An example technique includes initializing, by an obfuscation computing system, communications with nodes in a distributed computing platform. The nodes include compute nodes that provide resources in the distributed computing platform and a controller node that performs resource management of the resources. The obfuscation computing system serves as an intermediary between the controller node and the compute nodes. The technique further includes outputting an interactive user interface (UI) providing a selection between a first privilege level and a second privilege level, and performing one of: based on the selection being for the first privilege level, a first obfuscation mechanism for the distributed computing platform to obfuscate digital traffic between a user computing system and the nodes, or based on the selection being for the second privilege level, a second obfuscation mechanism for the distributed computing platform to obfuscate digital traffic between the user computing system and the nodes.

A method of tracking phishing activity is disclosed. A request to download a webpage hosted as part of a legitimate website on a server is initiated. The request includes identification data pertaining to at least one user computing device. The identification data is extracted from the request. A unique identifier corresponding to the extracted identification data is generated. Fingerprint data is generated using at least a subset of the extracted identification data. The unique identifier, the extracted identification data and the fingerprint data is stored. The fingerprint data is encoded into a program and/or data associated with the webpage to generate a modified webpage. The modified webpage is transmitted from the server to the user computing device in response to the request.

Computer-implemented methods and systems for assessing software vulnerabilities through a combination of external threat intelligence and internal information technology data are disclosed.

A threat actor identification system that obtains domain data for a set of domains, generates domain clusters, determines whether the domain clusters are associated with threat actors, and presents domain data for the clusters that are associated with threat actors to brand owners that are associated with the threat actors. The clusters may be generated based on similarities in web page content, domain registration information, and/or domain infrastructure information. For each cluster, a clustering engine determines whether the cluster is associated with a threat actor, and for clusters that are associated with threat actors, corresponding domain information is stored for presentation to brand owners to whom the threat actor poses a threat.

Evaluating computers, devices, or endpoints on a network, such as a large network of computers in an enterprise environment. Detecting computers, devices, or endpoints that may present a security risk to the network or may be compromised in some way. Generating network traffic that, in some cases, should be ignored or should prompt specific, known responses. Detecting endpoint(s) that respond to such network traffic in an anomalous way, or otherwise attempt to perform certain operations based on such network traffic.

A non-transitory computer-readable recording medium records a program for causing a computer to execute processes of: a collecting process of collecting a plurality of pieces of cyberattack information; a specifying process of analyzing the plurality of pieces of collected cyberattack information, specifying a plurality of addresses of cyberattack sources included in the plurality of pieces of cyberattack information, and specifying a period in which each of the specified addresses of the plurality of cyberattack sources is observed; a determining process of determining an address range or some addresses included in the address range as monitoring targets according to a result of comparing a first period distribution of an observed period corresponding to the plurality of specified addresses and a second period distribution of an observed period for each address range; and an outputting process of outputting information regarding the determined address range or some addresses included in the address range.

A specifying device receives detection information from a security device that detects hacking into a network or an activity of a terminal related to infection, and specifies a state of the terminal from information of the terminal and content of activity of the terminal included in the detection information. The specifying device specifies, when specifying that the terminal is in the state of being infected with malware, a terminal that may be infected before performing the content of the activity of the terminal included in the detection information based on connection information stored in a configuration information storage device, and specifies a terminal located on a route, along which the infected terminal is likely to be used for hacking or for infection of the terminal in the future, as a candidate for an infected terminal likely to be infected.

In some embodiments, a plurality of real-time monitoring node signal inputs receive streams of monitoring node signal values over time that represent a current operation of the industrial asset control system. A threat detection computer platform, coupled to the plurality of real-time monitoring node signal inputs, may receive the streams of monitoring node signal values and, for each stream of monitoring node signal values, generate a current monitoring node feature vector. The threat detection computer platform may then compare each generated current monitoring node feature vector with a corresponding decision boundary for that monitoring node, the decision boundary separating a normal state from an abnormal state for that monitoring node, and localize an origin of a threat to a particular monitoring node. The threat detection computer platform may then automatically transmit a threat alert signal based on results of said comparisons along with an indication of the particular monitoring node.

An exemplary computer-implemented method includes obtaining at least one teleportation invite block that records a virtual universe teleportation invite marked by at least one parameter. The teleportation invite identifies a virtual universe user as an invitee. Responsive to the parameter, assess whether the virtual universe teleportation invite is potentially malicious, and alert the invitee in case the virtual universe teleportation invite is potentially malicious. Another exemplary computer-implemented method includes obtaining at least one complaint block that records a complaint made against a virtual universe user; obtaining a plurality of traversal blocks that record virtual universe traversal events by the virtual universe user; identifying a pattern of harassment by analyzing a first plurality of traversal blocks that precede the complaint block; identifying a risk of future harassment by analyzing a second plurality of traversal blocks that follow the complaint block; and issuing an alert regarding the risk of future harassment.

A monitoring apparatus comprises a specifying part, a storing part, and a restoring part. The specifying part specifies an access source. The storing part stores changed item(s) in the environment caused by the activity of the access source. The restoring part restores an environment that is referred to when responding to an operation(s) of the access source based on the changed item(s) of the environment stored by the storing part.