A method for remote access includes obtaining, by a virtual private network (VPN) server, trust data of a user accessing a first network; determining, by the VPN server, a first trust level corresponding to the trust data according to a first correspondence, wherein the first correspondence comprises the trust data and the first trust level; determining, by the VPN server, a first access zone of the first network corresponding to the first trust level according to a second correspondence, wherein the second correspondence comprises the first trust level and the first access zone; and establishing, by the VPN server, a first VPN connection between a device used by the user and the first access zone.

A system and methods for sandboxed malware analysis and automated patch development, deployment and validation, comprising a business operating system, vulnerability scoring engine, binary translation engine, sandbox simulation engine, at least one network endpoint, at least one database, a network, and a combination of machine learning and vulnerability probing techniques, to analyze software, locate any vulnerabilities or malicious behavior, and attempt to patch and prevent undesired behavior from occurring, autonomously.

A system and methods for sandboxed malware analysis and automated patch development, deployment and validation, comprising a business operating system, vulnerability scoring engine, binary translation engine, sandbox simulation engine, at least one network endpoint, at least one database, a network, and a combination of machine learning and vulnerability probing techniques, to analyze software, locate any vulnerabilities or malicious behavior, and attempt to patch and prevent undesired behavior from occurring, autonomously.

There is disclosed a method, computer program product and a system for regulating execution of a suspicious process, comprising determining a file system location of an executable file associated with the suspicious process, encrypting the file, and creating a wrapper for the file with the same file name and location as the file associated with the suspicious process.

There is disclosed a method, computer program product and a system for regulating execution of a suspicious process, comprising determining a file system location of an executable file associated with the suspicious process, encrypting the file, and creating a wrapper for the file with the same file name and location as the file associated with the suspicious process.

Internet of Things (IoT) system and method of interfacing arbitrary non-network connected devices to wireless computer networks. The invention provides a configurable wireless communications module, in either fixed or removable formats, with wireless (e.g. WiFi) network connectivity. The invention uses at least one internal processor, which is configured to operate as a sandbox or virtual machine manner to isolate the code used to operate the arbitrary non-network connected device from the code used to operate the communications module.

Internet of Things (IoT) system and method of interfacing arbitrary non-network connected devices to wireless computer networks. The invention provides a configurable wireless communications module, in either fixed or removable formats, with wireless (e.g. WiFi) network connectivity. The invention uses at least one internal processor, which is configured to operate as a sandbox or virtual machine manner to isolate the code used to operate the arbitrary non-network connected device from the code used to operate the communications module.

Embodiments seek to prevent detection of a sandbox environment by a potential malware application. To this end, execution of the application is monitored, and provide information about the execution to a reinforcement learning machine learning model. The model generates a suggested modification to make to the executing application. The model is provided with information indicating whether the application executed successfully or not, and this information is used to train the model for additional modifications. By modifying the potential malware execution during its execution, detection of a sandbox environment is prevented, and analysis of the potential malware applications features are better understood.

Embodiments seek to prevent detection of a sandbox environment by a potential malware application. To this end, execution of the application is monitored, and provide information about the execution to a reinforcement learning machine learning model. The model generates a suggested modification to make to the executing application. The model is provided with information indicating whether the application executed successfully or not, and this information is used to train the model for additional modifications. By modifying the potential malware execution during its execution, detection of a sandbox environment is prevented, and analysis of the potential malware applications features are better understood.

A honeypot file is cryptographically secured with a cryptographic key. The key, or related key material, is then placed on a central keystore and the file is placed on a data store within the enterprise network. Unauthorized access to the honeypot file can then be detecting by monitoring use of the associated key material, which usefully facilitates detection of file access at any time when, and from any location where, cryptographic access to the file is initiated.