Zscaler ZDTE Dumps Questions Answers

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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In Zscaler, the Endpoint DLP report is specifically designed to give security teams visibility into how end users interact with sensitive data on their endpoints (laptops, desktops, etc.). This report aggregates activity such as copying, saving, printing, uploading, or otherwise handling sensitive content that is detected and classified by Zscaler Endpoint DLP. It focuses on data risk rather than just malware or traffic volumes, so it shows which files, users, and devices are involved in policy matches, along with the context of each event.

Unlike a generic malware or data usage report, the Endpoint DLP report is tightly aligned with DLP policies and data classifications you configure (such as PII, financial data, source code, or custom patterns). This allows you to quickly see which policies are triggering on endpoints, which channels or applications are most frequently involved, and where to fine-tune rules or add additional controls. Because it is endpoint-focused, it covers scenarios even when users are off the corporate network, giving a unified view across inline and endpoint DLP enforcement. For exam purposes, this is why Endpoint DLP report is the correct answer.

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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.