality of a binary code analysis task.

The invention discloses a taint type vulnerability detection method and system oriented to a native PHP application, and belongs to the technical field of vulnerability detection. The method comprises the following steps: generating a control flow diagram of each function in a PHP program source code; the method comprises the following steps of: initializing a function call graph which does not contain any node for a PHP program source code; determining a value range of each variable in the PHP program based on the control flow graph and the initialized function call graph, and carrying out iterative updating on an initial value set analysis result and the initialized function call graph; fusing the final function call graph and the control flow graph to generate an inter-process control flow graph, and executing inter-process arrival constant value analysis based on the inter-process control flow graph and a final value set analysis result to generate a data dependency graph; and propagating the stain information along the data dependence graph, and combining the final value set analysis result to obtain a stain type vulnerability detection result of the PHP program. According to the method, the dynamic value can be accurately deduced, and potential taint type vulnerabilities in the Web application can be found as early as possible.

The invention discloses an intelligent contract vulnerability detection method and system based on multi-modal knowledge distillation, and the method comprises the steps: collecting training source code data, and obtaining byte code data, operation code data, and corresponding control flow diagram information, gray matrix and sequence embedding vector according to the training source code data; inputting the multi-modal data into a teacher model to obtain a multi-modal feature and a classification prediction probability; inputting the multi-modal features and the classification prediction probability into a preset student model to obtain a final feature vector and a classification prediction probability; constructing a total loss function, and training the student model according to the total loss function to obtain an optimal student model; and processing the target source code data to obtain multi-modal features, and inputting the multi-modal features into the optimal student model to obtain an intelligent contract vulnerability detection result. According to the method, the security of on-chain transactions is improved while the vulnerability detection performance is remarkably improved.

The invention discloses a code reuse vulnerability detection method and device based on a large model, and relates to the technical field of vulnerability detection, and the method comprises the steps: constructing an intermediate representation, a control flow diagram and a data flow diagram according to a byte code of a to-be-detected smart contract; constructing a cue based on the intermediate representation and the control flow graph, and outputting an optimized intermediate representation in response to a function boundary of the cue optimization intermediate representation through a trained LLaMA2 large model; constructing a method signature according to an operation code associated with the optimized intermediate representation, and performing signature similarity comparison on the method signature and a vulnerability sub-contract in the vulnerability contract data set to determine a code multiplexing sub-contract; and performing vulnerability detection by adopting the control flow diagram, the data flow diagram and the code reuse sub-contract, and determining a code reuse vulnerability detection result of the to-be-detected smart contract. A contract inheriting method boundary is accurately recovered through a large model, an operation code execution method level comparison assists identification of a contract reuse part, analysis can be carried out at a byte code level, and code reuse vulnerabilities can be effectively identified on the whole.

The invention discloses a register-sensitive instruction selecting and sorting method based on tree pattern matching, which is used for performing expression tree construction and optimization on instructions in a control flow diagram, and selecting and sorting the instructions in combination with a Sethi-Ullman algorithm and an iburg instruction selector. According to the method, the expression tree of the instruction is merged and optimized, so that the pressure of a register is reduced, the instruction selection and sorting efficiency is improved, and the execution performance of a program is optimized. Compared with the prior art, the method has the advantages that register resources can be utilized more effectively, register conflicts in the instruction selection and sorting process are reduced, and the execution efficiency and performance of a program are improved.

The invention provides a structured annotation enhanced vulnerability detection method based on dynamic path selection, and belongs to the field of source code vulnerability detection. Comprising the steps that 1, each code snippet is analyzed into an abstract syntax tree, and a corresponding control flow graph is constructed; 2, evaluating the importance of paths in the control flow diagram, and dynamically selecting a plurality of paths; 3, the code snippets are provided for the large language model, corresponding row-level annotations are generated for each row of codes, and the annotations are inserted into a selected path according to a predefined annotation insertion rule; and step 4, coding the annotation paths into vectors, extracting a local dependency relationship between the paths, modeling a global dependency relationship between the paths, and finally performing vulnerability detection based on fusion features. According to the model provided by the invention, a code structure and a vulnerability situation can be comprehensively understood, and more efficient and more accurate vulnerability detection is realized.

The invention discloses a binary firmware similarity analysis method and device for quantum random walk, and belongs to the technical field of computer security. According to the method, the vulnerability control flow diagram of the vulnerability binary firmware and the to-be-verified control flow diagram of the to-be-verified binary firmware are constructed, so that code characteristics of the vulnerability binary firmware and the to-be-verified binary firmware can be accurately represented through the control flow diagrams; the vulnerability control flow diagram and the to-be-verified control flow diagram are decomposed based on the number of nodes of the vulnerability control flow diagram and the number of nodes of the to-be-verified control flow diagram, so that the complexity of the vulnerability quantum random walk diagram and the to-be-verified quantum random walk diagram can be reduced, and the solving efficiency of quantum random walk is improved; through the quantum random walk algorithm, the implicit features of the binary firmware can be efficiently extracted from the quantum random walk graph to be verified and the vulnerability quantum random walk graph, the feature extraction efficiency and feature expressivity are improved, and then the efficiency of similarity analysis of the binary firmware is improved.

The invention relates to a UML (Unified Modeling Language) model-oriented event-driven behavior code automatic generation method and system. The method comprises the following steps: exporting an XMI file containing class, activity and state machines from a UML (Unified Modeling Language) modeling tool, constructing a document tree through DOM (Document Object Model) analysis, and extracting meta-model elements and relationships thereof; and generating attributes and methods of the main class and the associated class and Java source codes of the main method according to an analysis result, taking the main method of the main class as a simulation / operation entry, and calling the main method of the associated class during operation. Aiming at the behavior type of the classifier: when the behavior type is Activity, traversing an identification sequence, branching / merging, parallelizing / synchronizing and circulating from an InitialNode, constructing a behavior control flow diagram, decomposing the behavior into SimpleTask and LoopTask, and generating a Java code containing an Execute method and a scheduling statement; and when the state conversion diagram is the StateMach, reconstructing the state conversion diagram and generating a state machine instance and a StateMach Runner operation management type instance code, thereby realizing migration execution driven by a signal event and a time event and mixed triggering of the signal event and the time event and the activity. The method is suitable for the field with high requirements for model consistency and rapid verification.

The invention discloses a method and a system for identifying software components in firmware of an embedded system. The method comprises the following steps: extracting an index file from a firmware file; extracting features from each index file, wherein the features comprise a hash value, semantic information, control flow chart information and function layer feature information; comparing the feature information with a database which collects numerous known index files to obtain an index file identification result; and based on the software component corresponding to each index file identification result, obtaining a software component identification result of the firmware file.

The invention provides an XSS vulnerability detection method and system based on a high-order function abstract and taint analysis, and belongs to Web security detection and program analysis. The method comprises the steps that a to-be-detected application program is received and preprocessed, a function call graph and a control flow graph of the to-be-detected application program are generated, and a function analysis sequence is determined according to inverse topological sorting; and according to the determined function analysis sequence, performing intra-process analysis on each function, traversing a current function control flow diagram, analyzing a taint propagation condition, recording a taint propagation flow, and storing the intra-process analysis of the function in a form of an abstract of a high-order function by utilizing the characteristic that the function in the high-order function is used as a return value. Effective packaging of function stain propagation behaviors and context-sensitive instantiation are achieved through the high-order function abstract, the analysis efficiency and analysis precision of XSS vulnerability detection are remarkably improved, and the problems of missing report and false report can be effectively solved.

The application discloses a code annotation generation method and device. The application obtains the source code of a first project, compiles the source code into bytecode, generates a control flow diagram according to the bytecode, inputs the bytecode and the control flow diagram into an annotation translation model, and obtains the annotation of the source code output by the annotation translation model. According to the application, the source code of a second project is converted into bytecode and a control flow diagram, the annotation translation model is trained by using the bytecode and the control flow diagram of the second project, the annotation of the source code of the second project output by the annotation translation model is obtained, and compared with the prior art, the annotation translation model can be trained by using the training data of the second project because the bytecode of the source code of the second project and the first project has similarity. The annotation translation model obtained can be used for the first project with similar bytecode, and the learning cost of the annotation translation model is reduced.

This invention relates to a method for identifying malicious app families based on multimodal feature fusion, belonging to the field of information security technology. The method preprocesses Android APKs, including unpacking and decompiling, to obtain bytecode files and smali code files. Bytecode image features, opcode sequence features, and control flow graph features are extracted respectively. Bytecode image features are extracted using an EfficientNetV2L convolutional neural network; opcode sequence features are extracted using the k-Shingles and SimHash algorithms; and control flow graph features are extracted using static analysis tools and capsule graph neural networks. The three features are then fused using low-rank multimodal methods, and a CNN-BiLSTM-Attention detection and classification model is constructed to identify and judge malicious app families. This invention improves the accuracy of identification and enhances the model's generalization ability.

Techniques and systems described herein relate to monitoring executions of computer instructions on computing devices based on learning and generating a control flow directed graph. The techniques and systems include determining telemetry representing execution of a process on a computing system and accessing a learned control flow diagram graph for the process. A transfer of an instruction pointer is determined based on the telemetry and a validity of the transfer is determined based on the learned control flow directed graph. If invalid, then an action to terminate the process is determined, otherwise the action may be allowed to execute when valid.