Zscaler ZDTE Dumps

Official EDU-202 materials describe the Engineer path as focusing on advanced architecture, connectivity, platform, access control, cyberthreat protection, data protection, risk management, ZDX, and Zero Trust Automation. The published learning outcomes explicitly include: discussing the architecture of the Zscaler platform and its API infrastructure; configuring advanced connectivity options; and configuring advanced cybersecurity services and Zscaler Digital Experience (ZDX)—including application monitoring, call quality, probes, diagnostics, alerts, and role-based administration. These map directly to options A, C, and D, which align to Zscaler Architecture, Cyberthreat/Access Control Services (IPS, DNS Control, Tenant Restrictions, segmentation), and ZDX content in the EDU-202 outline.

By contrast, Client Connector App Store “version enablement” and controlling which build is available when users manually or automatically update the app is documented as an administration task in the Client Connector help and is typically taught in the Essentials/Administrator (EDU-200) path, not in the Engineer path. Those materials show how to use the App Store to enable builds and control available versions, positioning it as operational client management rather than an advanced Engineer-level topic. Consequently, option B is considered out of scope for EDU-202 in the ZDTE context.

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Zscaler Digital Experience (ZDX) relies on Zscaler Client Connector to collect device and application telemetry from endpoints. Performance metrics (such as device, network, and application scores) are enabled as part of the core ZDX deployment, which explains why the administrator can already see performance data on the dashboard. However, software inventory is an additional inventory feature that must be explicitly enabled in the ZDX administration settings.

ZDX documentation describes an “Inventory Settings” page where administrators must turn on a setting such as “Collect Software Inventory Data.” When this option is enabled and the minimum supported versions of Client Connector and the ZDX module are present, Client Connector begins collecting installed software details and sending this inventory to the ZDX cloud for visualization.

If the collection toggle is left disabled, ZDX will continue to show performance metrics but no entries appear under Software Inventory or related views, even though licensing and versions are otherwise correct. The other options listed either relate to licensing, generic EDR conflicts, or a specific client version and do not match the documented dependency on enabling software-inventory collection. Therefore, the most accurate reason is that the ZDX client (via policy) is not configured to collect inventory data.

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In ZIA, user traffic is first forwarded to a Zscaler Enforcement Node (ZEN), where security and access policies are enforced and transaction logs are generated. Those logs are then sent from the ZEN to the cloud-based Nanolog cluster, which is the highly scalable logging and storage layer used by Zscaler. Nanolog compresses and stores the logs for reporting, analytics, and long-term retention.

To deliver logs to a customer’s SIEM, the Nanolog Streaming Service (NSS) is deployed in the customer environment. NSS establishes a secure, outbound tunnel to the Nanolog service in the Zscaler cloud and subscribes to that customer’s log stream. Nanolog then continuously streams a copy of relevant logs over this secure connection to NSS. NSS receives the logs, converts them into the required output format (for example, syslog or CEF), and forwards them on to the configured SIEM or log receiver.

Option C is the only answer that correctly represents the logical sequence: user traffic through ZEN, ZEN to Nanolog, secure tunnel from NSS, Nanolog streaming to NSS, and finally NSS forwarding to the SIEM.

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The ZIdentity documentation on external identity providers explains that Zscaler supports various third-party IdPs over SAML and OIDC, and then provides specific configuration guides for each provider. For PingOne, Auth0, and OneLogin, the ZIdentity help explicitly describes configuring each as an OpenID Provider (OP) for ZIdentity, clearly stating that they are used to provide SSO via OpenID Connect (OIDC).

By contrast, the ZIdentity guides for Microsoft AD FS consistently describe configuring AD FS “as the SAML Identity Provider (IdP) for ZIdentity,” and the examples focus on SAML assertions, claim rules, and certificate bindings—not OIDC flows. In other words, AD FS is supported in a SAML mode with ZIdentity, but it is not listed among the IdPs configured as OpenID Providers for OIDC-based integrations.

The Digital Transformation Engineer identity modules reinforce this differentiation by mapping external IdPs to either OIDC or SAML in the ZIdentity configuration, and the hands-on labs use Azure/Microsoft Entra ID or PingOne for OIDC examples, while AD FS is shown only in SAML scenarios.

Therefore, among the options listed, Microsoft AD FS is the external IdP that is unsupported by OIDC with Zscaler ZIdentity, making option C the correct answer.

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Zscaler provides specialized Log Streaming Services to export logs from the Zero Trust Exchange into external SIEM or log-analytics platforms for long-term storage and advanced analysis. For Zscaler Private Access (ZPA), the Log Streaming Service (LSS) forwards user activity, user status, App Connector metrics, and other diagnostic logs to a log receiver, which is typically a SIEM, syslog collector, or similar downstream system. Zscaler documentation notes that customers use LSS specifically to store logs beyond the default cloud retention period and to support external analytics and compliance use cases.

On the ZIA side, Nanolog Streaming Service (NSS) fulfills a similar purpose, streaming web and firewall logs from the Zscaler Nanolog cluster into SIEM solutions. Together, these streaming services give organizations centralized visibility and long-term retention while keeping the Zscaler cloud optimized for inline inspection and near-term reporting.

Role-Based Access Control (RBAC) governs who can view or manage configurations, not how logs are exported. The Zero Trust Exchange query or insights interfaces are used for in-portal searching and visualization, and “Log Recovery Service” is not the Zscaler term used for SIEM integration in ZDTE materials. Therefore, Log Streaming Services is the correct answer because it is the named mechanism for streaming Zscaler logs to external SIEM platforms for long-term storage.

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Within the Zscaler Client Connector administration portal, an App Profile defines how the client behaves for a set of users or devices. A key element of any App Profile is the associated Forwarding Profile. The Forwarding Profile tells the Zscaler Client Connector how to handle traffic in different network conditions: for example, whether to send traffic through Z-Tunnel 2.0 to ZIA and/or ZPA, rely on a PAC file, or bypass Zscaler when on trusted networks.

When you create or edit an App Profile, selecting a Forwarding Profile is mandatory because it determines how user traffic will actually reach the Zscaler cloud. Without a Forwarding Profile, the App Profile would not know which forwarding mode to use, and the client would have no consistent instructions on when and how to tunnel or bypass traffic. In practice, customers often define multiple Forwarding Profiles (for example, “ZIA-only,” “ZPA-only,” or “ZIA and ZPA”) and then bind them to different App Profiles for different user groups or device types.

“Bypass,” “authentication,” or “exception” profiles are not separate required profile objects in the ZCC policy model. Any bypass or exception behavior is defined inside the forwarding and app profile logic, not as standalone mandatory profiles. Therefore, a Forwarding Profile is the one element that every ZCC App Profile must include.

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The ZDTE study content groups Private Service Edge under Advanced Platform Services, explaining that PSEs host the same Zero Trust Exchange policy and inspection engines, but run as customer-managed service edges inside data centers or large offices. They are designed to give on-premises users a “local on-ramp” to ZIA and ZPA services while still enforcing full zero-trust policy.

The documentation emphasizes that PSEs do not replace App Connectors for ZPA; connectors are still required to establish inside-out application connectivity. Nor do PSEs remove the need for ZTNA policies—those policies remain central and are simply enforced closer to the user. Encryption is also preserved end-to-end; there is no “unencrypted fast path” described in the reference architecture.

Instead, the primary benefit highlighted is performance and user experience: by enforcing ZIA/ZPA policies at a local PSE rather than a distant public service edge, organizations reduce round-trip latency and keep traffic on optimal paths while maintaining identical security and access controls.

For a large retail organization with hundreds of geographically distributed stores and applications split across multiple data centers plus AWS, Zscaler reference designs emphasize an SD-WAN–to–Zscaler Edge model combined with ZPA App Connectors deployed close to the applications. In this model, each store uses SD-WAN to build resilient, policy-based connectivity to the nearest Zscaler Edge locations. Those edges then provide secure, optimized access to private applications published through App Connectors installed in the on-premises data centers and within AWS VPCs.

This approach centralizes security and access control in the Zscaler cloud while avoiding the operational burden of managing hundreds of direct site-to-site VPNs. It also aligns with Zero Trust principles by steering all store traffic to Zscaler rather than extending the corporate network to every store. Direct Connect between data centers and AWS (as in option A) is optional from a ZPA perspective because App Connectors in AWS communicate outbound to Zscaler over the internet. Branch Connector (option D) is typically used when SD-WAN or suitable edge devices are not present, whereas a large retail environment commonly standardizes on SD-WAN.

In the context of Zscaler’s public APIs, HTTP status code 409 indicates a conflict with the current state of the target resource, most commonly an edit conflict. When configuration is managed via API, Zscaler uses versioning or similar concurrency controls to ensure that two administrators or systems do not overwrite each other’s changes unintentionally. A 409 response typically appears when the payload being pushed is based on an outdated version of the object or when another change has been committed between the time the configuration was retrieved and the time the update was sent.

The Digital Transformation Engineer documentation explains that clients should first retrieve the latest configuration (often including a version or ETag-like value), apply their modifications, and then push the update. If the server detects that the version in the request no longer matches the current version, it returns 409 Conflict to signal that the update cannot be safely applied.

The other options map to different HTTP codes: rate limit or quota issues are indicated by 429 Too Many Requests, non-existent resources by 404 Not Found, and syntax or malformed payloads by 400 Bad Request. Thus, for a 409 response during a configuration push, the correct interpretation is an edit conflict.

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In a typical enterprise authentication setup, Zscaler functions as the Service Provider (SP) within the SAML authentication framework. This aligns with Zscaler’s architectural principle that identity verification is delegated to an external authoritative Identity Provider (IdP) such as Azure AD, Okta, Ping, or ADFS. Zscaler does not authenticate user credentials directly. Instead, it relies on the IdP to validate the user and then deliver a signed SAML assertion back to Zscaler.

When a user attempts to access the Zscaler service, the authentication request is redirected to the enterprise IdP. The IdP performs credential verification and returns a SAML assertion containing the authenticated user identity and associated attributes. Zscaler, acting as the SP, consumes and validates this assertion, then maps the identity to its internal user records or SCIM-synchronized directory objects. This identity becomes the basis for all ZIA/ZPA policy evaluation, including URL filtering, CASB controls, DLP policies, firewall rules, and access-control enforcement.

Since Zscaler depends on the IdP for primary identity verification and only consumes assertions, Zscaler’s role is clearly defined as the Service Provider in a standard authentication configuration.

For SD-WAN API integrations with Zscaler Internet Access (ZIA), the control point for establishing trust and enabling automation is the Cloud Service API configuration within the ZIA admin portal. As documented in Zscaler’s SD-WAN and Cloud Service API workflow, the ZIA administrator navigates to the Cloud Service API (under Administration) and configures the SD-WAN integration by generating and managing the SD-WAN Partner Key there. This key is then used by the SD-WAN orchestrator or controller to authenticate against Zscaler’s APIs and to automate the creation of locations and tunnels.

The key is not provided by the SD-WAN partner; rather, it is created and controlled by the customer’s ZIA admin, which makes option D incorrect. Locations and tunnels created via the integration remain visible and generally manageable within the ZIA admin interface, so option B is incorrect. While SD-WAN integrations can automate both GRE and IPsec tunnels in many deployments, that behavior depends on the specific SD-WAN vendor and design, so the blanket statement in option A is not the definitive, document-aligned fact being tested.

Zscaler Digital Experience (ZDX) organizes its telemetry and alerting around key domains: Application, Network, and Device. Wi-Fi signal strength is a client-side characteristic of the endpoint itself, measured from the user’s device, not from the network path or the application service. In the ZDX training content, Wi-Fi signal, Wi-Fi link speed, CPU, memory, and similar metrics are clearly categorized under Device health.

When creating an alert rule to monitor newly deployed laptops, the administrator should therefore choose a Device-type alert and then select Wi-Fi signal–related metrics and thresholds. This allows ZDX to trigger alerts whenever the Wi-Fi signal on those endpoints falls below an acceptable level, helping operations teams quickly identify poor local wireless conditions that degrade user experience.

Network alerts are intended for end-to-end path health (latency, packet loss, DNS resolution, gateway reachability, etc.), and Application alerts focus on performance and availability of specific apps or services. “Interface” as a standalone alert type is not how ZDX structures its top-level alert categories; interface-related metrics are surfaced as device-side attributes. Consequently, the correct classification for Wi-Fi signal monitoring in ZDX is a Device alert rule.

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Zscaler External Attack Surface Management (EASM) is focused on discovering and monitoring an organization’s internet-facing digital assets. In the Engineer curriculum, EASM is described as continuously identifying domains, subdomains, hostnames, IP addresses, TLS certificates, and cloud services that are exposed to the public internet. A key example used in the training is hostnames that “leak” internal context, such as environment names, projects, technologies, or business units. These hostnames are treated as digital entities because they represent externally reachable services and can give valuable clues to an attacker during reconnaissance.

By contrast, SSL inspection certificates installed on endpoints are internal controls and not part of the external attack surface. A Zscaler App Connector is designed to initiate only outbound connections and is intentionally not directly reachable from the internet, so its IP address is not an EASM discovery target. Likewise, lists of compromised usernames and passwords relate to threat intelligence and identity protection, not the mapping of exposed assets. Therefore, the only option that correctly matches the type of digital entity EASM is meant to identify is a service hostname that contains revealing information.

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Zscaler Cloud Sandbox is designed to detect advanced and previously unknown threats by deeply analyzing suspicious files in an isolated environment. According to Zscaler’s documented analysis pipeline, every sandboxed sample goes through a structured, multi-stage process rather than a single pass.

First, the file undergoes static analysis, where the system inspects the file without executing it. This phase looks at elements such as structure, headers, embedded resources, and known malicious patterns or indicators. Next, the file is executed in a dynamic analysis environment (a sandbox) where Zscaler observes runtime behavior such as process creation, registry modifications, file system changes, network connections, and attempts at evasion or privilege escalation.

During this dynamic phase, the file may drop or create additional files and artifacts. Zscaler then performs a second round of static analysis on those dropped components. This secondary static analysis is crucial because many sophisticated threats unpack or download their real payload only at runtime; analyzing those artifacts provides a much clearer view of the full attack chain.

Because of this defined three-step approach—static, dynamic, then secondary static analysis on dropped artifacts—option A is the correct description of how many rounds of analysis are performed on a sandboxed sample.

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Zscaler’s multi-tier cloud architecture is separated into distinct planes: the control plane, enforcement plane, and logging plane. The control plane is implemented by the Central Authority and is described in Zscaler architecture material as the “brains” of the platform, responsible for policy definition, administration, orchestration, and the admin UI. Crucially, this same layer also exposes the API interfaces that automation tools and scripts use. In architecture slides, the control plane is explicitly associated with “Admin UI” and “API,” showing that all administrative programmability terminates there.

The enforcement plane (Public/Private Service Edges) is focused on inspecting and enforcing policy on user traffic, while the logging plane is dedicated to storing and streaming Nanolog data to SIEM or analytics tools. Neither of these planes provides administrative configuration APIs. Study content for the ZDTE exam reinforces that the API infrastructure enables programmatic access to configure the Zero Trust Exchange and is part of the central management layer, not the traffic or logging tiers.

Therefore, when an administrator makes API calls, they are communicating with the Control Plane.

In the ZDTE material under Advanced Access Control Services, Tenant Restrictions (often discussed with “personal vs. corporate” SaaS use) are described as a way to ensure users can only authenticate to sanctioned organization tenants for apps like Microsoft 365, Google Workspace, or other major SaaS platforms.

Zscaler does this by acting as an inline Zero Trust proxy and modifying the authentication flow, not by bluntly blocking all external SaaS access. The docs explain that, for supported SaaS applications, Zscaler injects specific identity or tenant identifiers (for example, the allowed tenant ID or corresponding claim) into the HTTP(S) requests during sign-in. These injected headers or parameters signal to the SaaS provider which tenant is permitted so that logins to personal or unsanctioned tenants can be transparently blocked or challenged while corporate tenant access is allowed.

Because this enforcement is done at the HTTP/S layer using header/parameter insertion tied to identity and policy, users retain seamless access to approved corporate tenants while attempts to use personal or shadow-IT tenants are controlled according to policy—exactly what Option C describes.

Zscaler Identity (ZIdentity) supports modern, phishing-resistant passwordless authentication using the FIDO2 standard. FIDO2 combines Web Authentication (WebAuthn) and the Client to Authenticator Protocol (CTAP2) to enable users to authenticate with security keys or built-in platform authenticators (such as biometric sensors) without transmitting or storing a reusable password. The Digital Transformation Engineer documentation explains that when a user registers a FIDO2 authenticator with ZIdentity, the service stores a public key tied to that device and account. Future logins are validated using a cryptographic challenge–response, providing strong protection against credential theft and replay attacks.

By contrast, SAML (option B) and OIDC (option C) are federation protocols used for single sign-on (SSO) and identity delegation between an identity provider and service providers; they do not themselves define how passwordless authentication is performed. They can carry assertions from an IdP that might use FIDO2 behind the scenes, but SAML and OIDC are not the passwordless method. SCIM (option D) is a provisioning standard for creating, updating, and deprovisioning identities and groups, not an authentication protocol.

Therefore, the only option that directly represents the protocol enabling passwordless login to a ZIdentity account is FIDO2.

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Zscaler Cloud Sandbox is described in Zscaler threat-protection training as following a four-stage workflow. The documented order is: Cloud Effect, Pre-Filtering, Behavioral Analysis, and Post-Processing.

Cloud Effect – Before detonation, files are checked against global threat intelligence and prior sandbox verdicts so that known malicious objects can be immediately blocked, and known benign files can be allowed without re-analysis.

Pre-Filtering – Static and signature-based checks (antivirus, file heuristics, and related engines) quickly discard clearly malicious or clearly safe files, reducing load on deep analysis.

Behavioral Analysis – Suspicious or unknown samples are executed in a virtual environment to observe behavior such as process spawning, registry changes, or C2 activity.

Post-Processing – Final verdicts are generated, policies are enforced (block, quarantine, allow), and new indicators are fed back into threat intelligence for future Cloud Effect decisions.

This exact ordered sequence—Cloud Effect → Pre-Filtering → Behavioral Analysis → Post-Processing—is what appears in ZDTE study material, so option C is correct.