Zscaler, Inc.

Pooja Deshmukh

Arun Bhallamudi

Narinder Paul

Siva Udupa

Srikanth Devarajan

John A Chanak

William Fehring

Balakrishna Bhat Bayar

Nikhil Bhatia

Vijay Bulusu

Zhifeng Zhang

Jasbir Singh Kaushal

Naresh Kumar

James Tan

Sumit Guha

Leslie Smith

Santhosh Kumar

Frank Zhang

Apoorva Pasrija

Sravani Manukonda

Iris Gao

Sarthak Saxena

Systems and methods for browser fingerprinting and control for private application protection include monitoring access to one or more private applications; performing one or more compliance checks on any of the user and the browser used to access the one or more private applications; and performing one or more actions based on a result of the one or more compliance checks. These steps are performed in order to prevent users from accessing private applications via compromised or vulnerable browsers.

Browser fingerprinting and control for session protection and private application protection

Systems and methods include, providing a UI for a tenant to input one or more malware and DLP rules, and trusted user exceptions; responsive to a scan by the CASB system of a plurality of users associated with a tenant in a SaaS application where the scan includes identifying malware in content in the SaaS application and performing DLP in the content in the SaaS application based on the one or more malware and DLP rules and trusted user exceptions, maintaining records associated with a plurality of incidents for the malware and the DLP; and providing the UI for the tenant including an analytics view with a plurality of summary tiles including visualizations of the plurality of incidents for the malware and DLP for the tenant and a table listing any of the plurality of incidents for the malware and the DLP for the tenant.

Cloud access security broker user interface and analytics systems and methods

Systems and methods include, responsive to determining a user can access an application via a cloud-based system, wherein the application is in one of a public cloud, a private cloud, and an enterprise network, and wherein the user is remote over the Internet, obtaining a predetermined inspection profile for the user with the inspection profile including a plurality of rules evaluated in an order; performing inspection of the access using the plurality of rules in the order; and responsive to results of any of the plurality of rules, one or more of monitoring, allowing, blocking, and redirecting the access, via the cloud-based system.

Cloud-based web application and API protection from untrusted users and devices

Systems and methods include, responsive to a scan by the CASB system of a plurality of users associated with a tenant in a Software-as-a-Service (SaaS) application where the scan includes identifying malware in content in the SaaS application and performing Data Loss Prevention (DLP) in the content in the SaaS application, maintaining records associated with a plurality of incidents for the malware and the DLP; providing a User Interface (UI) for the tenant including an analytics view with a plurality of summary tiles including visualizations of the plurality of incidents for the malware and the DLP for the tenant; and providing the UI for the tenant including a table listing any of the plurality of incidents for the malware and the DLP for the tenant, including any of unique data objects, unique users internal to the tenant, and unique external entities, associated with the plurality of incidents.

Cloud access security broker user interface systems and methods

Systems and methods include obtaining a profile for an application, wherein the profile includes one or more tenants, rules for use of the application by the one or more tenants, and users for the rules; monitoring a user of a tenant of the one or more tenants inline via a node in a cloud-based system; identifying an application of the one or more applications based on the monitoring and associated rules for the user; and enforcing the associated rules for the user for the application.

Granular SaaS tenant restriction systems and methods

Systems and methods of Exact Data Matching (EDM) include receiving customer specific sensitive data for a customer, wherein the customer specific sensitive data are converted into a plurality of tokens; receiving a configuration for exact data matching of the plurality of tokens; performing inline monitoring of a user associated with the customer; detecting a presence of one or more tokens of the plurality of tokens based on the inline monitoring; and, responsive to the detecting, performing an action based on the configuration.

DLP exact data matching

Systems and methods of Exact Data Matching (EDM) for identifying related tokens in data content using structured signature data implemented in a cloud-based system receiving data sets and customer configuration from a customer, wherein the data sets include customer specific sensitive data from a structured data source with each token represented by a hash value and the customer configuration includes one or more primary keys for a plurality of records in the data sets; distributing the data sets and the customer configuration to a plurality of nodes in the cloud-based system; performing monitoring of content between a client of the customer and an external network; detecting a presence of a plurality of tokens associated with a record in the customer specific sensitive data based on the monitoring; and performing a policy-based action in the cloud-based system based on the detecting.

DLP appliance and method for protecting data sources used in data matching

A cloud-based security system includes a plurality of enforcement nodes connected to one another; a central authority connected to the plurality of enforcement nodes; and a Data Loss Prevention (DLP) service executed between the plurality of enforcement nodes, wherein the DLP service includes one or more DLP rules based on one or more DLP engines for a tenant, and wherein, for the DLP service, a first enforcement node is configured to monitor traffic of a user of the tenant, detect a DLP rule violation based on the one or more DLP rules, and forward DLP incident information to a second enforcement node, and the second enforcement node is configured to transmit the DLP incident information to a server for the tenant, including both DLP triggering content that cause the DLP rule violation and DLP scan metadata.

Data loss prevention incident forwarding

Systems and methods include obtaining an expression for a Data Loss Prevention (DLP) engine, wherein the expression includes one or more DLP dictionaries that evaluate to a score for comparison with a corresponding threshold and one or more logical operators used to combine an evaluation of the one or more DLP dictionaries; storing the expression in a database associated with a DLP service; monitoring traffic from one or more users; evaluating the traffic using the DLP engine and the expression; and determining a DLP trigger based on a result of the expression that is a logical TRUE.

Growing community of inventors

Sunnyvale, CA, United States of America

Pooja Deshmukh