Wells Fargo Bank, N.a.

Other

Peter Anatole Makohon

Lawrence T Belton, Jr

Ryan Bernard Benskin

Timothy H Morris

Christopher J Houser

Daniel Fricano

Shane D Cross

Thomas Gilheany

Kodzo Wegba

Charles Steven Edison

James Bonk

Omar S Bracey

Dale Miller

Robert I Kirby

Jonathan A McNeill

Robert Glenn Yelton, Jr

Scott A Keoseyan

Douglas C Rambo

Jonathan D Russell

Jon Gabel

Tammy C Fleming

Samantha Grosby

Deb J Sante

Jeremy B Hairston, Sr

Ross Cavanaugh

Jennifer Imus

Melissa Nicoletti

Tyra Frison

Kristina Draper

Jon Matthew Welborn

Gary Simms

Terrence W Gareau

Jacob Lee

Jonathan Louis Gabel

A system includes a data channel configured to provide device connectivity data associated with an entity, a data channel communication network configured to communicate the device connectivity data from the data channel, and a processing circuit communicatively coupled to the data channel via the data channel communication network. The processing circuit is structured to identify a vulnerability associated with a property of the device connectivity data, generate a scanner uniform resource locator (URL) based on the property of the device connectivity data, the scanner URL including a parametrized scanner executable structured to accept as a parameter at least a part of the property of the device connectivity data, and transmit the scanner URL to a computing system.

Security model utilizing multi-channel data with vulnerability remediation circuitry

Systems and methods for monitoring and enforcing a service level agreement for an entity are provided. A system includes a scanning engine, an assessment engine, a terms repository, an agreements repository, an assessments repository, and a processing circuit. The processing circuit is configured to perform operations including: receive device connectivity data; determine an entity; identify a data set of computing resources associated with the entity; reference a service level agreement associated with the entity; parse at least one term from the service level agreement; retrieve an assessment map for the at least one parsed term, wherein the assessment map comprises a key performance indicator, a data set of actual service level values, and a response protocol; score the identified data set of computing resources associated with the entity; determine an assessed service level value; store the assessed service level value; and monitor the identified data set of computing resources.

Security model utilizing multi-channel data with service level agreement integration

A computing system comprising a processing circuit is configured to receive, via a data channel from an agentless monitoring data source, user activity data associated with a first computing device of a first user, determine a policy violation based on the user activity data, compare employee-related information associated with the first user to a threshold, determine a baseline level of risk based on the employee-related information exceeding the threshold, determine a user score based on at least one of a threat dimension or an exposure dimension or an impact dimension, determine a probability of an adverse event based on the determined baseline level of risk and the user score, generate a user-interactive electronic notification comprising an indication of the probability of the adverse event, and transmit the user-interactive electronic notification to a second computing device of a second user.

Systems and methods for automated anomalous behavior detection and risk-scoring individuals

Systems and methods for managing cybersecurity for an entity are disclosed. An example method includes providing a content portal to a user configured to display a security risk profile via a generated GUI; receiving, via the generated GUI, a first input from the user comprising a selection of a component identified in the security risk profile and a response parameter; providing, via the generated GUI, parameters for a targeted scan of the selected component; receiving, via the generated GUI, a second input from the user comprising a selection of a confirmation of the parameters; identifying a vulnerability associated with a first property or a second property from device connectivity data based on the parameters; initiating the targeted scan of the selected component associated with the vulnerability; determining a result of the targeted scan; updating the security risk profile; and updating a multi-dimensional score based on the updated security risk profile.

Security model utilizing multi-channel data with risk-entity facing cybersecurity alert engine and portal

The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods of determining network segmentation. The innovation can search a network to determine a set of network entities, the network entities belonging to the network, and determine network factors of each network entity in the set of network entities. The innovation can evaluate each network factor and determine segmentation candidates based on the evaluation of each network factor. The innovation can determine a risk ranking for each network factor for each network entity and aggregate each risk ranking into a segmentation score for each network entity. The innovation can determine a segmentation candidate when a network entity segmentation score satisfies a threshold score. The innovation can generate a sub-network that is part of the network for the segmentation candidate, and transfer the segmentation candidate to the sub-network.

Network segmentation

Network entities of a network system are managed in an end-of-life context. A network system is scanned to determine network entities such as hardware devices and/or software applications. A network entity can be identified as vulnerable based on end-of-life data. A risk score for the vulnerable network entity is computed based on the end-of-life data and optionally other factors, and a potentially mitigating action is determined based on the risk score.

End-of-life management system

Systems, methods, and computer-readable storage media are utilized to analyze multi-channel data based on a security model in a computer network environment. One system includes a plurality of data channels configured to access entity data and a processing circuit communicatively coupled to a data channel of the plurality of data channels, the processing circuit configured to identify at least one vulnerability, determine an impact of the at least one vulnerability, assign the first property to a first cybersecurity dimension, generate a cybersecurity risk score based at least on the impact of the at least one vulnerability, and generate a multi-dimensional score for a target computer network environment based on the cybersecurity risk score.

Security model utilizing multi-channel data

Provided are a universal software installer and/or uninstaller. The universal software installer determines a structure of the software to be installed and verifies all necessary software elements are applied or installed on the endpoint during the install. The universal software uninstaller determines a structure of the software to be uninstalled and verifies all related software elements are removed from the endpoint. The universal software installer and/or uninstaller is independent of an operating system platform executing on the endpoint.

Universal installer and uninstaller

The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods of autonomous asset configuration modeling and management. The innovation includes probing elements of a networked architecture to compile information about elements in the networked architecture. The innovation learns a configuration for the at least one element in the environment based on the probing and determines vulnerabilities in the learned configuration. The innovation develops a threat model based on the learned configuration. The innovation applies the threat model to the elements of the networked architecture and deploys a configuration that resolves the vulnerabilities based on the threat model to the elements in the networked architecture. The threat model can be developed over time using machine learning concepts and deep learning of data sources associated with the elements and vulnerabilities.

Autonomous configuration modeling and management

Systems and methods for vulnerability remediation based on a dynamic security model are disclosed. Device connectivity data for an entity external to an identifier entity is received by the identifier entity. A vulnerability is identified and risk-scored based on a property parsed from the device connectivity data. The identifier entity may execute an automatic action to prevent the identifier entity from receiving electronic communications from the affected component of the external entity. Further, based on the risk score meeting various parameters, a hyperlink is generated by the identifier entity and provided to the external entity. The hyperlink may include a remediation executable parametrized using the property parsed from the device connectivity data. The remediation executable may include a reference to a patch structured to remediate the vulnerability. Once the external entity remediates the vulnerability, the external entity may initiate a rescan of its affected component.

Systems and methods that facilitate operational support for network infrastructures are discussed. The disclosed system and method facilitate a unified view of the current state of the network and networked devices including real-time log monitoring and for providing metrics for long term system planning. One such method can include the acts of automatically discovering a device deployed on a network, receiving device and network related data in real-time, determining whether a device is authorized, terminating device network access, filtering device data, validating device configuration, configuring a device and providing an output for use by a user. The disclosed system and method can be utilized, for example, to reduce the time involved in troubleshooting and resolving network issues, for establishing a baseline for network performance and for network capacity planning.

Operational support for network infrastructures

Blind spots in a network system are identified and eliminated. Synthetic transactions are generated and transmitted across a network system, and at least a portion of the synthetic transactions is captured. Parts of the synthetic transactions that were not captured can be determined and employed to generate a logical security map of the network system based on the captured synthetic transactions. At least one blind spot can be identified from in the logical security map of the network system, and a solution determined to eliminate the at least one blind spot. Subsequently, the solution is implemented for the network system to eliminate the blind spot.

Growing community of inventors

Huntersville, NC, United States of America

Peter Anatole Makohon