CN113869789A

CN113869789A - Risk monitoring method and device, computer equipment and storage medium

Info

Publication number: CN113869789A
Application number: CN202111217318.1A
Authority: CN
Inventors: 吴智炜
Original assignee: Ping An Life Insurance Company of China Ltd
Current assignee: Ping An Life Insurance Company of China Ltd
Priority date: 2021-10-19
Filing date: 2021-10-19
Publication date: 2021-12-31

Abstract

The application discloses a risk monitoring method and device, computer equipment and a storage medium, and belongs to the technical field of network pedestal operation and maintenance. According to the method, keyword extraction is carried out on a development requirement document to obtain a risk keyword, a risk code corresponding to the risk keyword is determined, a detection code is generated, the detection code is inserted into a program code, a test code is generated, the test code is operated, a generated log file and a thread record file are obtained, a realization thread of the test code is obtained from the thread record file, a call stack of the realization thread is searched from the log file, a non-operating system function is searched from the call stack, and the risk condition of the program code is determined based on the output result of the non-operating system function. In addition, the application also relates to a block chain technology, and the development requirement document can be stored in the block chain. The method and the device have the advantages that the risk of the program codes is automatically judged, the workload of testing personnel is reduced, and meanwhile, the code risk detection precision is improved.

Description

Risk monitoring method and device, computer equipment and storage medium

Technical Field

The application belongs to the technical field of network pedestal operation and maintenance, and particularly relates to a risk monitoring method and device, computer equipment and a storage medium.

Background

With the popularization of the internet era, the technological capability becomes one of the standards for measuring the potential of a company, and how to create value by using the IT technology is the core competitiveness of an enterprise. For users, the most direct experience is the system experience of the used science and technology products, and today with ever changing business opportunities, the system is updated more frequently in an iterative manner, so that how an enterprise ensures the safety and stability of each iterative version and ensures the user experience in the version iteration process is a direction of major attention of developers.

At present, risk monitoring of an iterative update process of system versions is generally achieved through artificial detection, for example, business analysts verify content required and developed by each version and evaluate related function modules; and then technical research personnel check system release items for each version, such as: system configuration, automatic file deployment, whether the file passes the test, and the like; and finally, the operator confirms whether to fill in the emergency contact, whether to perform safety scanning and the like. The existing risk monitoring of the system version iteration updating process is realized through manual detection, a large amount of repeated work exists, a large amount of manpower is consumed, and omission is hardly guaranteed.

Disclosure of Invention

An object of the embodiments of the present application is to provide a risk monitoring method, apparatus, computer device, and storage medium, so as to solve the technical problems of excessive human resource consumption and low detection accuracy in the existing risk monitoring scheme.

In order to solve the above technical problem, an embodiment of the present application provides a method for risk monitoring, which adopts the following technical solutions:

a method of risk monitoring, comprising:

receiving a risk monitoring instruction, and acquiring a development requirement document corresponding to a program code;

extracting keywords from the development requirement document to obtain risk keywords, and determining risk codes corresponding to the risk keywords in the program codes;

generating a detection code corresponding to the risk code, inserting the detection code into the program code, and generating a test code;

running the test code in the preset operating system, and acquiring a log file and a thread record file of the operating system;

acquiring the implementation thread of the test code from the thread record file, and searching the call stack of the implementation thread from the log file;

and searching a non-operating system function in the call stack, acquiring an output result of the non-operating system function, and determining the risk condition of the program code based on the output result.

Further, the step of extracting keywords from the development requirement document to obtain risk keywords and determining risk codes corresponding to the risk keywords in the program codes specifically includes:

performing word segmentation processing on the development requirement document to obtain text word segmentation;

preprocessing the text participles to remove stop words in the text participles;

determining risk keywords in the text participles after preprocessing based on a preset keyword extraction algorithm;

and searching code segments corresponding to the risk keywords in the program codes to obtain the risk codes.

Further, the step of generating a detection code corresponding to the risk code, inserting the detection code into the program code, and generating a test code specifically includes:

determining the type of the risk code according to the risk keyword;

generating a detection code corresponding to the risk code based on the type of the risk code;

and inserting the detection code into a preset position in the program code to generate a test code.

Further, the step of inserting the detection code into a predetermined position in the program code to generate a test code specifically includes:

creating a new thread in the program code, and searching a monitoring function position in the program code;

associating the new thread, the monitoring function location, and the risk code;

and adding the detection code into the new thread and the monitoring function position respectively to generate the test code.

Further, the step of running the test code in the preset operating system and acquiring the log file and the thread record file of the operating system specifically includes:

importing the test code into the operating system, compiling and running the test code in the operating system;

responding to a first trigger operation, determining an implementation thread corresponding to the test code, and storing the implementation thread in the thread record file, wherein the first trigger operation is the trigger operation of the new thread in the running process of the test code;

and responding to a second trigger operation, generating a call stack of the implementation thread, and storing the call stack of the implementation thread in the log file, wherein the second trigger operation is the trigger operation of the monitoring function position in the running process of the test code.

Further, the step of searching for a non-operating system function in the call stack and obtaining an output result of the non-operating system function specifically includes:

sequencing all functions of the call stack according to the function call sequence;

sequentially identifying the function names of the functions in the call stack according to the sequence from the stack bottom to the stack top so as to determine the non-operating system functions in the call stack;

and acquiring the output result of the non-operating system function from the log file.

Further, the step of determining the risk condition of the program code based on the output result specifically includes:

determining a standard output result corresponding to the risk keyword in the development requirement document;

comparing the output result of the non-operating system function with the standard output result;

if the output result of the non-operating system function is consistent with the standard output result, determining that the program code has no safety risk;

and if the output result of the non-operating system function does not accord with the standard output result, determining that the program code has safety risk.

In order to solve the above technical problem, an embodiment of the present application further provides an apparatus, which adopts the following technical solution:

an apparatus for risk monitoring, comprising:

the system comprises a document acquisition module, a risk monitoring module and a risk monitoring module, wherein the document acquisition module is used for receiving a risk monitoring instruction and acquiring a development requirement document corresponding to a program code;

the keyword extraction module is used for extracting keywords from the development requirement document to obtain risk keywords and determining risk codes corresponding to the risk keywords in the program codes;

the code generation module is used for generating a detection code corresponding to the risk code, inserting the detection code into the program code and generating a test code;

the code testing module is used for running the testing code in the preset operating system and acquiring a log file and a thread record file of the operating system;

the thread calling module is used for acquiring the implementation thread of the test code from the thread record file and searching the calling stack of the implementation thread from the log file;

and the risk monitoring module is used for searching a non-operating system function in the call stack, acquiring an output result of the non-operating system function and determining the risk condition of the program code based on the output result.

In order to solve the above technical problem, an embodiment of the present application further provides a computer device, which adopts the following technical solutions:

a computer device comprising a memory having stored therein computer readable instructions, and a processor implementing the steps of the method of risk monitoring as described above when executing the computer readable instructions.

In order to solve the above technical problem, an embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solutions:

a computer readable storage medium having computer readable instructions stored thereon which, when executed by a processor, implement the steps of a method of risk monitoring as described above.

Compared with the prior art, the embodiment of the application mainly has the following beneficial effects:

the application discloses a risk monitoring method and device, computer equipment and a storage medium, and belongs to the technical field of network pedestal operation and maintenance. When the method is used for carrying out risk detection on the program code in the iterative updating process of the system version, a development requirement document is analyzed to obtain a risk keyword, the risk code possibly having risk factors corresponding to the risk keyword is determined, a corresponding test code is configured for the risk code to generate a test code, the test code is operated in an operating system, an implementation thread is obtained from a thread record file obtained by testing, a call stack of the implementation thread is searched from a log file obtained by testing, a non-operating system function is searched in the call stack, an output result of the non-operating system function is obtained, and finally the output result of the non-operating system function is compared with a standard output result in the development requirement document to judge whether the program code has risk. According to the method and the device, the risk keywords are extracted and determined from the keywords, the risk codes in the program codes are determined through the risk keywords, so that the test codes are configured for the risk codes, and after the operation of the test codes is completed by the operating system, whether the program codes have risks or not is automatically judged through the output result of the non-operating system function in the test result, the workload of testers is reduced, and meanwhile, the code risk detection precision is improved.

Drawings

In order to more clearly illustrate the solution of the present application, the drawings needed for describing the embodiments of the present application will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and that other drawings can be obtained by those skilled in the art without inventive effort.

FIG. 1 illustrates an exemplary system architecture diagram in which the present application may be applied;

FIG. 2 illustrates a flow diagram of one embodiment of a method of risk monitoring according to the present application;

FIG. 3 illustrates a schematic structural diagram of one embodiment of an apparatus for risk monitoring according to the present application;

FIG. 4 shows a schematic block diagram of one embodiment of a computer device according to the present application.

Detailed Description

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "including" and "having," and any variations thereof, in the description and claims of this application and the description of the above figures are intended to cover non-exclusive inclusions. The terms "first," "second," and the like in the description and claims of this application or in the above-described drawings are used for distinguishing between different objects and not for describing a particular order.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

As shown in fig. 1, the system architecture 100 may include

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

The user may use the

terminal devices

101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The

terminal devices

101, 102, 103 may have various communication client applications installed thereon, such as a web browser application, a shopping application, a search application, an instant messaging tool, a mailbox client, social platform software, and the like.

The

terminal devices

101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture experts Group Audio Layer III, mpeg compression standard Audio Layer 3), MP4 players (Moving Picture experts Group Audio Layer iv, mpeg compression standard Audio Layer 4), laptop portable computers, desktop computers, and the like.

The server 105 may be a server that provides various services, for example, a background server that provides support for pages displayed on the

terminal devices

101, 102, and 103, and may be an independent server, or a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a web service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), and a big data and artificial intelligence platform.

It should be noted that the method for risk monitoring provided in the embodiments of the present application is generally performed by a server, and accordingly, a device for risk monitoring is generally disposed in the server.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

With continued reference to FIG. 2, a flow diagram of one embodiment of a method of risk monitoring in accordance with the present application is shown. The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.

The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like. The risk monitoring method comprises the following steps:

s201, receiving a risk monitoring instruction, and acquiring a development requirement document corresponding to a program code.

Before each product development task, a product manager needs to enter a development requirement document in advance, then developers develop products according to the development requirement document entered by the product manager to obtain program codes corresponding to the products, and finally the developers give the developed program codes to testers for product testing. The product requirement document is an instruction document which is generated by describing the business requirement document and the market requirement document in a professional language and guides product development. The product requirement document contains the strategy and tactics of the product, such as product positioning, target market, target user, competitor, product structure, core business process, specific use case description, function & content description, result description and the like.

In this embodiment, the electronic device (for example, the server/terminal device shown in fig. 1) on which the risk monitoring method operates may receive the risk monitoring instruction through a wired connection manner or a wireless connection manner. It should be noted that the wireless connection means may include, but is not limited to, a 3G/4G connection, a WiFi connection, a bluetooth connection, a WiMAX connection, a Zigbee connection, a uwb (ultra wideband) connection, and other wireless connection means now known or developed in the future.

Specifically, in the application, a developer develops a product according to a development requirement document input by a product manager, and after a program code is obtained, a server receives a risk monitoring instruction input by a user and obtains the development requirement document corresponding to the program code.

S202, extracting keywords from the development requirement document to obtain risk keywords, and determining risk codes corresponding to the risk keywords in the program codes.

Specifically, after acquiring a development requirement document corresponding to the program code, the server extracts keywords from the development requirement document based on a preset keyword extraction algorithm to obtain risk keywords, and determines risk codes corresponding to the risk keywords in the program code.

For example, in a specific embodiment of the present application, there is an operation step of acquiring the user privacy information (contact phone, address, identification number, etc.) in the core business process of developing the requirement document, sensitive information of a user can be leaked in the using process of the program, a product manager needs to perform desensitization processing when writing a development requirement document to indicate that the operation step is realized, and a developer needs to perform program development, a corresponding desensitization scheme is added to the operation step in the program code, and the code segment corresponding to the operation step belongs to the risk code, when the keyword extraction is carried out on the labeled description information of the operation steps, the risk keywords of 'user', 'privacy', 'desensitization', etc. can be obtained, and then searching a development document to obtain a code segment corresponding to the risk keyword to obtain a risk code.

S203, generating a detection code corresponding to the risk code, inserting the detection code into the program code, and generating a test code.

Specifically, the server generates the detection code according to the type of the operation step corresponding to the risk code. For example, in the above embodiment, the operation step corresponding to the risk code is private information entry and private information desensitization, and the generated detection code type is used for detecting whether leakage risk exists in the private information and the desensitization information. After the server generates the test code, the detection code is inserted into a preset position in the program code to generate the test code.

And S204, running the test code in the preset operating system, and acquiring a log file and a thread record file of the operating system.

Specifically, after the test code is imported into the operating system, the server compiles and runs the test code in the operating system, responds to user operation in the running process of the test code, and acquires a log file and a thread record file of the operating system after the running of the test code is finished. The log file records event records of the operating system in the testing process, and the thread record file records the calling relationship among threads of the operating system in the testing process.

In a specific embodiment of the present application, the operating system may be an iOS operating system or an android operating system, or another operating system that can run the test code, and after the test code is installed in the operating system, the test code is normally run in the operating system to detect whether a risk code exists in the test code. In order to record suspicious operation information of the test code during the process of running the test code in the operating system, the detection code may be added in advance to a code segment in which risks may exist in the test code.

S205, obtaining the implementation thread of the test code from the thread record file, and searching the call stack of the implementation thread from the log file.

Specifically, after completing the code test, the server calls the thread record file and the log file, obtains the implementation thread of the test code from the thread record file, and searches the call stack of the implementation thread from the log file. Among them, the call stack, also called the execution stack, has a LIFO (Last in, First out Last in) structure for storing all execution contexts created during the execution of the code. When the server engine first reads the test code, it creates a global execution context and pushes it onto the current execution stack. Whenever a function call occurs to the execution stack, the server engine creates a new execution context for the function and pushes to the top of the current execution stack. The server engine will run the function of the execution context at the top of the execution stack, according to the LIFO rule, after the function is finished, the corresponding execution context will be Pop out from the execution stack, and the context control right will be transferred to the next execution context of the current execution stack.

S206, searching a non-operating system function in the call stack, obtaining an output result of the non-operating system function, and determining the risk condition of the program code based on the output result.

Specifically, after searching a call stack for realizing a thread, a server traverses system functions in the call stack and acquires non-operating system functions therein, wherein the non-operating system functions refer to functions for realizing program code functions in the system functions, the non-operating system functions are searched one by one from the functions from the bottom of the stack to the top of the stack according to a function call sequence, then output results of each non-operating system function are searched in a log file, and the risk condition of the program code is determined based on the output results of the non-operating system functions and standard output results recorded in a development requirement document.

In this embodiment, when the program code of the iterative update process of the system version is subjected to risk detection, a development requirement document is analyzed to obtain a risk keyword, a risk code which is possibly associated with a risk factor and corresponds to the risk keyword is determined, a corresponding test code is configured for the risk code to generate a test code, the test code is run in an operating system, an implementation thread is obtained from a thread record file obtained through testing, a call stack of the implementation thread is searched from a log file obtained through testing, a non-operating system function is searched in the call stack, an output result of the non-operating system function is obtained, and finally the output result of the non-operating system function is compared with a standard output result in the development requirement document to judge whether the program code has a risk. According to the method and the device, the risk keywords are extracted and determined from the keywords, the risk codes in the program codes are determined through the risk keywords, so that the test codes are configured for the risk codes, and after the operation of the test codes is completed by the operating system, whether the program codes have risks or not is automatically judged through the output result of the non-operating system function in the test result, the workload of testers is reduced, and meanwhile, the code risk detection precision is improved.

Specifically, in general, the development requirement document is a text document. The method comprises the steps that after a server obtains a development requirement document, word segmentation processing is carried out on the development requirement document to obtain text word segmentation, preprocessing is carried out on the text word segmentation, the preprocessing comprises stop word removing processing so as to remove stop words in the text word segmentation, risk keywords in the text word segmentation after the stop words are removed are determined based on a preset keyword extraction algorithm, and finally code segments corresponding to the risk keywords are searched in program codes to obtain risk codes.

The preset keyword extraction algorithm may be any one of an LDA topic model keyword extraction algorithm, a TF-IDF keyword extraction algorithm, or a TextRank keyword extraction algorithm, and the application is not specifically limited.

In this embodiment, the risk keywords in the development requirement document are extracted through a preset keyword extraction algorithm, so that risk codes corresponding to the risk keywords are searched in the program codes.

determining the type of the risk code according to the risk keyword;

Specifically, the server performs semantic analysis on the risk keywords, determines the type of the risk codes based on the semantic analysis result of the risk keywords, generates detection codes corresponding to the risk codes based on the type of the risk codes, and finally inserts the detection codes into preset positions in the program codes to generate the test codes.

In a specific embodiment of the application, if the operation step corresponding to the risk code is private information entry and private information desensitization, the type of the generated detection code is used for detecting whether risks exist in the private data and the desensitization data; if the operation steps corresponding to the risk codes are video recording and video encryption, the generated detection codes are used for detecting whether risks exist in the video recording and the encrypted video recording.

In this embodiment, the type to which the risk code belongs is obtained through semantic analysis, so as to generate a corresponding detection code for the risk code.

Specifically, the server traverses the current thread of the program code, creates a new thread on the current thread of the program code, adds the detection code into the new thread, and simultaneously searches the monitoring function position in the program code and adds the detection code into the monitoring function position, wherein the monitoring function position is one of the self-carried function positions on the program code development basic framework, and is used for realizing the function monitoring of the program code, and the monitoring function position can be freely configured by a user, for example, the detection code for detecting the function of the program code can be inserted into the monitoring function position. After the server creates a new thread and searches for a monitoring function position, the new thread, the monitoring function position and a corresponding risk code are associated, and a detection code is added to the new thread and the monitoring function position respectively to generate a test code.

In the above embodiment, the present application implements monitoring of the risk code by creating a new thread on a current thread of the program code, searching for a monitoring function position in the program code, associating the monitoring function position with the risk code, and then adding the detection code generated in the previous step to the new thread and the monitoring function position, respectively.

Specifically, the server imports the test code into a preset operating system, and compiles and runs the test code in the operating system. In the running process of the test code, the server responds to a first trigger operation, determines an implementation thread corresponding to the test code, and stores the implementation thread into a thread record file, wherein the first trigger operation is the trigger operation of a new thread in the running process of the test code. Meanwhile, in the running process of the test code, the server responds to a second trigger operation to generate a call stack of the implementation thread and stores the call stack of the implementation thread into a log file, wherein the second trigger operation is the trigger operation of monitoring the functional position in the running process of the test code. It should be noted that, in the running process of the test code, each time the operating system calls the risk code, the operating system responds to a first trigger operation and a second trigger operation respectively.

In the above embodiment, the test code is compiled and run in the operating system to obtain the implementation thread and the call stack of the test code, and meanwhile, the implementation thread and the call stack of the test code are recorded in the running process of the test code, so that risk assessment of the risk code is performed subsequently.

Specifically, the server sorts all functions of the call stack according to the function call order, generally according to the principle of last-in first-out. And then the server sequentially identifies the function names of the functions in the call stack according to the sequence from the bottom of the stack to the top of the stack so as to determine the non-operating system functions in the call stack, wherein the functions in the call stack comprise the operating system functions and the non-operating system functions. And finally, the server acquires the output results of the non-operating system functions from the log file, wherein the log file records event records of the operating system in the test process, and the event records also comprise the output results corresponding to the functions.

Specifically, the server determines a standard output result corresponding to the risk keyword in the development requirement document, compares the output result of the non-operating system function with the standard output result, and determines that the program code has no safety risk if the output result of the non-operating system function is consistent with the standard output result; and if the output result of the non-operating system function is not consistent with the standard output result, determining that the program code has a safety risk, and outputting risk prompt information.

The application discloses a risk monitoring method, and belongs to the technical field of network pedestal operation and maintenance. When the method is used for carrying out risk detection on the program code in the iterative updating process of the system version, a development requirement document is analyzed to obtain a risk keyword, the risk code possibly having risk factors corresponding to the risk keyword is determined, a corresponding test code is configured for the risk code to generate a test code, the test code is operated in an operating system, an implementation thread is obtained from a thread record file obtained by testing, a call stack of the implementation thread is searched from a log file obtained by testing, a non-operating system function is searched in the call stack, an output result of the non-operating system function is obtained, and finally the output result of the non-operating system function is compared with a standard output result in the development requirement document to judge whether the program code has risk. According to the method and the device, the risk keywords are extracted and determined from the keywords, the risk codes in the program codes are determined through the risk keywords, so that the test codes are configured for the risk codes, and after the operation of the test codes is completed by the operating system, whether the program codes have risks or not is automatically judged through the output result of the non-operating system function in the test result, the workload of testers is reduced, and meanwhile, the code risk detection precision is improved.

It is emphasized that, in order to further ensure the privacy and security of the development requirement document, the development requirement document may also be stored in a node of a block chain.

The block chain referred by the application is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware associated with computer readable instructions, which can be stored in a computer readable storage medium, and when executed, can include processes of the embodiments of the methods described above. The storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a Random Access Memory (RAM).

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

With further reference to fig. 3, as an implementation of the method shown in fig. 2, the present application provides an embodiment of a risk monitoring apparatus, which corresponds to the embodiment of the method shown in fig. 2, and which can be applied in various electronic devices.

As shown in fig. 3, the risk monitoring apparatus according to this embodiment includes:

the document acquisition module 301 is configured to receive a risk monitoring instruction and acquire a development requirement document corresponding to a program code;

a keyword extraction module 302, configured to perform keyword extraction on the development requirement document to obtain a risk keyword, and determine a risk code corresponding to the risk keyword in the program code;

a code generating module 303, configured to generate a detection code corresponding to the risk code, and insert the detection code into the program code to generate a test code;

a code testing module 304, configured to run the test code in the preset operating system, and obtain a log file and a thread record file of the operating system;

a thread calling module 305, configured to obtain an implementation thread of the test code from the thread record file, and search a call stack of the implementation thread from the log file;

a risk monitoring module 306, configured to search a non-operating system function in the call stack, obtain an output result of the non-operating system function, and determine a risk condition of the program code based on the output result.

Further, the keyword extraction module 302 specifically includes:

the word segmentation processing unit is used for carrying out word segmentation processing on the development requirement document to obtain text word segmentation;

the preprocessing unit is used for preprocessing the text participles to remove stop words in the text participles;

the keyword extraction unit is used for determining risk keywords in the text participles after preprocessing based on a preset keyword extraction algorithm;

and the code searching unit is used for searching a code segment corresponding to the risk keyword in the program code to obtain the risk code.

Further, the code generating module 303 specifically includes:

the type distinguishing unit is used for determining the type of the risk code according to the risk key words;

the code generating unit is used for generating a detection code corresponding to the risk code based on the type of the risk code;

and the code inserting unit is used for inserting the detection code into a preset position in the program code to generate a test code.

Further, the code insertion unit specifically includes:

the searching and creating subunit is used for creating a new thread in the program code and searching a monitoring function position in the program code;

a code association subunit, configured to associate the new thread, the monitor function location, and the risk code;

and the code inserting subunit is used for respectively adding the detection code into the new thread and the monitoring function position to generate the test code.

Further, the code testing module 304 specifically includes:

the compiling and running unit is used for importing the test codes into the operating system, compiling and running the test codes in the operating system;

a first response unit, configured to determine, in response to a first trigger operation, an implementation thread corresponding to the test code, and store the implementation thread in the thread record file, where the first trigger operation is a trigger operation of the new thread in a running process of the test code;

and the second response unit is used for responding to a second trigger operation, generating a call stack of the implementation thread, and storing the call stack of the implementation thread in the log file, wherein the second trigger operation is the trigger operation of the monitoring function position in the running process of the test code.

Further, the risk monitoring module 306 specifically includes:

the function sorting unit is used for sorting all functions of the call stack according to the function call sequence;

the function name identification unit is used for sequentially identifying the function names of the functions in the call stack according to the sequence from the stack bottom to the stack top so as to determine the non-operating system functions in the call stack;

a first output result obtaining unit, configured to obtain an output result of the non-operating system function from the log file.

Further, the risk monitoring module 306 further comprises:

the second output result acquisition unit is used for determining a standard output result corresponding to the risk keyword in the development requirement document;

the output result comparison unit is used for comparing the output result of the non-operating system function with the standard output result;

the first comparison result unit is used for determining that the program code has no safety risk when the output result of the non-operating system function is consistent with the standard output result;

and the second comparison result unit is used for determining that the program code has safety risk when the output result of the non-operating system function is not consistent with the standard output result.

The application discloses device of risk monitoring belongs to network bed frame fortune dimension technical field. When the method is used for carrying out risk detection on the program code in the iterative updating process of the system version, a development requirement document is analyzed to obtain a risk keyword, the risk code possibly having risk factors corresponding to the risk keyword is determined, a corresponding test code is configured for the risk code to generate a test code, the test code is operated in an operating system, an implementation thread is obtained from a thread record file obtained by testing, a call stack of the implementation thread is searched from a log file obtained by testing, a non-operating system function is searched in the call stack, an output result of the non-operating system function is obtained, and finally the output result of the non-operating system function is compared with a standard output result in the development requirement document to judge whether the program code has risk. According to the method and the device, the risk keywords are extracted and determined from the keywords, the risk codes in the program codes are determined through the risk keywords, so that the test codes are configured for the risk codes, and after the operation of the test codes is completed by the operating system, whether the program codes have risks or not is automatically judged through the output result of the non-operating system function in the test result, the workload of testers is reduced, and meanwhile, the code risk detection precision is improved.

In order to solve the technical problem, an embodiment of the present application further provides a computer device. Referring to fig. 4, fig. 4 is a block diagram of a basic structure of a computer device according to the present embodiment.

The computer device 4 comprises a memory 41, a processor 42, a network interface 43 communicatively connected to each other via a system bus. It is noted that only computer device 4 having components 41-43 is shown, but it is understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead. As will be understood by those skilled in the art, the computer device is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and the hardware includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.

The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer equipment can carry out man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch panel or voice control equipment and the like.

The memory 41 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the computer device 4. Of course, the memory 41 may also include both internal and external storage devices of the computer device 4. In this embodiment, the memory 41 is generally used for storing an operating system installed in the computer device 4 and various application software, such as computer readable instructions of a risk monitoring method. Further, the memory 41 may also be used to temporarily store various types of data that have been output or are to be output.

The processor 42 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is configured to execute computer readable instructions stored in the memory 41 or process data, such as computer readable instructions for executing the risk monitoring method.

The network interface 43 may comprise a wireless network interface or a wired network interface, and the network interface 43 is generally used for establishing communication connection between the computer device 4 and other electronic devices.

The application discloses computer equipment belongs to network bed frame fortune dimension technical field. When the method is used for carrying out risk detection on the program code in the iterative updating process of the system version, a development requirement document is analyzed to obtain a risk keyword, the risk code possibly having risk factors corresponding to the risk keyword is determined, a corresponding test code is configured for the risk code to generate a test code, the test code is operated in an operating system, an implementation thread is obtained from a thread record file obtained by testing, a call stack of the implementation thread is searched from a log file obtained by testing, a non-operating system function is searched in the call stack, an output result of the non-operating system function is obtained, and finally the output result of the non-operating system function is compared with a standard output result in the development requirement document to judge whether the program code has risk. According to the method and the device, the risk keywords are extracted and determined from the keywords, the risk codes in the program codes are determined through the risk keywords, so that the test codes are configured for the risk codes, and after the operation of the test codes is completed by the operating system, whether the program codes have risks or not is automatically judged through the output result of the non-operating system function in the test result, the workload of testers is reduced, and meanwhile, the code risk detection precision is improved.

The present application provides yet another embodiment, which provides a computer-readable storage medium having stored thereon computer-readable instructions executable by at least one processor to cause the at least one processor to perform the steps of the method of risk monitoring as described above.

The application discloses a storage medium, and belongs to the technical field of network pedestal operation and maintenance. When the method is used for carrying out risk detection on the program code in the iterative updating process of the system version, a development requirement document is analyzed to obtain a risk keyword, the risk code possibly having risk factors corresponding to the risk keyword is determined, a corresponding test code is configured for the risk code to generate a test code, the test code is operated in an operating system, an implementation thread is obtained from a thread record file obtained by testing, a call stack of the implementation thread is searched from a log file obtained by testing, a non-operating system function is searched in the call stack, an output result of the non-operating system function is obtained, and finally the output result of the non-operating system function is compared with a standard output result in the development requirement document to judge whether the program code has risk. According to the method and the device, the risk keywords are extracted and determined from the keywords, the risk codes in the program codes are determined through the risk keywords, so that the test codes are configured for the risk codes, and after the operation of the test codes is completed by the operating system, whether the program codes have risks or not is automatically judged through the output result of the non-operating system function in the test result, the workload of testers is reduced, and meanwhile, the code risk detection precision is improved.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.

The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

It is to be understood that the above-described embodiments are merely illustrative of some, but not restrictive, of the broad invention, and that the appended drawings illustrate preferred embodiments of the invention and do not limit the scope of the invention. This application is capable of embodiments in many different forms and is provided for the purpose of enabling a thorough understanding of the disclosure of the application. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to one skilled in the art that the present application may be practiced without modification or with equivalents of some of the features described in the foregoing embodiments. All equivalent structures made by using the contents of the specification and the drawings of the present application are directly or indirectly applied to other related technical fields and are within the protection scope of the present application.

Claims

1. A method of risk monitoring, comprising:

2. The risk monitoring method according to claim 1, wherein the step of extracting keywords from the development requirement document to obtain risk keywords and determining risk codes corresponding to the risk keywords in the program codes specifically comprises:

3. The risk monitoring method according to claim 1, wherein the step of generating a detection code corresponding to the risk code, inserting the detection code into the program code, and generating a test code specifically includes:

determining the type of the risk code according to the risk keyword;

4. The risk monitoring method according to claim 3, wherein the step of inserting the detection code into a predetermined location in the program code to generate a test code specifically comprises:

5. The risk monitoring method according to claim 1, wherein the step of running the test code in the preset operating system and obtaining a log file and a thread record file of the operating system specifically includes:

6. The risk monitoring method according to any one of claims 1 to 5, wherein the step of searching for a non-operating system function in the call stack and obtaining an output result of the non-operating system function specifically comprises:

7. The risk monitoring method according to claim 6, wherein the step of determining the risk profile of the program code based on the output result specifically comprises:

8. An apparatus for risk monitoring, comprising:

9. A computer device comprising a memory having computer readable instructions stored therein and a processor which when executed implements the steps of the method of risk monitoring of any one of claims 1 to 7.

10. A computer-readable storage medium, having computer-readable instructions stored thereon, which, when executed by a processor, implement the steps of the method of risk monitoring of any of claims 1 to 7.