372 results about "Application security" patented technology

The method provides for securely harvesting and distributing trusted metadata from devices to artificial intelligence (AI) systems. It enables use of cryptographic hashes and signatures on data for supply chain provenance. It is an agentless method to enhance application security by design, and data protection with data authenticity and confidentiality in device to upstream services communications and data sharing. It helps securely harvest, filter, and forward device metadata to webhooks for AI / ML driven data analytics.

Various embodiments include systems and methods of implementing a machine learning model for calculating confidence scores associated with potential security vulnerabilities. The machine learning model is trained using vulnerability data associated with a set of previously identified vulnerabilities, where the vulnerability data indicates whether a previously identified vulnerability is a true positive or a false positive. In some embodiments, scan traffic data may be obtained. The scan traffic data may be associated with potential security vulnerabilities detected via scan engine(s) that implement application security testing. The machine learning model may be used to determine respective confidence scores for each potential security vulnerability. According to some embodiments, responsive to a request for scan findings associated with a particular application, the respective confidence scores may be displayed via a vulnerability analysis graphical user interface.

The invention discloses a quantum secret communication application security test method, system and device and a medium, and belongs to the technical field of communication security. According to the quantum secret communication application security test method, an attack detection model, a receiving and transmitting end detection model, a security performance index test model and a security result analysis model are constructed, and a security test process and a test process index are provided for the security problem of a classical communication process in quantum secret key distribution practical application; according to the method, the anti-attack capability and the security performance of a tested system are evaluated, so that the security of the quantum key distribution network is evaluated, and a corresponding test result is generated, so that the integrity and the confidentiality of a key in a transmission process are ensured, and a security evaluation reference can be provided for a power wireless public network; a communication security test verification scheme is provided for the quantum key distribution network, and the security operation of the key infrastructure is ensured.

Systems and methods for resolving code vulnerabilities through collaborative agents which may include accessing a code base of an identified vulnerability; configuring a plurality of autonomous agents, each comprising a predefined agent role associated with application security remediation process; executing a directed workflow of the plurality of agents, wherein the workflow is a conditional sequence of agent-driven processing steps for generating a proposed resolution to the identified vulnerability; and outputting a candidate resolution for the vulnerability based on results produced by the workflow.

A method and system for classifying a triage-related message related to a software application security technical problem is provided. A triage-related classification is generated for the triage-related message by applying a processor-implemented machine learning model that has been trained to analyze the text of the triage-related message. The generated triage-related classification is sent to a user for remediating the software application security technical problem.

The invention provides a mobile application security access method based on randomness, and relates to the field of mobile application security, and the method comprises the steps: firstly, sending request information to a server through a client, and then carrying out the risk assessment of the request information through the server by using a deep learning algorithm, including the extraction of a user identity, an operation type and context information; and in combination with real-time security threat intelligence, dynamic response coding characteristics are generated by utilizing structured and semantic coding technologies, and the risk level of the request is calculated, so that the challenge complexity is dynamically adjusted, and random challenges are generated and sent to the client. And after the client responds, the server verifies the correctness so as to decide whether to continue service processing or deny access. Thus, risks can be quantified within milliseconds, the delay and stiffness problems of a traditional static strategy are solved, and efficient safety protection and good user experience balance are achieved.

The invention relates to the field of block chain technology and application security, and discloses a block chain-based APP data trusted storage and sharing method, which comprises the following steps of: maintaining a verifiable state container comprising state data and an access policy dual-Merkel tree under a chain, and recording a root hash of the verifiable state container in the block chain; for different updates, generating corresponding evidences: generating single-step evidences containing Merkel evidences for single-step updates; and generating the composite proof containing the zero-knowledge proof for the complex process. And the intelligent contract can update the root hash in an atomized manner only through verification and certification. During data sharing, data and dual Merkel proof are provided for a consumer to verify data authenticity and access legality. According to the method, complex calculation is arranged under a chain, low cost and constant overhead of on-chain verification are achieved, and meanwhile high-safety data credible storage and refined authority control capacity are provided through a dual-tree dual-certificate mechanism.

Disclosed are various approaches for multimodal large language model (LLM) based threat modeling. The multimodal LLM based threat modeling can include a system or method that can input, into a threat modeling multimodal LLM, prompting data that includes audio data, image data, and LLM instructions to generate application security data. The threat modeling multimodal LLM can generate and provide application security data that includes at least one of: threat data, weakness data, security control data, a security risk summarization, an application threat model, or any combination thereof.

The invention relates to an electric power mobile application security protection method based on a swan gap microkernel, which comprises the following steps of: S1, establishing a hardware trust root, and storing a device root key and a certificate chain by utilizing a non-tampering storage area built in a chip; s2, establishing a complete trusted boot chain based on a hardware root of trust, and verifying the integrity and credibility of the next layer by each layer from Bootloader to a swan microkernel and then to an application program; s3, constructing a triple authentication system based on user identity, equipment identity and biological characteristics, and performing user authentication; s4, according to a user authentication result, realizing fine-grained authority control based on an RBAC model and ABAC, and ensuring that authority check can be executed during resource access every time by utilizing an IPC security mechanism of a swan micro kernel; and S5, creating an independent execution environment for each power application according to the process isolation capability of the swan microkernel, and ensuring that memories among the applications cannot be mutually accessed through virtual address space isolation. The reliability of power mobile application safety protection is effectively improved.

The method provides for securely harvesting and distributing trusted metadata from devices to artificial intelligence (Al) systems. It enables use of cryptographic hashes and signatures on data for supply chain provenance. It is an agentless method to enhance application security by design, and data protection with data authenticity and confidentiality in device to upstream services communications and data sharing. It helps securely harvest, filter, and forward device metadata to webhooks for AI / ML driven data analytics.

The invention discloses a commercial password application security assessment evidence identification method based on image identification, relates to the technical field of image identification, and aims to assess employee advanced engineer certificates, extract information from multi-modal documents by using a Qwen-VL visual language model, generate vectors, label the vectors, convert the vectors into structured evidence nodes and store the structured evidence nodes in a graph database. Establishing various edges according to different associations, and constructing a preliminary evidence network; identifying certificate nodes, and clustering to form a certificate entity group; a correlation score is calculated by searching the support evidence through forward traceability, a correlation score is calculated by searching the contradiction evidence through reverse traceability, the credibility of the certificate entity group is dynamically adjusted, and the influence is propagated according to the updated credibility; and screening abnormal certificates lower than a threshold value, analyzing causes and contradictory points, listing abnormal information, visually displaying key evidences, the contradictory points and associated paths, and generating text description.

The invention relates to the field of application security detection, and provides a mobile application security assessment and automatic detection method, which adopts a data processing technology based on artificial intelligence to carry out syntactic analysis and semantic understanding on an obtained code of a mobile application program so as to obtain a code semantic structured coding feature. Meanwhile, semantic embedding coding is carried out on a set of security vulnerability rules extracted from the security vulnerability rule base to obtain a set of security vulnerability rule semantic embedding coding features; then, a detection result is automatically obtained based on dynamic query analysis representation of a set of code semantic structured coding features and security vulnerability rule semantic embedded coding features, and a security alarm prompt is generated in response to the detection result under the condition that the confidence coefficient of security vulnerabilities in the mobile application program exceeds a preset threshold value. In this way, the accuracy and reliability of the security vulnerability detection result can be effectively improved.

The invention provides an application unauthorized vulnerability detection method, device and equipment and a readable storage medium, and relates to the technical field of network security, and the method comprises the steps: obtaining request execution information returned according to at least one request message in an application operation process based on an interactive application security test technology; performing message arrangement on the request message according to the request execution information; replacing the user associated information in the arranged request message with target test information to obtain a new request message; replaying the new request message for the application, and obtaining feedback information of the application; and based on the feedback information, determining whether the application has an unauthorized vulnerability. According to the scheme, the request execution flow information generated in the application running process is collected, and the request of the application is rearranged, replaced and transformed into the new request message, so that the normal operation process of a user can be simulated, automatic unauthorized vulnerability detection is realized, the detection efficiency is improved, and the detection effect of the unauthorized vulnerability of the application is improved.

The invention provides a cloud native application security protection and monitoring method and system for financial science and technology, and relates to the technical field of financial science and technology network security, and the method comprises the steps: obtaining multi-dimensional monitoring data, building a security threat knowledge graph, recognizing a high-risk attack path through a graph convolution network, generating a potential threat prediction result, and recognizing an abnormal behavior. And configuring a dynamic honeypot environment, recording behavior tracks of attackers, analyzing attack intentions and technical characteristics, and generating and deploying protection rules in real time. According to the invention, the safety protection capability of the financial cloud environment is improved, and intelligent threat prediction and active defense are realized.

The embodiments herein provide a method and a system for developer identification and ticket assignment. The method comprises applying owner identification logics through a plurality of application security testing methodologies such as SAST, DAST and SCA tool. The method further comprises making an API call through a vulnerability management platform to a code repository to identify the developer who has changed the portion of the code recently; assigning a ticket to the identified developer and saving the developer in the vulnerability management platform; viewing the status of the ticket through various options such as insight view, CTO view, Engineering Manager view and Developer view; and providing training requirements and assessing the effectiveness of training.

The present disclosure relates to the technical field of intelligent gateway security, in particular to a security architecture and system for a central gateway, and a storage medium. The security architecture includes an application security layer, a data security layer, a network security layer, a node security layer, an identity and authentication management layer, and a security operation and maintenance layer; wherein the application security layer is used to ensure the security of application software; the data security layer is used to ensure the security of data passing through a central gateway; the security of in-vehicle and out-vehicle network communication of the central gateway is ensured by the network security layer; the node security layer is a support carrier for the application security layer, the data security layer, and the network security layer; and the identity and authentication management layer and the security operation and maintenance layer are both applied to the application security layer, the data security layer, the network security layer, and the node security layer. The central gateway is not only a simple data exchange center, but also has data and computing power, and provides common functions of a sharing service, central management, central control, and the like for a complete vehicle; and the central gateway in the present disclosure has double-layer protection of local data security and data transmission security.

The present invention includes systems and methods for providing cybersecurity to web-enabled applications for protection of critical software and host systems. The present invention is operable to build a Hidden Markov model of an application using automated analysis of code and documentation in order to characterize potential state and state transitions. The present invention is also operable to use additional data such as timing and proximity to assess incoming data. Incoming messages are then assigned a trust score based on Bayesian calculations.

The method provides for securely harvesting and distributing trusted metadata from devices to artificial intelligence (AI) systems. It enables use of cryptographic hashes and signatures on data for supply chain provenance. It is an agentless method to enhance application security by design, and data protection with data authenticity and confidentiality in device to upstream services communications and data sharing. It helps securely harvest, filter, and forward device metadata to webhooks for AI / ML driven data analytics.

The invention relates to the technical field of element security risk identification in an informatization system development process, in particular to a code and component security risk identification method and device and a medium, and the method comprises the following steps: collecting version history of codes and components, auditing security risk characteristics of different programming languages, and evaluating a dependency relationship between the codes and the components; and analyzing static security characteristics of the code and the component, and generating a development security risk model. According to the method, the identification capability of potential development security risks is enhanced through security risk auditing of codes and binary components, and the development security risks are revealed in advance and the accuracy of development security risk assessment is optimized through continuous left shift of the security identification stage of an informatization system; therefore, security vulnerability identification of codes and components does not depend on detection of past data or known vulnerabilities any more, security threat modes of codes and components which emerge newly or have complex logic structures can be identified in real time, and the application security level in a software application development period is remarkably improved.

The application provides a security management system and method applied to a smart education platform, wherein the system comprises: a platform application security management module, which is used for performing security management on a data application layer of the smart education platform; a data security management module, which is used for performing security management on a data storage layer of the smart education platform; and a big data component security management module, which is used for performing security management on a big data basic component layer of the smart education platform. The security management system applied to the smart education platform of the application performs security management on the data application layer, the data storage layer and the big data basic component layer of the smart education platform through the platform application security management module, the data security management module and the big data component security management module, so that the security of the big data platform is ensured.

The invention provides a prison break attack method, device and equipment for testing a model defense mechanism, and relates to the field of artificial intelligence application security. A jailbreak attack method for testing a model defense mechanism comprises the following steps: setting a plurality of behavior templates and a jailbreak attack suffix to generate a prompt statement for inputting a model; based on the prompt statement, performing optimization and token updating on the prison break attack suffix; inputting a prompt statement containing the prison break attack suffix subjected to optimization and token updating into a preset model, and performing iterative updating on the prison break attack suffix according to the output content of the model; and determining a stable jailbreak attack suffix in the iteratively updated jailbreak attack suffixes. According to the embodiment of the invention, the stable and effective jailbreak attack suffixes can be selected, and the attack performance and efficiency of the model are improved.

The method provides an automated and scalable system for the generation, distribution, management of symmetric pre-shared keys (PSKs) to applications executing on headless and mobile devices. It helps achieve device protection, application security, and data protection with data authenticity and confidentiality in intra-device, inter-device, device-to-edge, and device-to-cloud communications. It helps Transport Layer Security (TLS) enabled applications dynamically acquire and renew PSKs and use identity hints for PSK based authentication ceremony during a TLS handshake. It helps manage and distribute API shared secrets and API access tokens required for authenticated API requests and API security. It helps applications (producers, brokers, and consumers of content) with PSKs for supply chain tamper resistance. It helps real-time low-latency applications with selective encryption of partial messages.

The invention relates to the technical field of software testing, and particularly discloses an automatic inspection platform based on a grey box test, comprising a detection console module used for managing and controlling a test process; the grey box security test overall module is used for enabling the data flow generated by the test to penetrate through the network; the grey box security test network module is used for taking a rear-end server as a computing resource and a storage resource, and packaging the rear-end server into a service by a certain management server for external provision; the grey box security test function module is used for detecting newly generated vulnerabilities in the software development process in real time; and the grey box security test tool module is used for detecting security problems in the software. By using the instrumentation technology and the flow agent, real-time vulnerability detection is carried out on the running application and API in the research and development test stage, full life cycle management and multi-dimensional application security management and control of vulnerabilities detected by an application system are supported, and the method has the advantages of high coverage, low false alarm, real-time detection and the like, and can be seamlessly fused with a DevSecOps process.

A superlattice corresponding to static application security testing (SAST) of source code specifies lattices respectively corresponding to static analyses performable on the source code. Each lattice is specified by all possible lattice elements of the lattice and an operator indicating how two lattice elements of the lattice are combined during the static analysis to which the lattice corresponds. A lattice product of the lattices specified by the superlattice is generated based on all the possible lattice elements of each lattice and the operator of each lattice indicating how two lattice elements are combined. Generalized dataflow analysis executable code is executed on the source code, using the lattice product, to perform the SAST of the source code, including the static analyses respectively corresponding to the lattices.

The invention discloses an automatic detection method, system and device for Python language password API misuse and a medium. In the scheme provided by the invention, an abstract syntax tree is reconstructed in combination with Python language characteristics, the abstract syntax tree is reconstructed according to the Python language characteristics, node representation is simplified while function consistency is guaranteed, and the probability of misuse of the Python language password API misuse is lowered. Therefore, the false alarm rate and the missing report rate are reduced in the subsequent taint analysis process; meanwhile, a static taint analysis technology is utilized, taint propagation in the process and between functions is carried out based on reconstruction of an abstract syntax tree, and all password API misuse rules are covered through a taint detector, so that a detected password API misuse instance is determined. Generally speaking, the method fills up the blank that no password API misuse detection for the Python application program exists at present, and plays an important supporting and promoting role in the field of password application security evaluation.

In one embodiment, a method includes receiving, by a network component, application performance data. The application performance data is associated with one or more applications. The method also includes determining to transform, by the network component, the application performance data into application security data, generating, by the network component, a baseline for the application security data, and detecting, by the network component, an anomaly in the baseline. The method further includes determining, by the network component, a potential security threat based on the anomaly.

The invention relates to the technical field of static application security detection, and discloses a training data generation method and system based on static application security detection, and the method comprises the steps: analyzing a source code of a target application program, obtaining a key condition variable and a use position, and introducing condition logic on the basis, an unsecure execution path is created that is triggered under a particular runtime condition. And then, according to the conditional logic, generating environment simulation information during operation, verifying the source code sample into which the conditional logic is introduced, determining whether a defect exists in combination with the environment simulation information, and finally generating a defect label. The method effectively solves the problem that an existing SAST tool is difficult to effectively capture the hidden security defect triggered under the specific runtime condition when facing a modern complex software system, especially a micro-service or distributed architecture application.

One or more computing devices, systems, and / or methods for managing security associated with applications are provided. In an example, a central security gateway may determine first security policy information associated with a first application. The central security gateway may establish a first encrypted connection with a first device of the first application. The central security gateway may manage, based upon the first security policy information and using the first encrypted connection, security associated with the first application. The central security gateway may determine second security policy information associated with a second application. The central security gateway may establish a second encrypted connection with a second device of the second application. The central security gateway may manage, based upon the second security policy information and using the second encrypted connection, security associated with the second application.

The invention relates to the technical field of digital information application security, in particular to a fine-grained malicious behavior positioning method and system based on semantic enhancement, and the method comprises the steps: carrying out the feature extraction of a benign sample and a to-be-detected malicious sample, designing a feature set containing a semantic embedding API sequence, carrying out the coding through a weight, generating a node embedding expression, and carrying out the recognition of the feature set. Fusing the numerical features and the sequence features, and constructing an attribute control flow diagram; optimizing the attribute control flow diagram; training a graph attention auto-encoder model containing bidirectional propagation and multiple masks based on a benign sample; a malicious sample is input into the trained auto-encoder model for reconstruction, a reconstruction error is calculated, and basic block level fine-grained malicious behavior positioning is realized; according to the method, the related semantics of malicious behaviors in malicious samples are highly condensed, a feature coding technology and a graph structure optimization strategy are fused, and a trained model can accurately position basic blocks of the malicious behaviors through a customized loss function.

The invention discloses a multi-agent-driven security alarm log simulation generation method, and relates to the technical field of network security, and the method comprises the following steps: S1, obtaining a sample log; s2, on the basis of the sample log, obtaining and defining an overall feature as Ft, a session feature as Fs, a field feature as Fc, an overall rule as Rt, a session rule as Rs and a field rule as Rc; s3, Ft, Fs, Fc, Rt, Rs and Rc are input into the large language model, logs are generated, and the generated logs are classified into overall logs, session logs and field logs; s4-S6, performing outer-layer circulation, middle-layer circulation and inner-layer circulation on the basis of the generated overall log, session log and field log, so as to obtain a final simulation security alarm log set; and S7, performing quality evaluation on the generated simulation security alarm log. According to the method, the security simulation logs meeting the requirements are generated through various agents, and the method is very valuable in scenes such as security testing, security simulation and application security testing.