Abstract: Various embodiments for predicting which software vulnerabilities will be exploited by malicious hackers and hence prioritized by patching are disclosed.

Abstract: Various embodiments for predicting which software vulnerabilities will be exploited by malicious hackers and hence prioritized by patching are disclosed.

Abstract: Systems and methods for predicting enterprise cyber incidents using social network analysis on the darkweb hacker forums are disclosed.

Abstract: Various embodiments of systems and methods for an at-risk system identification via analysis of discussions from various online hacker communities are disclosed herein.

Abstract: Systems and methods for predicting enterprise cyber incidents using social network analysis on the darkweb hacker forums are disclosed.

Abstract: Various embodiments of a computer-implemented framework for predicting exploitation of software vulnerabilities are disclosed.

Abstract: Various embodiments of a computer-implemented framework for predicting exploitation of software vulnerabilities are disclosed.

Abstract: Embodiments of a computer-implemented system and methods for predicting and/or determining a probability of a cyber-related attack and associated costs are disclosed.

Abstract: System and methods may detect and mitigate cybersecurity threats to containers. The systems may scan an image of the container using a vulnerability scanner to generate a scan result identifying a cybersecurity vulnerability present in the image. The System may receive threat-intelligence data from a threat intelligence source comprising a first set of information regarding a plurality of cybersecurity vulnerabilities in addition to ground-truth data from a ground-truth data source comprising a second set of information regarding the plurality of cybersecurity vulnerabilities. Ground truth data and threat-intelligence data may be aggregated to generate aggregated data identifying an exploit related to the cybersecurity vulnerability. The aggregated data may be aligned with the scan result to identify the exploit for the cybersecurity vulnerability.

Abstract: Embodiments for systems and methods for third party assessment related to the evaluation of risks associated with third parties in which hacker conversations on websites are filtered and analyzed using keywords as input to uncover relevant forum and marketplace discussions are disclosed herein.

Abstract: Embodiments of a computer-implemented system and methods for automated ranking of computer element/asset importance are disclosed.

Abstract: Embodiments of a computer-implemented system and methods for identifying and analyzing cyber threats and associated vulnerabilities associated with implementation of remote network devices are disclosed.

Abstract: Embodiments of a computer-implemented system for improving classification of data associated with the deep web or dark net are disclosed.

Abstract: A computing device configured for predictive functions related to cyber threat risk accesses historical cybersecurity event data that lists past attacks on particular companies in different industry vertical classifications. Using vulnerability data associated with each attack, enhanced by metadata specifying vulnerable hardware and/or software stacks associated with the attacks, exemplary technology configurations are created that map industry vertical classifications to vulnerable hardware and/or software stacks. These exemplary technology configurations are used as bases for comparison to subject technology configurations under evaluation.

Abstract: Systems and methods for predicting enterprise cyber incidents using social network analysis on the darkweb hacker forums are disclosed.

Abstract: Systems may anticipate exploitation of cyber threats to various technologies. The systems may receive threat-intelligence data from a threat intelligence source, extracting a technology identified in the threat-intelligence data, and extract a first tactic from the threat-intelligence data wherein the tactic is associated with the technology. The system may receive ground-truth data from a ground-truth data source and extract a second technology identified in the ground-truth data. The first technology may match the second technology. The system may extract a second tactic from the ground-truth data wherein the tactic is associated with the technology with the first tactic matching the second tactic. The system may train a statistical model to predict threats to at least one of the first technology or the second technology.

Abstract: Embodiments of a system and methods for detecting social media designed to spread malicious information to “viral” proportions are disclosed. Historical cascade event data from preselected social media accounts as well as information from related accounts is applied to one or more causality metrics to generate a set of causality values. Causality values are further refined and analyzed to determine how casual a user is with respect to a cascade as opposed to other similar users.

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

Abstract: Embodiments of a computer-implemented system and methods for predicting and/or determining a probability of a cyber-related attack in view of data indicative of hacking discussions are disclosed.

Abstract: Embodiments of a system and methods for detecting social media designed to spread malicious information to “viral” proportions are disclosed. Historical cascade event data from preselected social media accounts as well as information from related accounts is applied to one or more causality metrics to generate a set of causality values. Causality values are further refined and analyzed to determine how casual a user is with respect to a cascade as opposed to other similar users.