Abstract: The technology disclosed includes a system to reduce clutter when displaying a security analysis graph of nodes and edges. Simple chains of nodes do not have branches and are equivalent when they have the same length, connection types and endpoints. First, second and potentially more simple chains can be aggregated for display. A third and potentially more simple chains can be excluded from aggregation based on an accumulated risk analysis score. The excluded simple chain can readily be called to an analyst's attention.

Abstract: A multi-tenant cloud native system for providing network connections between a plurality of gateway endpoints using tags and secure tunnels. The system includes an end-user device, a cloud control plane, and a cloud provider. The end-user device includes a client endpoint providing a request for establishing a network connection with a service endpoint of the gateway endpoint. Zones and tenants are identified from the request. Tags are assigned to the gateway endpoints in the network based on a tag policy. Connectivity of the tags and tunnels between the gateway endpoint are identified from network traffic of devices corresponding to the gateway endpoints. A database of devices with device addresses is identified to determine routes between the gateway endpoints. A secure tunnel is determined from the plurality of tunnels based on the tags corresponding to the tenant and the network connection is established via the secure tunnel using the routes.

Abstract: A policy-controlled access system comprising a client device running a local application, A mid-link server monitors network traffic from the client device. The network traffic includes third-party content accessed by a user on the client device. A request for data from the end-user is received using the local application, a category associated with the request for the data is determined, and a plurality of policies associated with access to the data is determined based on the category. A machine-learning based Uniform Resource Locator (URL) score associated with the data is determined based on URLs extracted from user activities. A machine learning based policy engine preference is generated based on priority levels of the plurality of policies. The access to the data is provided based on the machine-learning based URL score in accordance with the machine learning based policy engine preference.

Abstract: A system for providing policy-controlled communication over the Internet includes a client endpoint function that executes on a client device while coupled to a first VPN tunnel, a service endpoint function that operates a remote service of a plurality of remote services, and a mid-link server coupled to the first VPN tunnel and a second VPN tunnel. The client endpoint function includes a first VPN endpoint component, and the service endpoint function includes a second VPN endpoint component. A router component operates to route network packet traffic between the first and second VPN tunnels via a route specified by a plurality of policies, an inspection component that analyzes network packet traffic in accordance with the plurality of policies. The plurality of policies for the network packet traffic and the content mediation selected dynamically on the basis of one or more of a user, an application, an endpoint, and a session.

Abstract: The disclosed technology teaches facilitate User and Entity Behavior Analytics (UEBA) by classifying a file being transferred as encrypted or not. The technology involves monitoring movement of a files by a user over a wide area network, detecting file encryption for the files using a trained classifier, wherein the detecting includes processing by the classifier some or all of the following features extracted from each of the files: a chi-square randomness test; an arithmetic mean test; a serial correlation coefficient test; a Monte Carlo-Pi test; and a Shannon entropy test, counting a number of the encrypted files moved by the user in a predetermined period, comparing a predetermined maximum number of encrypted files allowed in the predetermined period to the count of the encrypted files moved by the user and detecting that the user has moved more encrypted files than the predetermined maximum number, and generating an alert.

Abstract: The technology disclosed enables metadata-based policy enforcement for requests that do not include metadata relevant to a policy. In a particular example, a method provides, in a network security system interposed between clients and a cloud application, receiving an incoming request from a client directed towards the cloud application. In response to determining that the incoming request lacks metadata for enforcement of a policy, the method includes transmitting a synthetic request to obtain the metadata from the cloud application and receiving a response to the synthetic request. The response provides the metadata. The method further includes applying the policy to the incoming request based on the metadata.

Abstract: A predetermined credential system for remote administrative operating system (OS) authorization and policy control is disclosed. Administrative activities are packaged in single-use downloaded software. When executed, the administrative access to the OS is activated before completing the administrative activities. The admin credential is encrypted in a wrapped program. A payload program and administrative credentials are extracted from a wrapped program. The payload program adds functionality or affects policies and/or change update settings and configuration selected for an end user computer or a group of end user computers.

Abstract: Systems and methods for risk assessment of a computer network are described. In one embodiment a first static risk score corresponding to a first computing device is computed. A connectivity map corresponding to the first computing device is determined. Communication performed by the first computing device via the connectivity map is analyzed, and a first dynamic risk score corresponding to the first computing device is computed. The first static risk score and the first dynamic risk score are combined to generate a first total risk score for the first computing device. A second total risk score for a second computing device is determined. The first total risk score and the second total risk score are aggregated into an aggregate risk score. A risk assessment of the computer network is determined based on the aggregate risk score.

Abstract: A cloud network for automatically provisioning a user directory in a multi-tenant system. User attributes for configuration of the user directory and groups associated with a plurality of end-users are received from a local application on an end-user device. A program module integrates with an external application and the user interface allows integration with a mid-link server. User policies and group policies associated with the plurality of end-users are determined. A high-risk user from the plurality of end-users is determined using the external application. A threat is determined associated with an end-user based on a type of the threat, a threat level is determined based on the type of the threat, and the threat level is compared to a threshold level, the threshold level categorizes the end-user as the high-risk user. The user directory is deployed using a snippet based on the user policies and the group policies.

Abstract: A control plane system for providing data exchange between a plurality of gateway endpoints using a secure tunnel between the gateway endpoints. The system includes an end-user device, a cloud control plane, and a cloud provider. The end-user device includes a client endpoint providing a request for accessing data using a gateway device by sending data packets. The cloud control plane uses a data plane and a control plane for provisioning the request. The control plane is isolated from the data plane. Routing information of network traffic is received, a tenant associated with the request is identified and isolated. A network policy associated with the access to the data is identified based on the network patterns. The network policy specifies routing for access to the data and the secure tunnel. The access to the data is provided from the cloud provider to the client endpoint on the gateway device.

Abstract: The technology disclosed includes a system to efficiently classify sensitivity of document generated by and downloaded from cloud-based provider services. The system monitors network traffic at a document-generation initiating endpoint and receives a web page identifying the document generated. The system parses the network traffic that selects the document for download, based on the user selecting a link, and intercepts a document handle in an API parameter string used to download the document. The system interprets the document handle to analyze sensitivity of the document to assign a sensitive classification to the document. The sensitivity classification is encoded into the document header metadata. The encoded sensitivity classification can be used to enhance security, for example, preventing data exfiltration.

Abstract: The technology disclosed teaches incident-driven and user-targeted data loss prevention that includes a CASB controlling infiltration via cloud-based services storing documents in use by organization users, by monitoring manipulation of the documents. The CASB identifies the cloud-based services that the particular user has access to and at least one document location on the cloud-based services to inspect for sensitive documents, in response to receiving an indication that user credentials have been compromised. The CASB performs deep inspection of documents identified as stored at the location and detects at least some sensitive documents. Based on the detected sensitive documents, the CASB determines an exposure for the organization due to the particular user.

Abstract: Disclosed is distributed routing and load balancing in a dynamic service chain, receiving a packet at a first service instance, including a NSH imposed on the by a service classifier. The NSH includes a stream affinity code consistent for packets in a stream. The method also includes processing the packet at the first instance where the instance performs a first service in a service chain that includes second and third services. The first service instance accesses a flow table using the stream affinity code to select a second service instance performing the second service from among service instances performing the second service, and the first instance routes the packet to the selected second service instance upon egress from the first service instance. The method can include hashing the stream affinity code to access the flow table and access an available instance using the hash as a key to a CHT.

Abstract: The technology disclosed describes a network security system that is configured to configure a synthetic request with an object identifier, and to inject the synthetic request into an application session to transmit the synthetic request to a cloud application. The synthetic request is configured to retrieve object metadata about the object using the object identifier. The network security system is further configured to receive from the cloud application a response to the synthetic request. The response supplies the object metadata.

Abstract: The technology disclosed relates to a method, system, and non-transitory computer-readable media that trains a cloud traffic classifier to classify cross-application communications as malicious command and control (C2) traffic or benign cloud traffic. The training uses blocks of malicious Hypertext Transfer Protocol (HTTP) transactions targeted at a plurality of cloud applications by a plurality of clients prequalified as malicious command and control (C2) cloud traffic, and also blocks of benign HTTP transactions targeted at the plurality of cloud applications by the plurality of clients prequalified as benign cloud traffic. A cloud traffic classifier is trained on the cross-application malicious training example set and on the cross-application benign training example set by processing the blocks of the malicious and benign HTTP transactions as inputs, and generating outputs that classify the training examples as respectively malicious C2 cloud traffic or benign cloud traffic.

Abstract: A policy-controlled communication system including a plurality of client devices establishing a secure session with remote instances on a web server using a protocol. The system includes a policy component with a set of policies customized based on parameters. The policies specify configuration settings of encryption protocols for content security on a client device. A local application on the client device selects a cloud service. A mid-link server includes a security developer to determine an encryption link to deliver the cloud service to the client device and a linker to select a session protocol for establishing the secure session between the client device and the web server based on the set of policies. The policies are modified when the encryption link does not meet the set of policies. The router establishes via the encryption link the secure session based on the session protocol and the modified policies.

Abstract: The disclosed technology teaches training a classifier that classifies a file being transferred as encrypted or not. The technology involves accessing a plurality of training sample files, each of which is accompanied by a label of encrypted or not encrypted, sampling a configurable number of bytes of each respective file, generating features from the sampled bytes, including generating at least three of the following features: a chi-square randomness test; an arithmetic mean test; a serial correlation coefficient test; a Monte Carlo-Pi test; a Shannon entropy test; applying the generated features to train coefficients of a classifier algorithm to classify the sample files as encrypted or not encrypted; and saving the trained coefficients and classifier, whereby the classifier is trained to classify the sample files as encrypted or not encrypted.

Abstract: The disclosed technology teaches facilitate User and Entity Behavior Analytics (UEBA) by classifying a file being transferred as encrypted or not. The technology involves monitoring movement of a files by a user over a wide area network, detecting file encryption for the files using a trained classifier, wherein the detecting includes processing by the classifier some or all of the following features extracted from each of the files: a chi-square randomness test; an arithmetic mean test; a serial correlation coefficient test; a Monte Carlo-Pi test; and a Shannon entropy test, counting a number of the encrypted files moved by the user in a predetermined period, comparing a predetermined maximum number of encrypted files allowed in the predetermined period to the count of the encrypted files moved by the user and detecting that the user has moved more encrypted files than the predetermined maximum number, and generating an alert.

Abstract: A policy-controlled authorization system including a local application on a client device, a policy component including a plurality of policies, and a mid-link server, coupled to the client device is provided. A request for access to a service using a token is provided by the local application. A correlator correlates the token with the plurality of tokens for identifying a policy from the plurality of policies associated with the token. A token inspector authorizes the token for accessing the service based on the correlation. Based on the authorization, either the token is authorized for access to the service via the remote application, or the token is blocked when unauthorized to prevent access to the service. Confidence scores are assigned to each token based on their categories, compliance with the policies, and a threat level. The confidence scores indicate need to re-authorize the tokens and/or disable them temporarily.

Abstract: A cloud service security enforcement system may include a Cloud Access Security Broker (CASB) proxy and a CASB Application Programming Interface (API) endpoint. Upon receipt of a request for a change operation by a user device, the CASB proxy may execute security enforcement and, upon determining the change operation is allowed, transmit a notification of the change operation to the CASB API endpoint and the cloud service. The CASB API endpoint may pre-process for security enforcement of the change operation based on the notification. When the CASB API endpoint receives the notification from the cloud service of the change operation, the CASB API endpoint may finalize the security enforcement using the pre-processing previously done to expedite the security enforcement and reduce the experienced change processing latency.