50 results about "Vulnerability assessment" patented technology

The present disclosure includes techniques for performing automated vulnerability assessment. The technique includes receiving a designation associated with a Common Vulnerabilities and Exposures (CVE) and retrieving one or more attributes describing the CVE. The technique also includes aggregating, by one or more distributed data acquisition operations, CVE data associated with the CVE, wherein the one or more distributed data acquisition operations electronically capture data from a plurality of networked information sources in parallel, and generating, via a first machine learning model, a prompt data structure based on the CVE designation, the one or more attributes, and the CVE data. The technique further includes transmitting the prompt data structure to a second machine learning model that generates a vulnerability assessment, generating one or more CVE reports based on the vulnerability assessment, and performing an automated remediation action based on the one or more CVE reports.

The invention discloses a software supply chain vulnerability assessment method based on multi-Agent collaboration and dynamic hypergraph learning, which is used for opening a link between vulnerability assessment and repair and realizing full-life-cycle collaboration linkage. For the problem of vulnerability assessment and repair splitting, the method covers the core capabilities of static analysis (SAST), dynamic detection (DAST), interactive analysis (IAST), intelligence analysis and the like. Evaluation results of various agents are output through standardized vulnerability portraits, and a subsequent repair strategy is driven to be automatically generated and executed, so that whole-process closed-loop linkage and fine control of'discovery-evaluation-repair-verification 'of vulnerabilities are realized.

A method may include querying, via a processing system, a database comprising a list of cybersecurity threats associated with operational technology (OT) devices within an industrial system. The method may also include identifying OT devices associated with the list of cybersecurity threats, generating scripts configured to confirm that the OT devices are associated with at least one cybersecurity threat of the list of cybersecurity threats, and sending the scripts to the one or more OT devices. The method may then involve determining that the OT devices are associated with the at least one cybersecurity threat based on responses from the OT devices generated based on the scripts, generating instructions for resolving the at least one cybersecurity threat based on a generative artificial intelligence (AI) system, and sending the instructions to one or more devices.

This invention discloses a software vulnerability assessment method, system, and medium based on contrastive learning. The software vulnerability assessment method of this invention includes: training a feature extraction model using a contrastive learning-based training method, wherein the training method includes learning to extract feature vectors of vulnerability attributes by comparing positive and negative samples of vulnerability attributes; extracting feature vectors from the vulnerability attributes of the vulnerability to be assessed using the trained feature extraction model; and classifying the feature vectors using a vulnerability classifier to obtain the classification result of the vulnerability to be assessed. This invention aims to improve the accuracy of software vulnerability assessment by utilizing contrastive learning in the feature extraction process to obtain more effective high-dimensional vulnerability feature representations.

This invention belongs to the field of fan control technology. It provides a laboratory exhaust gas-induced high-altitude jet fan control system, comprising: a multi-source data acquisition module for real-time acquisition of multi-dimensional time-series data related to laboratory exhaust gas emission safety, including fan operating parameters, building environment parameters, exhaust gas source equipment status parameters, and meteorological environment parameters; and a predictive maintenance and early warning module based on the multi-dimensional time-series data. By integrating multi-source data perception, chronic risk trend prediction, system vulnerability assessment based on digital twins, and graded resilience control strategies, a closed loop of "perception-prediction-assessment-decision-execution" is constructed. This achieves early identification, proactive early warning, and adaptive control of coupled risks between "equipment-building-environment-personnel," thereby enhancing the proactive safety capability to prevent toxic exhaust gases from entering the breathing zone of personnel.

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.

A private network is scanned to identify devices, and profiling identified devices for vulnerabilities. A score is determined from a Common Vulnerability Scoring System (CVSS) database for each vulnerability individually that characterizes severity. A score is determined for a collection of vulnerabilities. Exponential tapering functions curb an influence of large numbers of low priority threats on the collection score. The collection threat score increases with severity of the collection of vulnerabilities.

This invention belongs to the technical field of computer network security and relates to a method and system for assessing vulnerabilities in network communication transmission nodes. The method includes: matching vulnerabilities based on static attributes of communication nodes, analyzing their exploitation prerequisites and impacts to generate an asset knowledge base; analyzing network topology and access control permissions to generate potential communication topologies; collecting information such as session connections and process activities, and encapsulating it into critical state transition events; determining whether the transition events meet the vulnerability exploitation prerequisites and updating the logical state; generating dynamic attack paths based on the updated logical state and communication topology, constructing a complete attack graph, and calculating a network-wide vulnerability risk score; simulating intervention measures for nodes with risk exposure values ​​greater than a preset threshold, and generating defense hardening strategies based on changes in the risk score. This invention addresses the problem of insufficient accuracy and timeliness in risk assessment results.

This vulnerability determination device being an example of an information processing device has: a deployment unit that deploys an attack content into a content provision device providing content via a server device having a cache function; a registration unit that registers, into a cache of the server device, the attack content deployed in the content provision device; and a determination unit that determines vulnerability to a threat which causes a browser to download the attack content via the cache of the server device.

The invention discloses an intelligent power grid vulnerability analysis method and system, and relates to the technical field of power grid analysis, and the method comprises the following steps: constructing an intelligent power grid graph structure based on a topological structure, business attributes and physical attributes of an intelligent power grid; performing graph representation learning to obtain a plurality of representation vectors of different dimensions; performing fusion, nonlinear transformation and mapping on the plurality of representation vectors to obtain a score of each node, performing descending sorting on different scores, and taking nodes corresponding to the first n scores as key nodes; different attack simulation evaluations are carried out on the key nodes, structural evaluation is carried out on the key nodes through vulnerability analysis indexes, and importance evaluation is carried out on the key nodes through service attributes; and weighting the first score, the second score and the third score to obtain a vulnerability score of the smart grid. According to the method, comprehensive analysis is carried out from multiple dimensions, and the comprehensiveness and accuracy of power grid vulnerability assessment are improved.

The invention discloses a rigid-body-like medical equipment earthquake vulnerability evaluation method considering multi-motion-state coupling, and aims to solve the problem that the earthquake vulnerability of wheeled medical equipment under the influence of factors such as strong shock, rolling, sliding-swinging coupling and non-uniform friction is difficult to accurately evaluate only depending on classic rigid body sliding or overturning criteria. Medical equipment is regarded as a rigid body, the motion state of the rigid body at each moment in the earthquake process is determined according to geometric parameters and supporting information of the rigid body, the gravitational acceleration and the earthquake oscillation time history, and the motion states comprise fixed foot support sliding, trundle rolling, swinging and sliding-swinging coupling. The maximum translation displacement and the maximum rotation angle of the rigid body are obtained based on the motion state, the damage state of the rigid body is judged according to the maximum translation displacement and the maximum rotation angle, nonlinear incremental dynamic analysis is conducted on the rigid body, an earthquake vulnerability function is obtained, the larger the median value of the earthquake vulnerability function is, the lower the earthquake vulnerability of the rigid body is, and otherwise, the higher the earthquake vulnerability of the rigid body is. The invention belongs to the field of shock resistance of medical instruments.

A computer implemented method processes vulnerabilities. A processor set identifies a vulnerability and a description of the vulnerability in a vulnerability report. The processor set extracts a set of key exploit conditions for the vulnerability from the description of the vulnerability. The processor set generates a set of different code snippets for the set of key exploit conditions. The processor set searches a set of repositories for a match between the set of components and the set of different code snippets to form a search result. The processor set identifies vulnerability assessment information relating to an applicability of the vulnerability in response to the match between the set of components and the set of different code snippets in the search result.

The application discloses a kind of information system security vulnerability risk early warning method based on big data, comprising the following steps: step S1, the index library is established to enterprise internal various levels various types of information systems, network equipment, application software, and safety related data is collected;Step S2, integrate the security intelligence on Internet and third party vulnerability database, obtain the latest security vulnerability information, and carry out classified storage;Step S3, the original data collected is cleaned and preprocessed;Step S4, big data analysis and mining;Step S5, security vulnerability assessment and classification;Step S6, early warning trigger and notification;Step S7, establish security decision support system, provide reasonable security decision suggestion, the third party vulnerability database is collected, stored and analyzed in the application, realize the accurate detection and evaluation of potential vulnerability of business system, network and application program etc. each aspect, and timely security risk early warning and repair suggestion.

The invention discloses a robustness test method for a retrieval enhancement generative software vulnerability evaluation system, and belongs to the technical field of software engineering and information security. The method comprises the following steps: S1, for a vulnerability code to be evaluated, acquiring a related original example set by utilizing a retrieval module; s2, analyzing and generating candidate variants which keep semantic consistency based on the abstract syntax tree; s3, selecting a confrontation example set through a comprehensive scoring function and a beam search strategy; and S4, constructing a prompt context by utilizing an adversarial example to interfere with vulnerability severity evaluation of the large language model, and particularly inducing high-risk / key vulnerability degradation to be misjudged as medium-risk / low-risk. The testing method can effectively reveal potential security risks caused by a retrieval enhancement mechanism, and is used for quantitatively evaluating the robustness of a vulnerability evaluation system.

Systems and methods are described herein for performing vulnerability assessment on partially functional software applications (e.g., software applications currently at a phase in the development cycle prior to a user acceptance testing phase). By doing so, the system may detect vulnerabilities, if any, more easily based on the fewer functional components of the application. Additionally or alternatively, curing any vulnerabilities will require fewer modifications to the application's software, architecture, and / or intended functionality (as these characteristics are also earlier in their development cycle).

Methods, system, and non-transitory processor-readable storage medium for regex engine system are provided herein. An example method includes a Continuous Integration / Continuous Delivery (CI / CD) pipeline that triggers a regex engine system to scan source code. The regex engine system scans the source code for a plurality of regular expressions, and determines a regular expression vulnerability assessment associated with the plurality of regular expressions. The regex engine system generates a regular expression vulnerability assessment report comprising the regular expression vulnerability assessment.

Method and apparatus for analyzing operational processes to detect vulnerabilities are provided. The method includes generating a documented workflow by processing a plurality of unstructured documents associated with an operational process, generating an implemented workflow by analyzing source code that implements the operational process in a computing system, generating an executed workflow by processing real-world execution data for the operational process, analyzing the documented workflow, the implemented workflow, and the executed workflow to identify one or more inconsistencies among the workflows and one or more exploits within the operational process, and generating one or more recommended actions to remedy at least one of the one or more identified inconsistencies or the one or more identified exploits.

The application discloses a power transmission and transformation foundation flood vulnerability assessment method and system based on an optimized neural network, relates to the technical field of power facility disaster assessment, and comprises the following steps: obtaining structure parameters and flood boundary information, combining scour dynamic time sequence characteristics to form working condition data; mapping the working condition data to a two-dimensional phase space, and identifying a to-be-supplemented working condition set with insufficient sample coverage; constructing a physical constraint term based on a fluid-solid-seepage coupling equation, generating working condition data by using a physical information generative adversarial network to form a training data set; constructing a vulnerability assessment network and iteratively training the network; based on maximum Lyapunov index monitoring result distribution, when the distribution tends to be concentrated, constructing a negative curvature direction to update network parameters according to a loss function second-order gradient; inputting real-time flood load into the updated network, and outputting an instability risk grade after forward modeling and checking by the coupling equation. The application solves the problems of insufficient sample coverage and loose combination of physical mechanism and data driving, and realizes high-precision risk assessment.

The invention discloses a novel power distribution system vulnerability assessment method and system based on a dynamic weight. The method comprises the following steps: establishing a power distribution system vulnerability assessment index system, and determining an initial weight through an analytic hierarchy process (MSDM-AHP) based on a Muslim diagram; collecting safety monitoring data in real time; updating the weight of each index through a dynamic weight adjustment mechanism based on real-time data: calculating the current threat level of each index, dynamically adjusting the weight when the current threat level exceeds a trigger threshold value, and performing normalization processing; and finally, calculating a comprehensive vulnerability factor through a TOPSIS algorithm by using the obtained dynamic weight, and then calculating a comprehensive risk value based on the vulnerability factor, the asset value and the influence consequence to quantify a network security evaluation result of the novel power distribution system. According to the method, the defects of lag and stiffness of a traditional static evaluation model are overcome, and real-time, self-adaptive and accurate evaluation of the network security state of the novel power distribution system is realized.

The application discloses a substation communication network fragile structure evaluation method based on a complex network theory, which comprises the following steps: constructing a substation communication network model, generating link weights based on attack paths of the substation communication network model, combining the complex network theory with the link weights, and calculating a plurality of node vulnerability values; based on the node vulnerability values, comprehensively considering local information and global information of the links, and calculating a plurality of link vulnerability values; and based on the node vulnerability values and the link vulnerability values, respectively evaluating the fragile structure of the substation communication network. The application can solve the problems of fast network attack updating speed and difficulty in quantification and subjectivity of expert evaluation in the prior art.

The invention relates to the technical field of scanning verification, and discloses an electric power information system vulnerability hidden danger scanning verification system. Comprising a data set module for matching and binding power data and power equipment into a data set, an active scanning module for actively scanning suspicious vulnerabilities of the data set, an intrusion verification module for performing intrusion verification on the suspicious vulnerabilities and verifying risk vulnerabilities, and a vulnerability assessment module for assessing vulnerability hidden danger levels of the power information system. According to the method, the hindrance encountered by loophole hidden dangers during active scanning is reduced, the phenomena of mismatching of verification conditions and inaccurate verification results caused by sharing one verification environment are avoided, and the risk hidden dangers of suspicious loopholes can be accurately verified by utilizing an intrusive verification mode; the scanning verification effect of two dimensions of active non-intrusive scanning and active intrusive verification of the loophole hidden danger is realized, and the scanning verification accuracy of the loophole hidden danger in the electric power information system is greatly improved.

A method for multi-source cloud infrastructure vulnerability management includes receiving cloud element information related to a cloud-based element in a cloud environment. The method also includes receiving first vulnerability information from a first vulnerability source and receiving second vulnerability information from a second vulnerability source. Cloud element context information is also received from the cloud environment regarding the cloud-based element. A multi-source vulnerability database is then generated from both the first vulnerability information and from the second vulnerability information. The cloud element information and the cloud element context information are then evaluated using the multi-source vulnerability database to generate a vulnerability assessment.

This invention discloses a vulnerability assessment method, identification method, and apparatus for oil pipeline operating conditions. The vulnerability assessment method includes: segmenting target operating condition data to obtain multiple multidimensional time series; performing correlation analysis and feature extraction on the multiple multidimensional time series to obtain corresponding adjacency matrices and input features; combining the adjacency matrix and input features of each multidimensional time series to obtain subgraphs of each time series; using each subgraph as a node, calculating the conditional probability between any two adjacent nodes to obtain the weight of the edge between any two adjacent nodes; obtaining a target network model based on the nodes and the weights of the edges between any two adjacent nodes; calculating the evaluation index of each node based on the target network model and the node data; and selecting the operating conditions with the highest vulnerability based on the evaluation index of each node. This method can accurately identify vulnerable operating conditions of oil pipelines.

In an embodiment, a software object development system generates a pre-release version of a machine image of a software object, and transmits information associated with the pre-release version of the software object to a vulnerability management system. The vulnerability management system performs a vulnerability scan for known vulnerabilities(s) on the information associated with the pre-release version of the machine image of the software object. The vulnerability management system determines scan result(s) based on the vulnerability scan, and transmits, to the software object development system, a report comprising the scan result(s).

A method may include obtaining first network information from a network scan of a computer network that describes network vulnerabilities of a computer network and second network information that describes network traffic of the computer network. The method may include identifying an interaction with the computer network based on the network traffic included in the second network information. The method may include correlating the first network information and the identified interaction to determine a network security issue for the computer network. Correlating the first network information and the identified interaction may include determining a correspondence between the interaction with the computer network and the network vulnerabilities described by the first network information. A network alert may be generated based on the potential network security issue.

The application discloses a power distribution network vulnerability assessment method and terminal based on typhoon gale and heavy rainfall, and realizes fine identification of composite disasters by constructing a typhoon gale and heavy rainfall composite event identification matrix at an hourly level, and overcomes the limitations of traditional daily scale and single disaster factor methods. According to the composite event identification matrix, the effective influence frequency of the typhoon gale and heavy rainfall composite event is calculated, in order to quantify the composite disaster intensity, the maximum wind speed, the rain intensity, the cumulative rainfall and the effective influence frequency are fused, the composite disaster index is calculated, and the regional adaptation degree is improved. In the aspect of establishing the vulnerability index, the Logistic function is introduced to establish the nonlinear mapping between the composite disaster index and the feeder failure rate, and the vulnerability index is formed. Furthermore, in order to solve the problem of insufficient disaster loss samples in some areas, the similarity interpolation is constructed based on the Mahalanobis distance, the vulnerability parameters of the missing areas are inferred, and the global quantitative evaluation is realized.

The invention relates to the technical field of power network security, in particular to a power network-oriented network security attack and defense script automatic generation method, system and device and a medium, and aims to construct a survey model to perform demand investigation and formulate a demand analysis model to ensure that the generated script meets the actual demand; meanwhile, a knowledge graph model and an automatic generation model are constructed, and automatic generation of a high-simulation attack and defense script is achieved; different from a traditional static script generation method, the method adopts reinforcement learning, knowledge graph and automatic generation technologies, realizes real-time update and adaptability of the script, and accurately simulates a complex attack and defense scene; and in addition, adversarial drilling, vulnerability assessment and emergency response training are combined, so that the response speed and defense effect of the power network to novel threats are improved, and the system risk is reduced.

The embodiments disclosed herein are directed to a continuous vulnerability assessment system for detecting exploitable vulnerabilities. For example, an agent executes on a plurality of computing devices. Each agent profiles various pieces of software executing on its respective device and obtains various characteristics thereof. For instance, each agent determines, among other things, the length of time certain software executes on the device. Each agent provides descriptors of the determined characteristics to a vulnerability assessment engine. The engine determines a cumulative length of time that each particular piece of software executed across the plurality of computing devices. The engine also determines whether a vulnerability exists with respect to each particular piece of software, assigns a security risk level for the software based at least on the determined vulnerability and the cumulative length of time, and performs an action to mitigate the determined vulnerability based on the security risk level.

This application discloses an integrated assessment method and device for multivariate seismic vulnerability of tunnels that incorporates physical priors, relating to the technical field of seismic analysis and seismic risk probability assessment of underground engineering structures. The method includes: generating predicted samples based on a logarithmic domain joint distribution description; inputting each predicted sample into a heteroscedastic moment estimation substitution model to obtain predicted values ​​of the conditional mean and conditional variance of the logarithmic domain demand response; reconstructing and dynamically anchoring the conditional marginal distributions of each response based on the predicted values ​​and residual information, and coupling each anchored conditional marginal distribution to obtain a multi-response joint probability model; calculating the point-state failure probability of each projected sample under a preset damage state based on the multi-response joint probability model, constructing discrete sample pairs; and fitting each discrete sample pair to obtain seismic vulnerability curves under each preset damage state. This application improves the accuracy, robustness, and engineering usability of tunnel seismic vulnerability assessment.

The application belongs to the technical field of fatigue damage and seismic risk assessment of high-rise steel structure, and discloses a wind-induced fatigue damage high-rise steel structure full-life seismic vulnerability assessment method based on Bayesian theory. By introducing the cross-wind vibration response into the fatigue damage assessment, the calculation precision of the full-life cycle fatigue damage accumulation of the key components of the high-rise building is significantly improved. By establishing a time-varying seismic demand model based on Bayesian updating, the cognitive uncertainty of unknown model parameters in the seismic demand is effectively quantified and constrained, so that the defect of large dispersion of the traditional deterministic vulnerability analysis results is overcome. Finally, the time-varying seismic vulnerability curve with a clear confidence boundary is generated, which provides a reliable probabilistic basis far beyond the traditional method for the life cycle safety assessment and risk decision of the high-rise building under multiple disaster scenarios.