Sophos Limited

Emc Corporation

Emc IP Holding Company LLC

Karl Ackerman

Andrew James Thomas

Kenneth D Ray

Lawrence N Friedman

Daniel Stutz

James Douglas Bean

Yedidya Dotan

Mark David Harris

Simon Neil Reed

Edward W Vipond

William Duane

Russell Humphries

Yong Qiao

Daniel A Wilder

Ari Juels

Ronald L Rivest

Marten Van Dijk

Daniel Salvatore Schiappa

Roy Hodgman

Dmitri Pal

Alex Vaystikh

Oleg Freylafert

John Edward Tyrone Shaw

Fraser Howard

Andrew Nanopoulos

Piers Bowness

Marco Ciaffi

Anton Khitrenovich

Erik Jan Loman

Ross McKerchar

Dmitri Samosseiko

Robert Black

Daniel T Cohen

Shane D Rice

Kerav Vaidya

Craig Paradis

Gali Kedar Ratson

Markus Jakobsson

Burt Kaliski

Roy Dagan

Mark Anthony Russo

Thomas John Walsh

Christoph Georg Hoyer

Johan Petter Nordwall

Mirco Stratmann

Emily Shen

Abraham Zeev Rosen

An endpoint in an enterprise network is instrumented with sensors to detect security-related events occurring on the endpoint. Event data from these sensors is augmented with contextual information about, e.g., a source of each event in order to facilitate improved correlation, analysis, and visualization at a threat management facility for the enterprise network.

Data augmentation for threat investigation in an enterprise network

Disclosed herein is a technique for detecting potential phishing attacks by monitoring outbound web traffic from an endpoint, along with inbound electronic mail traffic addressed to a user of the endpoint. With this information, a search can be performed for possible sources in the web traffic of a request for a hyperlink located in the inbound mail traffic, and when no source is located, phishing remediation can be performed, including restrictions on access to the hyperlink at an endpoint operated by the user.

Detecting phishing attacks

Security is improved by adding a security heartbeat for and endpoint as a factor in a multi-factor authentication system. The security heartbeat may be used directly as an authentication factor, e.g., where the heartbeat provides a reliable and verifiable indication of identity, or the security heartbeat may be used as a gating input for some other verification method, e.g., where a text message with a temporary security code can only be transmitted to a user when the user's endpoint is providing a secure heartbeat.

Multi-factor authentication

A firewall uses information about an application that originates a network request to determine whether and how to forward the request over a network. The firewall may more generally rely on the identity of the originating application, the security state of the originating application, the security state of the endpoint, and any other information that might provide an indication of malicious activity, to make routing and forwarding decisions for endpoint-originated network traffic.

Application firewall

A computer-implemented method includes training a machine-learning model, using a training dataset that distinguishes between critical systems and non-critical systems, to classify a particular computer system as critical or non-critical, wherein a label is applied to the particular computer system during the training that identifies the particular computer system as critical or non-critical, and wherein parameters that describe the critical systems or non-critical systems are used as features during the training. The method further includes receiving an input dataset that describes a plurality of computer systems in the enterprise environment. The method further includes outputting, using the trained machine-learning model, an identification of one or more critical systems of the plurality of computer systems within the enterprise environment and an identification of one or more non-critical systems of the plurality of computer systems within the enterprise environment, wherein each identification is associated with a confidence level.

Implementing a machine-learning model to identify critical systems in an enterprise environment

A threat management system provides a collection of queries for investigating security issues within an enterprise. Useful inferences are drawn about the value of different queries, and about the security posture of the enterprise, by monitoring contextual activity such as the popularity and context of query usage, patterns of end user modification to queries, and post-query activity.

Live discovery of enterprise threats based on security query activity

When security-related behavior is detected on an endpoint, e.g., through a local security agent executing on the endpoint, a threat management facility associated with the endpoint can interact with a user via a second local security agent on a second endpoint in order to solicit verification, authorization, authentication or the like related to the behavior. In one aspect, an administrator for an enterprise managed by the threat management facility may verify, authorize, or otherwise approve the detected behavior using this technique. In another aspect, a user of the device may use this infrastructure to approve of a potentially risky behavior on one device by using a verification procedure on a second device associated with the user.

Behavior detection and verification

Various aspects related to threat management are disclosed. An example method includes monitoring network traffic on a computer network that includes a plurality of endpoints, identifying a software application executing on at least one endpoint from one or more of the sent data or the received data, where execution of the software application is associated with a startup time window and a post-startup time window, determining a security status score for the at least one endpoint based on a comparison of the sent data and the received data with a known pattern of network activity associated with the software application, wherein the known pattern of network activity is based upon the startup time window of the software application, determining a threat status for the at least one endpoint based on the security status score, and, generating an indication of the threat status for the at least one endpoint.

Security threat monitoring for network-accessible devices

Malware uses various techniques to detect a sandbox environment so that malicious code can avoid execution in closely monitored contexts that might otherwise trigger detection and remediation. A security system is dynamically updated to exploit these anti-sandbox techniques, e.g., by causing endpoints to mimic sandbox environments in a manner that discourages malware execution on the endpoint, and by updating sandboxes to alter or hide sandbox detection triggers.

Dynamic sandbox scarecrow for malware management

An endpoint in an enterprise network is monitored, and when a potential trigger for a distributed denial of service (DDoS) attack is followed by an increase in network traffic from the endpoint to a high reputation network address, the endpoint is treated as a DDoS service bot and isolated from the network until remediation can be performed.

Detecting triggering events for distributed denial of service attacks

In a threat management platform, a number of endpoints log events in an event data recorder. A local agent filters this data and feeds a filtered data stream to a central threat management facility. The central threat management facility can locally or globally tune filtering by local agents based on the current data stream, and can query local event data recorders for additional information where necessary or helpful in threat detection or forensic analysis. The central threat management facility also stores and deploys a number of security tools such as a web-based user interface supported by machine learning models to identify potential threats requiring human intervention and other models to provide human-readable context for evaluating potential threats.

Enterprise network threat detection

An endpoint in a network periodically generates a heartbeat encoding health state information and transmits this heartbeat to other network entities. Recipients of the heartbeat may use the health state information to independently make decisions about communications with the source endpoint, for example, by isolating the endpoint to prevent further communications with other devices sharing the network with the endpoint. Isolation may be coordinated by a firewall or gateway for the network, or independently by other endpoints that receive a notification of the compromised health state.

Server-client authentication with integrated status update

Growing community of inventors

Topsfield, MA, United States of America

Karl Ackerman