19824 results about "Computer security" patented technology

An example operation may include one or more of storing a database of payment card data, conversing with a user via a chatbot within a chat window of a software application, wherein the conversing comprises receiving a query from the user about a payment card during a chat session between the user and the chatbot, executing a large language model (LLM) on the query about the payment card and the database of payment card data to generate a chatbot response, and displaying the generated chatbot response via the chatbot within the chat window of the software application during the chat session.

An example operation may include one or more of receiving an identifier of a product from a digital wallet on a user device, identifying one or more payment cards stored within the digital wallet on the user device, determining benefits that will be obtained by using each of the one or more payment cards to purchase the product via execution of an LLM on the identifier of the product and a corpus of credit card documents, and displaying a chat message within a chat window on the user device with a description of the determined benefits that will be obtained.

An example operation may include one or more of storing a data store of credit card documentation, conversing with a user via a chatbot within a chat window of a software application, wherein the conversing comprises receiving natural language inputs with requests for information about a payment card, identifying a benefit obtained by the user based on the conversation, executing a large language model (LLM) on the identified benefit and the data store of the credit card documentation to generate a letter of confirmation, and generating an electronic message with the letter of confirmation attached, and transmitting the electronic message to a user device.

An example operation may include one or more of storing a database of payment card data, receiving an identifier of a product from a digital wallet on a user device, identifying one or more payment cards stored within the digital wallet on the user device, determining the benefits that will be obtained by using each of the one or more payment cards to purchase the product via execution of an LLM on the identifier of the product and the database of payment card data; and displaying a chat message within a chat window on the user device with a description of the determined benefits that will be obtained.

The present disclosure includes computer-implemented methods of guardrails for securely using large language models (LLMs). The method comprises monitoring user data flow using an application programming interface (API) and receiving an administrative policy from an administration communication interface. The method involves dynamically applying a plurality of LLM input inspectors to LLM input data. The application of the plurality of LLM input inspectors is based on the administration policy. The dynamic application of the plurality of LLM input inspectors is in sequence for latency optimization. The plurality of LLM input inspectors serve as LLM input guardrails for a plurality of secure deployed large language models (LLMs). The plurality of LLM input inspectors are configured by the administrative policy and validate the LLM input data to validated LLM input data based on the administration policy. Additionally, the method comprises dynamically applying a plurality of LLM output inspectors to LLM output data.

A system and method for securing inter-process communications (IPCs) between generative AI and external tool servers, including intercepting IPCs having a requested operation, performing a security analysis on the IPCs for security threats, performing a permission validation for permissions for the requested operation of each IPC, and either approving or blocking the requested operation of each IPC based on the security analysis and the permission validation.

A method, apparatus, and computer-readable medium of a migration platform for analyzing a legacy database based on applying a large language model to the legacy database and legacy application code to extract legacy database values and legacy application values, determining destination database values corresponding to a destination database based on the legacy database values and the legacy application values, generating migration code for migrating the legacy database to the destination database based on code generation templates, user preferences, and code generation procedures configured to create one or more files and one or more directories based on the code generation templates, validating the migration code based on generating mock data, storing the mock data in the legacy database, and applying the migration code to the mock data to migrate the mock data to the destination database, and executing the validated migration code to perform a migration of the legacy database.

The present application provides a vulnerability remediation code identification method, comprising: acquiring commit information of open-source software, the commit information comprising a committed code snippet and text information associated with the code snippet; inputting the commit information into a first language model and performing identification to obtain function change information and test case information; inputting the function change information into a vulnerability remediation identification model to obtain a vulnerability remediation code snippet for a target vulnerability, and inputting the test case information into a vulnerability test case identification model to obtain a test case code snippet for the target vulnerability; and inputting the vulnerability remediation code snippet for the target vulnerability and the test case code snippet for the target vulnerability into a second language model and performing integration and identification to obtain an identification result. On the basis of notable characteristics in a test case for a vulnerability, the identification rate of vulnerability remediation code can be effectively increased. In this way, a user can discover potential vulnerabilities in advance, thus reducing security risks.

Disclosed here are various embodiments to evaluate a device and present a price quote to the user by detecting a presence of a device in proximity to a wireless charger. The system can utilize a wireless charger to obtain information about the device while charging the device. The information can include the make of the device. The system can guide the user to navigate the device to provide additional information such as model, memory capacity, unique identifier, and carrier associated with the device. Based on the unique identifier, the system can determine whether device has been stolen. If the device has not been stolen, the system can determine a price based on information obtained from the device and can facilitate presenting the price to the user. If the user accepts the price, the system can facilitate purchase of the device.

Systems, methods, and computer-readable storage media for compliance verification and validation of cyber resilience in a distributed entity or third-party network (DETPN). Some methods can include generating or identifying, by one or more processing circuits, one or more compliance parameters for a plurality of entities or third-parties on the DETPN. Some methods can include determining, by the one or more processing circuits, at least one compliance level. Some methods can include receiving or identifying, by the one or more processing circuits, environmental data of the DETPN. Some methods can include determining, by the one or more processing circuits at a second timing phase, an updated at least one compliance level for at least one of the plurality of entities or third-parties based at least on the environmental data. In some implementations, some methods can include generating and storing, by the one or more processing circuits, one or more tokens.

Systems, methods, and / or computer readable storage media for protecting data. A system can include one or more processing circuits configured to receive or identify at least one token including cyber resilience data of at least one entity and corresponding with at least one posture or compliance parameter of at least one third party The one or more processing circuits can perform a zero-knowledge proof (ZKP) on the cyber resilience data, determine at least one posture or compliance parameter of the at least one third party is satisfied based on the cyber resilience data, and / or generate at least one ZKP including at least one cryptographic commitment obfuscating the cyber resilience data. The one or more processing circuits can provide, to at least one third party computing system of the at least one third party, the at least one ZKP or indication of performance of the at least one ZKP.

Systems and methods for directing and enforcing zero trust control on requests to destination services. In various embodiments, steps include receiving a request from a user to access a destination service; directing the request to a control layer; enforcing one or more controls, via the control layer, on the request based on a configuration provided by an owner of the destination service; and providing access to the destination service to the user based on the one or more controls.

Techniques for verifying authenticity of a cosmetic product using a distributed ledger include generating a transaction including identification information for a cosmetic product indicating a manufacturer of the cosmetic product. The transaction is augmented with a cryptographic signature from the manufacturer to prove the identity of the manufacturer. Additionally, the transaction is transmitted to at least one other participant in a distributed ledger network of participants maintaining the distributed ledger. A unique identifier is embedded on the cosmetic product or on packaging for the cosmetic product that references the identification information for a cosmetic product in the distributed ledger.

In embodiments, systems and methods for configuring and deploying artificial intelligence driven transacting agents that are permitted to autonomously execute transactions on behalf of the individual or organization and configuring the transacting agent based on the agent configuration instructions and a set of predefined system prompts. The method further includes granting the transacting agent access to a digital wallet associated with the individual or organization and deploying the transacting agent to a public network, such that the transacting agent executes transactions on behalf of the individual or organization via one or more digital marketplaces using the digital wallet to which the transacting agent was granted access. In some embodiments, the transacting agent is granted access to the digital wallet using a consent token. In some embodiments, the method also includes hyper-personalizing and / or fine-tuning the agent.

Systems and methods for controlling rights related to digital knowledge are disclosed. A sample system may include an input system to receive digital knowledge from a user, a tokenization system to tokenize the digital knowledge and a ledger management system to create, manage, and store things on a distributed ledger and provide provable access to the digital knowledge. A smart contract system may create a smart contract including triggering action is and respond with a defined smart contract action on an occurrence of the triggering event. The smart contract system may also process commitments to the smart contract.

An illustrative method includes accessing, by a data platform, an alert generation policy associated with an entity that deploys containers in a cloud environment, the alert generation policy modifiable by the entity and specifying criteria for providing alerts associated with one or more vulnerabilities associated with the containers; detecting, by the data platform based on a scan of a container included in the containers, a vulnerability associated with the container; determining, by the data platform, an attribute of the vulnerability; and generating, by the data platform when the attribute meets the criteria specified in the alert generation policy, an alert associated with the vulnerability.

Systems and methods for intelligent application definition and protection. In various embodiments, steps include receiving a destination service definition from a customer; performing an assessment of the destination service to determine one or more policies to use for the destination service; responsive to receiving a request from a user to access the destination service, directing the request to a control layer, and enforcing one or more controls on the request based on the one or more policies; and providing access to the destination service to the user based on the one or more controls.

Systems and methods for abnormal Classless Inter-Domain Routing (CIDR) access detection. The present systems and methods are configured to perform the steps of scanning one or more security groups associated with a cloud environment; assigning a score to one or more Classless Inter-Domain Routing (CIDR) groups within the one or more security groups; and providing one or more suggested actions based on the score of the one or more CIDR groups.

A disclosed data platform may be configured to access a custom policy developed by a particular client entity that uses the data platform. The custom policy may invoke a query that targets a target dataset ingested from a cloud environment and stored in a data store. The data platform may determine that the custom policy is likely to be of value to one or more other client entities, besides the particular client entity, that also use the data platform. In response to the determining that the custom policy is likely to be of value to the one or more other client entities, the data platform may generate a community policy based on the custom policy. The community policy may be available for use by the one or more other client entities. Corresponding methods, systems, and products are also disclosed.

The invention discloses a cue word optimization method and device for a large language model, and the method comprises the steps: inputting a jailbreak attack instruction set into a to-be-tested large language model for loop attack, and obtaining a response result of the large language model; calculating an evaluation index according to a response result of the large language model, and when the evaluation index exceeds a preset threshold value, updating cue words in the large language model; the method comprises the following steps: constructing a multi-strategy defense template, analyzing the type of each jail break attack instruction by using the multi-strategy defense template, determining the type of each jail break attack instruction, matching a defense strategy of a corresponding type in the multi-strategy defense template according to the type of the jail break attack instruction, converting the defense strategy into a corresponding defense cue word, and sending the defense cue word to the jail break attack instruction. And inputting the defense prompt words into the large language model to optimize and update the defense prompt words of the large language model. The prompt word updating timeliness and accuracy can be improved, and the resistance and safety of a large language model are improved.

Described herein are systems and methods for discovering and proactively mitigating previously unknown security vulnerabilities. The systems and methods herein can utilize security vulnerability information to discover potential security threats and can utilize this information to generate an attack using a machine learning model, such as a large language model. Generated attacks can be carried out to assess impact of a security vulnerability. An output can be provided that represents the assessed impact. In some implementations, the systems and methods herein generate patches or other mitigations for security vulnerabilities, which can be tested and deployed to address security vulnerabilities.

A method may include, based on a recovery policy associated with the primary database, creating a first snapshot of the primary database at a primary computing system, replicating the first snapshot of the primary database to a secondary computing system, wherein a backup database of the primary database is hosted on the secondary cluster, in response to the primary database being unavailable, applying the first snapshot of the primary database to the backup database, creating, according to the recovery policy associated with the primary database, a snapshot of the backup database, in response to the primary database having restored availability, creating, according to the recovery policy associated with the primary database, a second snapshot of the primary database.

Disclosed herein are apparatus, system, method, and computer-readable medium aspects for identifying and preventing digital skimming attacks using a machine learning model. A threat management system may crawl one or more external sources in order to obtain training data for one or more machine learning models. A plurality of different models may be used to conduct different analyses with respect to an application under test. For example, a first model may identify malicious code. A second model may detect the presence of threat protection code which may protect against skimming attacks. Depending on whether an application under test is free from malicious code and / or includes threat protection code, a threat management system may determine whether close may be promoted to a production or live environment. The threat management system may also use a third model to generate security protocol code for a developer based on learned best practices.

Systems and techniques may generally be used for chatbot-based fraud assistance. An example method may include initiating a chatbot session with a user and receiving a prompt from the user related to suspected suspicious activity in an account. The method may include retrieving, using a Retrieval-Augmented Generation (RAG) component, contextual information from at least one of transaction data and a knowledge base. The method may include evaluating the prompt using a large language fraud model and the retrieved contextual information to determine a response.

A system and method for facilitating an instant lottery game with either or both physical and virtual instant lottery tickets, and in certain embodiments to a system and method for facilitating virtual instant lottery ticket creation, virtual instant lottery ticket selling, virtual instant lottery ticket transferring, virtual instant lottery ticket scratching, and virtual instant lottery ticket redemption. The instant lottery ticket system and method of various embodiments provides the seamless integration with existing physical instant lottery game and ticket systems (and processes thereof), substantially the same overall player experience as provided with physical instant lottery tickets.

Described herein are systems and methods for discovering and proactively mitigating previously unknown security vulnerabilities. The systems and methods herein can utilize security vulnerability information to discover potential security threats and can utilize this information to generate an attack using a machine learning model, such as a large language model. Generated attacks can be carried out to assess impact of a security vulnerability. An output can be provided that represents the assessed impact. In some implementations, the systems and methods herein generate patches or other mitigations for security vulnerabilities, which can be tested and deployed to address security vulnerabilities.

One variation of a method includes: accessing a first policy associated with a computer network; extracting a first entitlement from the first policy, the first entitlement granting permission to a first identity in the set of identities to access a first resource according to a first access level; accessing a first set of event data representing a first access attempt associated with the first resource by the first identity during a first time period, the first access attempt characterized by a second access level; detecting a deviation between the second access level and the first access level defined in the first entitlement; generating a second policy representing a second entitlement granting permission to the first identity to access the first resource according to the second access level in response to the deviation; and serving the second policy to an operator via an interface.

Systems and methods for the creation of human-readable cyber incident reports from cyber incident logs, in which the cyber incident reports may link cyber incidents recorded in a cyber incident log to the existing knowledge sources. To do so, the systems and methods overcome the technical problems of conventional systems as well as the technical problems inherent in adapting artificial intelligence solutions to the creation of cyber incident reports.

A method of secure data routing with dynamic packet spoofing is disclosed that comprises a scatter network node receiving data packets from a user communication device and a scattering application selecting a logical communication channel from a plurality of logical communication channels. The method also comprises a channel controller receiving channel information that comprises a size limit corresponding to data packets being transmitted over the logical communication channel and modifying a received data packet based on the channel information such that a size of the modified data packet satisfies the size limit. The method additionally comprises a channel adapter wrapping the modified data packet to correspond to a particular protocol that is different than an initial protocol of the modified data packet. The method further comprises transmitting the modified data packet wrapped to correspond to the particular protocol via the logical communication channel to a counterpart scatter network device.