Abstract: The disclosed subject matter includes a system, which when installed in a specific host, such as an end point, or end point computer, will model its behavior over time, score new activities in real time and calculate outliers, by creating and analyzing vectors. The vectors are formed of feature values, extracted from executable processes, and the analysis includes the determining and evaluating the distance between a current vector and a cluster of vectors.

Abstract: Methods and systems provide a vulnerabilities list and an open devices list based on results from scanning by scanners not associated with a host computer or resource.

Abstract: Computerized methods and systems determine an entry point or source of an attack on an endpoint, such as a machine, e.g., a computer, node of a network, system or the like. These computerized methods and systems utilize an attack execution/attack or start root, to build an attack tree, which shows the attack on the end point and the damage caused by the attack, as it propagates through the machine, network, system, or the like.

Abstract: Computerized methods and systems determine an initial execution of an attack on an endpoint. An indicator of the attack is obtained by analysis of a first process on the endpoint. A sequence of processes that includes the first process associates the initial execution of the attack with the first process. Each respective process in the sequence of processes is created or executed by at least one of the initial execution or a process in the sequence of processes. The initial execution is identified based on linking from the first process to the initial execution through a combination of executions and creations of the processes in the sequence of processes.

Abstract: Computerized methods and systems determine an entry point or source of an attack on an endpoint, such as a machine, e.g., a computer, node of a network, system or the like. These computerized methods and systems utilize an attack execution/attack or start root, to build an attack tree, which shows the attack on the end point and the damage caused by the attack, as it propagates through the machine, network, system, or the like.

Abstract: Disclosed are methods and systems for detecting malware and potential malware based on using generalized attack trees (generalized attack tree graphs). The generalized attack trees are based on attack trees (attack tree graphs), whose objects, such as links and vertices, have been analyzed, and some of these objects have been generalized, resulting in the generalized attack tree of the invention.

Abstract: Computerized methods and systems identify events associated with an attack initiated on an endpoint client. A listing of processes executed or created on the endpoint during the attack is obtained. The listing of processes includes a first process and at least one subsequent process executed or created by the first process. The computerized methods and systems analyze for the occurrence of at least one event during a time interval associated with the attack. The computerized methods and systems determine whether the listing of processes includes a process that when executed caused the occurrence of the at least one event. If the listing of processes excludes process that when executed caused the occurrence of the at least one event, the at least one event and the causing process are stored, for example, in a database or memory.

Abstract: Computerized methods and systems determine an entry point or source of an attack on an endpoint, such as a machine, e.g., a computer, node of a network, system or the like. These computerized methods and systems utilize an attack execution/attack or start root, to build an attack tree, which shows the attack on the end point and the damage caused by the attack, as it propagates through the machine, network, system, or the like.

Abstract: Computerized methods and systems determine summary events from an attack on an endpoint. The detection and determination of these summary events is performed by a machine, e.g., a computer, node of a network, system or the like.

Abstract: Disclosed are methods and systems for detecting malware and potential malware based on using generalized attack trees (generalized attack tree graphs). The generalized attack trees are based on attack trees (attack tree graphs), whose objects, such as links and vertices, have been analyzed, and some of these objects have been generalized, resulting in the generalized attack tree of the invention.

Abstract: Disclosed are methods and systems for detecting malware and potential malware based on using generalized attack trees (generalized attack tree graphs). The generalized attack trees are based on attack trees (attack tree graphs), whose objects, such as links and vertices, have been analyzed, and some of these objects have been generalized, resulting in the generalized attack tree of the invention.

Abstract: Computerized methods and systems identify events associated with an attack initiated on an endpoint client. A listing of processes executed or created on the endpoint during the attack is obtained. The listing of processes includes a first process and at least one subsequent process executed or created by the first process. The computerized methods and systems analyze for the occurrence of at least one event during a time interval associated with the attack. The computerized methods and systems determine whether the listing of processes includes a process that when executed caused the occurrence of the at least one event. If the listing of processes excludes process that when executed caused the occurrence of the at least one event, the at least one event and the causing process are stored, for example, in a database or memory.

Abstract: Disclosed are methods and systems for detecting malware and potential malware based on using generalized attack trees (generalized attack tree graphs). The generalized attack trees are based on attack trees (attack tree graphs), whose objects, such as links and vertices, have been analyzed, and some of these objects have been generalized, resulting in the generalized attack tree of the invention.

Abstract: Computerized methods and systems determine an initial execution of an attack on an endpoint. An indicator of the attack is obtained by analysis of a first process on the endpoint. A sequence of processes that includes the first process associates the initial execution of the attack with the first process. Each respective process in the sequence of processes is created or executed by at least one of the initial execution or a process in the sequence of processes. The initial execution is identified based on linking from the first process to the initial execution through a combination of executions and creations of the processes in the sequence of processes.

Abstract: Computerized methods and systems determine summary events from an attack on an endpoint. The detection and determination of these summary events is performed by a machine, e.g., a computer, node of a network, system or the like.

Abstract: Computerized methods and systems determine an entry point or source of an attack on an endpoint, such as a machine, e.g., a computer, node of a network, system or the like. These computerized methods and systems utilize an attack execution/attack or start root, to build an attack tree, which shows the attack on the end point and the damage caused by the attack, as it propagates through the machine, network, system, or the like.