150P that is both part of the cloud-based system 100 and part of a private network. Further, of note, the enforcement node described herein may simply be referred to as a node or cloud node. Also, the terminology enforcement node 150 is used in the context of the cloud-based system 100 providing cloud-based security. In the context of secure, private application access, the enforcement node 150 can also be referred to as a service edge or service edge node. Also, a service edge node 150 can be a public service edge node (part of the cloud-based system 100) separate from an enterprise network or a private service edge node (still part of the cloud-based system 100) but hosted either within an enterprise network, in a data center 114, in a branch office 118, etc. Further, the term nodes as used herein with respect to the cloud-based system 100 (including enforcement nodes, service edge nodes, etc.) can be one or more servers, including physical servers, virtual machines (VM) executed on physical hardware, etc., as described above. The service edge node 150 can also be a Secure Access Service Edge (SASE).

The enforcement nodes 150 are full-featured secure internet gateways that provide integrated internet security. They inspect all web traffic bi-directionally for malware and enforce security, compliance, and firewall policies, as described herein, as well as various additional functionality. In an embodiment, each enforcement node 150 has two main modules for inspecting traffic and applying policies: a web module and a firewall module. The enforcement nodes 150 are deployed around the world and can handle hundreds of thousands of concurrent users with millions of concurrent sessions. Because of this, regardless of where the users 102 are, they can access the Internet 104 from any device, and the enforcement nodes 150 protect the traffic and apply corporate policies. The enforcement nodes 150 can implement various inspection engines therein, and optionally, send sandboxing to another system. The enforcement nodes 150 include significant fault tolerance capabilities, such as deployment in active-active mode to ensure availability and redundancy as well as continuous monitoring.

In an embodiment, customer traffic is not passed to any other component within the cloud-based system 100, and the enforcement nodes 150 can be configured never to store any data to disk. Packet data is held in memory for inspection and then, based on policy, is either forwarded or dropped. Log data generated for every transaction is compressed, tokenized, and exported over secure Transport Layer Security (TLS) connections to the log routers 154 that direct the logs to the storage cluster 156, hosted in the appropriate geographical region, for each organization. In an embodiment, all data destined for or received from the Internet is processed through one of the enforcement nodes 150. In another embodiment, specific data specified by each tenant, e.g., only email, only executable files, etc., is processed through one of the enforcement nodes 150.

Each of the enforcement nodes 150 may generate a decision vector D=[d1, d2, . . . , dn] for a content item of one or more parts C=[c1, c2, . . . , cm]. Each decision vector may identify a threat classification, e.g., clean, spyware, malware, undesirable content, innocuous, spam email, unknown, etc. For example, the output of each element of the decision vector D may be based on the output of one or more data inspection engines. In an embodiment, the threat classification may be reduced to a subset of categories, e.g., violating, non-violating, neutral, unknown. Based on the subset classification, the enforcement node 150 may allow the distribution of the content item, preclude distribution of the content item, allow distribution of the content item after a cleaning process, or perform threat detection on the content item. In an embodiment, the actions taken by one of the enforcement nodes 150 may be determinative on the threat classification of the content item and on a security policy of the tenant to which the content item is being sent from or from which the content item is being requested by. A content item is violating if, for any part C=[c1, c2, . . . , cm] of the content item, at any of the enforcement nodes 150, any one of the data inspection engines generates an output that results in a classification of “violating.”

The central authority 152 hosts all customer (tenant) policy and configuration settings. It monitors the cloud and provides a central location for software and database updates and threat intelligence. Given the multi-tenant architecture, the central authority 152 is redundant and backed up in multiple different data centers. The enforcement nodes 150 establish persistent connections to the central authority 152 to download all policy configurations. When a new user connects to an enforcement node 150, a policy request is sent to the central authority 152 through this connection. The central authority 152 then calculates the policies that apply to that user 102 and sends the policy to the enforcement node 150 as a highly compressed bitmap.

The policy can be tenant-specific and can include access privileges for users, websites and/or content that is disallowed, restricted domains, DLP dictionaries, etc. Once downloaded, a tenant's policy is cached until a policy change is made in the management system 120. The policy can be tenant-specific and can include access privileges for users, websites and/or content that is disallowed, restricted domains, DLP dictionaries, etc. When this happens, all of the cached policies are purged, and the enforcement nodes 150 request the new policy when the user 102 next makes a request. In an embodiment, the enforcement node 150 exchange “heartbeats” periodically, so all enforcement nodes 150 are informed when there is a policy change. Any enforcement node 150 can then pull the change in policy when it sees a new request.

The cloud-based system 100 can be a private cloud, a public cloud, a combination of a private cloud and a public cloud (hybrid cloud), or the like. Cloud computing systems and methods abstract away physical servers, storage, networking, etc., and instead offer these as on-demand and elastic resources. The National Institute of Standards and Technology (NIST) provides a concise and specific definition which states cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. Cloud computing differs from the classic client-server model by providing applications from a server that are executed and managed by a client's web browser or the like, with no installed client version of an application required. Centralization gives cloud service providers complete control over the versions of the browser-based and other applications provided to clients, which removes the need for version upgrades or license management on individual client computing devices. The phrase “Software as a Service” (SaaS) is sometimes used to describe application programs offered through cloud computing. A common shorthand for a provided cloud computing service (or even an aggregation of all existing cloud services) is “the cloud.” The cloud-based system 100 is illustrated herein as an example embodiment of a cloud-based system, and other implementations are also contemplated.

As described herein, the terms cloud services and cloud applications may be used interchangeably. The cloud service 106 is any service made available to users on-demand via the Internet, as opposed to being provided from a company's on-premises servers. A cloud application, or cloud app, is a software program where cloud-based and local components work together. The cloud-based system 100 can be utilized to provide example cloud services, including Zscaler Internet Access (ZIA), Zscaler Private Access (ZPA), Zscaler Digital Experience (ZDX), Zscaler Posture Control (ZPC), all from Zscaler, Inc. (the assignee and applicant of the present application). Also, there can be multiple different cloud-based systems 100, including ones with different architectures and multiple cloud services. The ZIA service can provide the access control, threat prevention, and data protection described above with reference to the cloud-based system 100. ZPA can include access control, microservice segmentation, etc. The ZDX service can provide monitoring of user experience, e.g., Quality of Experience (QoE), Quality of Service (QoS), etc., in a manner that can gain insights based on continuous, inline monitoring. For example, the ZIA service can provide a user with Internet Access, and the ZPA service can provide a user with access to enterprise resources instead of traditional Virtual Private Networks (VPNs), namely ZPA provides Zero Trust Network Access (ZTNA). ZPC is a Cloud-Native Application Protection Platform (CNAPP) which is a new category of security products, encompassing the functionality previously found in Cloud Security Posture Management (CSPM) and Cloud Workload Protection Platform (CWPP) products and more. Those of ordinary skill in the art will recognize various other types of cloud services 106 are also contemplated. Also, other types of cloud architectures are also contemplated, with the cloud-based system 100 presented for illustration purposes.

Example Server Architecture

FIG. 3 is a block diagram of a server 200, which may be used in the cloud-based system 100, in other systems, or standalone. For example, the enforcement nodes 150 and the central authority 152 may be formed as one or more of the servers 200. The server 200 may be a digital computer that, in terms of hardware architecture, generally includes a processor 202, input/output (I/O) interfaces 204, a network interface 206, a data store 208, and memory 210. It should be appreciated by those of ordinary skill in the art that FIG. 3 depicts the server 200 in an oversimplified manner, and a practical embodiment may include additional components and suitably configured processing logic to support known or conventional operating features that are not described in detail herein. The components (202, 204, 206, 208, and 210) are communicatively coupled via a local interface 212. The local interface 212 may be, for example, but not limited to, one or more buses or other wired or wireless connections, as is known in the art. The local interface 212 may have additional elements, which are omitted for simplicity, such as controllers, buffers (caches), drivers, repeaters, and receivers, among many others, to enable communications. Further, the local interface 212 may include address, control, and/or data connections to enable appropriate communications among the aforementioned components.

The processor 202 is a hardware device for executing software instructions. The processor 202 may be any custom made or commercially available processor, a Central Processing Unit (CPU), an auxiliary processor among several processors associated with the server 200, a semiconductor-based microprocessor (in the form of a microchip or chipset), or generally any device for executing software instructions. When the server 200 is in operation, the processor 202 is configured to execute software stored within the memory 210, to communicate data to and from the memory 210, and to generally control operations of the server 200 pursuant to the software instructions. The I/O interfaces 204 may be used to receive user input from and/or for providing system output to one or more devices or components.

The network interface 206 may be used to enable the server 200 to communicate on a network, such as the Internet 104. The network interface 206 may include, for example, an Ethernet card or adapter or a Wireless Local Area Network (WLAN) card or adapter. The network interface 206 may include address, control, and/or data connections to enable appropriate communications on the network. A data store 208 may be used to store data. The data store 208 may include any of volatile memory elements (e.g., random access memory (RAM, such as DRAM, SRAM, SDRAM, and the like)), nonvolatile memory elements (e.g., ROM, hard drive, tape, CDROM, and the like), and combinations thereof.

Moreover, the data store 208 may incorporate electronic, magnetic, optical, and/or other types of storage media. In one example, the data store 208 may be located internal to the server 200, such as, for example, an internal hard drive connected to the local interface 212 in the server 200. Additionally, in another embodiment, the data store 208 may be located external to the server 200 such as, for example, an external hard drive connected to the I/O interfaces 204 (e.g., SCSI or USB connection). In a further embodiment, the data store 208 may be connected to the server 200 through a network, such as, for example, a network-attached file server.

The memory 210 may include any of volatile memory elements (e.g., random access memory (RAM, such as DRAM, SRAM, SDRAM, etc.)), nonvolatile memory elements (e.g., ROM, hard drive, tape, CDROM, etc.), and combinations thereof. Moreover, the memory 210 may incorporate electronic, magnetic, optical, and/or other types of storage media. Note that the memory 210 may have a distributed architecture, where various components are situated remotely from one another but can be accessed by the processor 202. The software in memory 210 may include one or more software programs, each of which includes an ordered listing of executable instructions for implementing logical functions. The software in the memory 210 includes a suitable Operating System (O/S) 214 and one or more programs 216. The operating system 214 essentially controls the execution of other computer programs, such as the one or more programs 216, and provides scheduling, input-output control, file and data management, memory management, and communication control and related services. The one or more programs 216 may be configured to implement the various processes, algorithms, methods, techniques, etc. described herein.

Example User Device Architecture

FIG. 4 is a block diagram of a user device 300, which may be used with the cloud-based system 100 or the like. Specifically, the user device 300 can form a device used by one of the users 102, and this may include common devices such as laptops, smartphones, tablets, netbooks, personal digital assistants, MP3 players, cell phones, e-book readers, IOT devices, servers, desktops, printers, televisions, streaming media devices, and the like. The user device 300 can be a digital device that, in terms of hardware architecture, generally includes a processor 302, I/O interfaces 304, a network interface 306, a data store 308, and memory 310. It should be appreciated by those of ordinary skill in the art that FIG. 4 depicts the user device 300 in an oversimplified manner, and a practical embodiment may include additional components and suitably configured processing logic to support known or conventional operating features that are not described in detail herein. The components (302, 304, 306, 308, and 302) are communicatively coupled via a local interface 312. The local interface 312 can be, for example, but not limited to, one or more buses or other wired or wireless connections, as is known in the art. The local interface 312 can have additional elements, which are omitted for simplicity, such as controllers, buffers (caches), drivers, repeaters, and receivers, among many others, to enable communications. Further, the local interface 312 may include address, control, and/or data connections to enable appropriate communications among the aforementioned components.

The processor 302 is a hardware device for executing software instructions. The processor 302 can be any custom made or commercially available processor, a CPU, an auxiliary processor among several processors associated with the user device 300, a semiconductor-based microprocessor (in the form of a microchip or chipset), or generally any device for executing software instructions. When the user device 300 is in operation, the processor 302 is configured to execute software stored within the memory 310, to communicate data to and from the memory 310, and to generally control operations of the user device 300 pursuant to the software instructions. In an embodiment, the processor 302 may include a mobile optimized processor such as optimized for power consumption and mobile applications. The I/O interfaces 304 can be used to receive user input from and/or for providing system output. User input can be provided via, for example, a keypad, a touch screen, a scroll ball, a scroll bar, buttons, a barcode scanner, and the like. System output can be provided via a display device such as a Liquid Crystal Display (LCD), touch screen, and the like.

The network interface 306 enables wireless communication to an external access device or network. Any number of suitable wireless data communication protocols, techniques, or methodologies can be supported by the network interface 306, including any protocols for wireless communication. The data store 308 may be used to store data. The data store 308 may include any of volatile memory elements (e.g., random access memory (RAM, such as DRAM, SRAM, SDRAM, and the like)), nonvolatile memory elements (e.g., ROM, hard drive, tape, CDROM, and the like), and combinations thereof. Moreover, the data store 308 may incorporate electronic, magnetic, optical, and/or other types of storage media.

The memory 310 may include any of volatile memory elements (e.g., random access memory (RAM, such as DRAM, SRAM, SDRAM, etc.)), nonvolatile memory elements (e.g., ROM, hard drive, etc.), and combinations thereof. Moreover, the memory 310 may incorporate electronic, magnetic, optical, and/or other types of storage media. Note that the memory 310 may have a distributed architecture, where various components are situated remotely from one another but can be accessed by the processor 302. The software in memory 310 can include one or more software programs, each of which includes an ordered listing of executable instructions for implementing logical functions. In the example of FIG. 3, the software in the memory 310 includes a suitable operating system 314 and programs 316. The operating system 314 essentially controls the execution of other computer programs and provides scheduling, input-output control, file and data management, memory management, and communication control and related services. The programs 316 may include various applications, add-ons, etc. configured to provide end user functionality with the user device 300. For example, example programs 316 may include, but not limited to, a web browser, social networking applications, streaming media applications, games, mapping and location applications, electronic mail applications, financial applications, and the like. In a typical example, the end-user typically uses one or more of the programs 316 along with a network such as the cloud-based system 100.

User Device Application for Traffic Forwarding and Monitoring

FIG. 5 is a network diagram of the cloud-based system 100 illustrating an application 350 on user devices 300 with users 102 configured to operate through the cloud-based system 100. Different types of user devices 300 are proliferating, including Bring Your Own Device (BYOD) as well as IT-managed devices. The conventional approach for a user device 300 to operate with the cloud-based system 100 as well as for accessing enterprise resources includes complex policies, VPNs, poor user experience, etc. The application 350 can automatically forward user traffic with the cloud-based system 100 as well as ensuring that security and access policies are enforced, regardless of device, location, operating system, or application. The application 350 automatically determines if a user 102 is looking to access the open Internet 104, a SaaS app, or an internal app running in public, private, or the datacenter and routes mobile traffic through the cloud-based system 100. The application 350 can support various cloud services, including ZIA, ZPA, ZDX, ZPC, etc., allowing the best in class security with zero trust access to internal apps.

The application 350 is configured to auto-route traffic for seamless user experience. This can be protocol as well as application-specific, and the application 350 can route traffic with a nearest or best fit enforcement node 150. Further, the application 350 can detect trusted networks, allowed applications, etc. and support secure network access. The application 350 can also support the enrollment of the user device 300 prior to accessing applications. The application 350 can uniquely detect the users 102 based on fingerprinting the user device 300, using criteria like device model, platform, operating system, etc. The application 350 can support Mobile Device Management (MDM) functions, allowing IT personnel to deploy and manage the user devices 300 seamlessly. This can also include the automatic installation of client and SSL certificates during enrollment. Finally, the application 350 provides visibility into device and app usage of the user 102 of the user device 300.

The application 350 supports a secure, lightweight tunnel between the user device 300 and the cloud-based system 100. For example, the lightweight tunnel can be HTTP-based. With the application 350, there is no requirement for PAC files, an IPSec VPN, authentication cookies, or end user 102 setup.

Identity Power Score

The present disclosure provides systems and methods for an identity power scoring system that assigns each identity in a cloud environment or cloud-based system, human or non-human, a score of 0-100, signifying how privileged the identity is in the context of a cloud account. The scoring system helps identify and prioritize risk associated with specific identities, allowing more optimized methods of protection for information in the cloud-based system. In addition, the identity is scored 0-100 in categories such as compute admin, secret admin, storage admin, and others of the like. it will be appreciated that the power score range can be any range, and the exemplary power score range of 0-100 is a non-limiting example.

Identities in a cloud environment or cloud-based system are varied and are used in various access scenarios, such as root accounts for extremely privileged tasks, Identity and Access Management (IAM) users with access keys for routine scripts, Elastic Compute Cloud (EC2) instances with roles, etc. Each of these identities can be assigned permissions in various different ways such as policies, group policies, inline policies, assumed roles, etc. To detect risk in a public cloud, it is critical to identify powerful users. For example, an EC2 instance that is publicly exposed and attached is a powerful role.

The scoring system helps to assess the power of an identity in the following manners. All cloud entitlements for any given identity are expended (action x resource) and calculated considering roles, policies, guardrails, deny policies, etc. Each entitlement is classified to its category such as compute, storage, etc. For each cloud account in scope, systems calculate all the possible entitlements for that account (unique action x resource pairs). Thus, the present systems and methods fully expand the span of what is possible to be done with a particular cloud account, followed by what is possible to be done by this cloud account for each category. For each identity with permissions/entitlements, systems calculate what the percentage is of the entitlements the identity has, in relation to the possible entitlements in the cloud account. This generates a value of Pe. Combining domain expertise, methods select the critical entitlements, and a result is a power score greater than or equal to the Pe value. The present disclosure enables systems to identify privileged human identities and enforce authentication controls, identify over privileged non-human identities, discover hidden admins, and govern permission drifts.

Given a customer environment with identities that have access to their cloud resources, the present systems and methods have the ability to score how powerful an identity is. This power should be expressed in a score (i.e., 0-100). For example, a global admin in Azure, or the root user in an Amazon Web Services (AWS) account, will have a score of 100. In contrast, an identity without any permissions (i.e., can only login to the console) will have a power score of 0. The purpose of this power score is to provide the score as a token that can be used in custom rules. For example, systems can define a rule that alerts to any user with score greater than 80 (or any other threshold) that is not enrolled with Multi-factor Authentication (MFA), or other security features of the like. The score can help assess the severity of an incident/risk that involves an identity. For example, the severity of old access keys for identities will depend on the identity's power score (i.e., category power score or global power score). The score also provides a way for customers to sort and view their most powerful identities. It will be appreciated that in examples such as AWS, roles can be assigned power scores in addition to identities.

Various embodiments of the present disclosure aim to help identify a risk associated with users/accounts. While “super-users” are relatively easy to detect, the range of other users in between becomes more difficult to detect/sort without understanding the context of the access. For example, data access may be critical in case of sensitive data, or almost meaningless in case of static, publicly available data. The same goes to workloads and systems. As such, given the entitlements and access of an identity, it is complicated to measure how powerful an identity is, relatively to the use case of a customer.

Various embodiments take advantage of the fact that systems/services have full visibility into the net identity's entitlements to calculate the following parameter of Pe. In short, Pe measures the percentage of entitlements an identity has, in relation to all the possible entitlements in the scope. In that context, all possible entitlements refer to all unique combinations (of action x resource) that can be found in the entitlements in that scope (ignoring grant path and identity elements). The scope can be a given service and a given category, such as a data services category, or an entire tenant (AWS account). A Pr parameter measures the percentage of resources the identity has (any) access to, in relation to all resources in the scope.

The calculation of power score for a given identity is built from the bottom up, leveraging the Pe parameter per service, in the following manner. Identities with a Pe score in the scope of the tenant which is greater than 99 are super admins with a power score of 100. Identities with a Pe score for an IAM service in the scope of the tenant greater than 99 are IAM admins with a power score of 100. For the rest of the identities, embodiments define the admin categories, for which an identity is given a category power score as detailed below. Each admin category is composed of a list of one or more relevant services. For example, data admin is composed of S3, RDS, DynamoDB, etc. Each cloud service belongs to a single admin category only, where, for each admin category, for each cloud service in that category, systems calculate a Pe score (service score) for the identity for the cloud service. For example, looking at an example identity, in the admin category of data admin, the following vector is produced [S3:80, RDS:20, DynamoDB:0, . . . ]. Various embodiments calculate a combined power score for the admin category (category power score), derived from all the Pe scores of the cloud services, in the formula detailed below. In that stage, a power score for the identity in each of the admin categories is derived. For example, an example user has the following scores for the following admin categories of Data Admin: 70, Compute Admin: 40, IAM Admin: 10, . . . etc. Systems proceed to calculate the global power score for the identity, based on the category power score for each admin category, following the formula detailed herein.

The following table provides a list of exemplary admin categories. It will be appreciated that other embodiments of the present disclosure contemplate additional admin categories.

Category

DATA_ADMIN

STORAGE_ADMIN

COMPUTE_ADMIN

IAM_ADMIN

SECURITY_ADMIN

INFRASTRUCTURE_ADMIN

CICD_ADMIN

SECRET_ADMIN

AI_ADMIN

LOG_ADMIN

APPLICATION_ADMIN

COST_ADMIN

OTHER

For each identity with access in an associated scope, the following outputs are contemplated.