Systems and methods for a.i.-based malware analysis on offline endpoints in a network

Abstract

Disclosed herein are systems and method for optimizing artificial intelligence (A.I)-based malware analysis on offline endpoints in a network. In one aspect, a method includes identifying a file that has not been executed on an endpoint system and scanning the endpoint system to detect malicious behavior using a machine learning algorithm. In response to determining that the endpoint system does not exhibit malicious behavior based on the machine learning algorithm, the method includes enabling execution of the file. Subsequent to the execution of the file, the method includes rescanning the endpoint system to detect malicious behavior using the machine learning algorithm. In response to determining that the endpoint system does exhibit malicious behavior subsequent to the execution, the method includes extracting attributes of the file and retraining the machine learning algorithm using the extracted attributes to detect malicious behavior associated with the file without having to execute the file.