Abstract: Systems, methods, and computer-readable media are disclosed for detecting a malware sample by creating polymorphic variants of a malware sample using a large language model. The technology can obtain a known malware sample and decompose the known malware sample into behavioral characterizations of the known malware sample that correspond to respective processes taken by the known malware sample. The technology can then train a large language model with data corresponding to the behavioral characterizations and generate polymorphic variants of the known malware sample with a large language model based on the behavioral characterizations. When the technology later receives a potential malware sample, it can analyze the potential malware sample by comparing the potential malware sample to the polymorphic variants of the known malware sample generated by the large language model.

Abstract: In one aspect, a method includes creating a polymorphic variant of a sample of malware, analyzing the polymorphic variant of the sample of malware by a security management service to determine if the polymorphic variant of the sample of malware evades detection by the security management service, when the security management service fails to detect the polymorphic variant during the analysis of the polymorphic variant, detonating the polymorphic variant in a virtualized environment to identify characterizations of the polymorphic variant, and training the security management service to detect the polymorphic variant based on the characterizations.

Abstract: In one aspect, a method for enhancing cybersecurity using Large Language Model (LLM)-generated honeypot schemes, the method includes generating a plurality of deceptive information using an LLM, configured to attract and engage potential attackers, where the plurality of deceptive information includes one or more characteristics referencing vulnerabilities of a network, continuously monitoring for interactions initiated by an interacting party with one or more components of the generated deceptive information, where the interaction is identified as a potential threat to the network, in response to detection of an interaction identified as a potential threat, extracting interaction data associated with the interacting party retrieved during the interaction, and retraining the LLM with the interaction data to create more effective honeypots.

Abstract: Systems, methods, and computer-readable media are disclosed for detecting a malware sample by creating polymorphic variants of a malware sample using a large language model. The technology can obtain a known malware sample and decompose the known malware sample into behavioral characterizations of the known malware sample that correspond to respective processes taken by the known malware sample. The technology can then train a large language model with data corresponding to the behavioral characterizations and generate polymorphic variants of the known malware sample with a large language model based on the behavioral characterizations. When the technology later receives a potential malware sample, it can analyze the potential malware sample by comparing the potential malware sample to the polymorphic variants of the known malware sample generated by the large language model.

Abstract: In one aspect, a method for enhancing cybersecurity using Large Language Model (LLM)-generated honeypot schemes, the method includes generating a plurality of deceptive information using an LLM, configured to attract and engage potential attackers, where the plurality of deceptive information includes one or more characteristics referencing vulnerabilities of a network, continuously monitoring for interactions initiated by an interacting party with one or more components of the generated deceptive information, where the interaction is identified as a potential threat to the network, in response to detection of an interaction identified as a potential threat, extracting interaction data associated with the interacting party retrieved during the interaction, and retraining the LLM with the interaction data to create more effective honeypots.

Abstract: A product information system and method include a housing, and a communication device coupled to the housing. The communication device is configured to provide information regarding one or more products in response to being engaged by a device of an individual.

Abstract: A product information system and method include a card having an insertion beam. The card retains a communication device configured to provide information regarding one or more products in response to being engaged by a device of an individual. A housing includes an insertion channel leading into an interior chamber. The insertion beam is configured to be inserted into the insertion channel. The housing is configured to retain the insertion beam within the interior chamber to secure the card to the housing.

Abstract: A system and a method are configured to retain one or more components within a sink. The system and the method include a bin configured to retain the one or more components, and a mounting panel configured to removably couple the bin to an interior surface of the sink. The mounting panel includes a coupling pad configured to secure to the interior surface of the sink.

Abstract: A system and a method are configured to retain one or more components within a sink. The system and the method include a bin configured to retain the one or more components. and a mounting panel configured to removably couple the bin to an interior surface of the sink.

Abstract: In one aspect, a method for enhancing cybersecurity using Large Language Model (LLM)-generated honeypot schemes, the method includes generating a plurality of deceptive information using an LLM, configured to attract and engage potential attackers, where the plurality of deceptive information includes one or more characteristics referencing vulnerabilities of a network, continuously monitoring for interactions initiated by an interacting party with one or more components of the generated deceptive information, where the interaction is identified as a potential threat to the network, in response to detection of an interaction identified as a potential threat, extracting interaction data associated with the interacting party retrieved during the interaction, and retraining the LLM with the interaction data to create more effective honeypots.

Abstract: In one aspect, a method includes creating a polymorphic variant of a sample of malware, analyzing the polymorphic variant of the sample of malware by a security management service to determine if the polymorphic variant of the sample of malware evades detection by the security management service, when the security management service fails to detect the polymorphic variant during the analysis of the polymorphic variant, detonating the polymorphic variant in a virtualized environment to identify characterizations of the polymorphic variant, and training the security management service to detect the polymorphic variant based on the characterizations.

Abstract: A product information system and method include a housing, and a communication device coupled to the housing. The communication device is configured to provide information regarding one or more products in response to being engaged by a device of an individual.

Abstract: Methods and apparatus consistent with the present disclosure may be used to create Internet apps and associated websites that bring human-levels of personal trust and intimacy/closeness into use while people are messaging and posting on a fully secured private peer-to-peer Internet communication system empowered by distributed ledger technology and applications. This disclosure reviews useful ways of bringing personal freedom and personal rights using methods that may be objective or subjective using methods that allow users to manage licensing and the fair use of their intellectual property and other information. Meaning an advanced technology that makes manifest the much-needed Enlightenment of the Internet desired by so many thoughtful and concerned people in the US and within the very vocal leadership of the EU. Communications sent between devices may be secured using encrypted such that only users of end devices or nodes may review data sent from another device.

Abstract: Various implementations include a counter system. The system includes a countertop portion, a barrier section, and one or more trays. The countertop portion has a front side and a back side. The barrier section is coupled to a bottom side of the countertop portion along the front side of the countertop. The barrier section is configured to support the countertop portion in use. The barrier section defines one or more openings therethrough. Each tray is aligned with one of the one or more openings and slidable relative to the barrier section between a retracted position and an extended position. Each of the trays is closer to the back side of the countertop in the extended position than it is in the retracted position. Each of the trays passes at least partially through its respective opening when sliding between the retracted position and the extended position.

Abstract: Methods and apparatus consistent with the present disclosure may be used to create Internet applications and associated websites that bring human-levels of personal trust and intimacy/closeness into use while people are messaging and posting on a fully secured private peer-to-peer Internet communication system empowered by distributed ledger technology and applications. This invention and its embodiments represent a useful way of bringing personal freedom and personal rights into full use in an objective a subjective manner on the Internet. Meaning an advanced technology that makes manifest the much-needed Enlightenment of the Internet desired by so many thoughtful and concerned people in the United States and within the very vocal leadership of the European Union. Communications sent between devices may be encrypted such that only users of end devices or nodes may receive message data sent from another device.

Abstract: Various implementations include a laundry fur remover. The laundry fur remover includes a body and one or more protrusions. The body has a body outer surface and a body maximum dimension. The one or more protrusions are coupled to and extend outwardly from the body outer surface. At least one of the one or more protrusions has a protrusion maximum dimension. At least a portion of the body or the one or more protrusions comprises a polymer. The body maximum dimension is greater than the protrusion maximum dimension.

Abstract: A pet feeding device includes a floor and a plurality of flexible members extending upwardly from the floor, each of the plurality of flexible members having a lower portion proximate to the floor and an upper portion that is distal therefrom. The plurality of flexible members are located across an upper surface of the floor to substantially conceal the upper surface of the floor. The plurality of flexible members are formed of a flexible fabric material and are movable in response to a pet searching for food on the pet feeding device.

Abstract: An extender for securing an article around a pet, the extender including: a first fastener portion located proximate a first end of the extender, the first fastener portion located on a first side of the extender; and a second fastener portion located proximate a second end of the extender, the second fastener portion located on a second side of the extender. The first fastener portion is shaped to engage a first fastener of the article and the second fastener portion is shaped to engage a second fastener of the article such that a length of the article is extended by a length of the extender between the first fastener portion and the second fastener portion.