Zscaler, Inc.

Michael Andrew William Sutton

Narinder Paul

Balakrishna Bhat Bayar

Julien Sobrier

Sriram Natarajan

Karthikeyan Thamilarasu

Srikanth Devarajan

Amit Sinha

Jeff Forristal

A cloud-based method, a behavioral analysis system, and a cloud-based security system can include a plurality of nodes communicatively coupled to one or more users, wherein the plurality of nodes each perform inline monitoring for one of the one or more users for security comprising malware detection and preclusion; and a behavioral analysis system communicatively coupled to the plurality of nodes, wherein the behavioral analysis system performs offline analysis for any suspicious content from the one or more users which is flagged by the plurality of nodes; wherein the plurality of nodes each comprise a set of known malware signatures for the inline monitoring that is periodically updated by the behavioral analysis system based on the offline analysis for the suspicious content.

Systems and methods for dynamic cloud-based malware behavior analysis

The present disclosure provides systems and methods for mobile application security classification and enforcement. In particular, the present invention includes a method, a mobile device, and a distributed security system (e.g., a 'cloud') that is utilized to enforce security on mobile devices communicatively coupled to external networks (i.e., the Internet). Advantageously, the present invention is platform independent allowing it to operate with any current or emerging mobile device. Specifically, preventing malicious applications from running on an end user's mobile device is challenging with potentially millions of applications and billions of user devices; the only effective way to enforce application security is through the network that applications use to communicate.

Systems and methods for mobile application security classification and enforcement

System and methods for injecting content into a response for improving client-side security. The system includes a content injection service external to network edges of at least one system. The content injection service receives a request from a client within the at least one system and identifies or anticipates a potential threat associated with the response. The content injection service is configured to determine an appropriate counter for the identified or anticipated potential threat and in response injects content into the response according to the potential or anticipated threat identified.

Web security via response injection

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Reston, VA, United States of America

Michael Andrew William Sutton