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NEW QUESTION # 22
During a pilot of Prisma Browser, several users note that web-based communication tools do not recognize their integrated webcams. The administrator confirms that the hardware is functioning correctly on the operating system level. Which two policy rule types should the administrator investigate within the Prisma Browser profile? (Choose two answers)
Answer: B,C
Explanation:
A web-based communication tool failing to recognize a webcam that is confirmed healthy at the OS level points to the browser itself withholding device access or media capability, rather than a hardware or driver fault - which narrows the investigation to the two Prisma Browser control categories that govern exactly those functions. Access & Data Controls is where the Camera control lives; it can be set to Allow or Block access to the device ' s camera on a per-URL, per-application, or per-category basis, and a Block setting here will cause every matching web application to behave precisely as described, with the site unable to access the webcam even though the OS reports it as fully functional. Browser Security Controls is the second area to check because it governs WebRTC, the underlying protocol nearly all browser-based video and audio communication tools depend on to negotiate and carry real-time media streams; setting WebRTC to Block is explicitly documented as breaking video conferencing and communication tools unless their domains are added to an exclusion list, which would also produce the exact symptom reported. Update & Maintenance Controls govern browser and extension update behavior, and Visibility & Analytics Controls govern session recording and reporting - neither category has any bearing on device permissions or real-time media protocol handling, so they can be ruled out as the source of this issue.
Reference: Prisma Access Browser - Access & Data Controls (Camera) and Browser Security Controls (WebRTC).
NEW QUESTION # 23
In addition to creating a Security policy, how can an AI Access Security be used to prevent users from uploading financial information to ChatGPT?
Answer: A
Explanation:
Palo Alto Networks AI Access Security integrates with Enterprise Data Loss Prevention (DLP) capabilities to control sensitive data within AI applications like ChatGPT. The most effective way to prevent users from uploading financial information is to:
* Define an Enterprise DLP rule:This rule would be configured to identify content that matches patterns or keywords associated with financial information (e.g., credit card numbers, bank account details, tax identifiers, financial statements).
* Apply the DLP rule to the AI Access Security policy:This policy would be specifically configured to inspect traffic to and from ChatGPT. When the DLP rule detects a user attempting to upload content containing financial information, it can take a defined action, such as blocking the upload.
Let's analyze why the other options are incorrect based on official documentation:
* A. Apply File Blocking to stop file uploads containing financial information.While File Blocking can prevent the upload of certain file types, it is not content-aware. It cannot inspect thecontentof a file to determine if it contains financial information. Therefore, it's not a granular or effective solution for this specific requirement.
* C. Add the ChatGPT domains using URL Filtering to block uploads containing financial information.URL Filtering controls access to specific websites or categories of websites. While you could potentially block access to ChatGPT entirely, it does not provide the capability to inspect the content being uploaded to a permitted domain and prevent the transfer of sensitive financial data.
* D. Apply a vulnerability profile to stop attempts to exploit system flaws or gain unauthorized access to financial systems.Vulnerability profiles are designed to detect and prevent attempts to exploit known security vulnerabilities in systems. They are not designed to inspect the content of user uploads for sensitive data like financial information. While importantfor overall security, they do not directly address the requirement of preventing financial data uploads to ChatGPT.
Therefore, configuring an Enterprise DLP rule within AI Access Security is the correct and most effective method to prevent users from uploading financial information to ChatGPT by inspecting the content of the uploads.
NEW QUESTION # 24
A customer using Prisma Access (Managed by Panorama) wants to monitor traffic patterns across all remote networks and use Strata Logging Service to gather insights on network usage. An engineer notices that some network data is missing from the Application Command Center (ACC). What should the engineer do to ensure complete data visibility?
Answer: D
Explanation:
ACC visibility is entirely dependent on logs actually reaching Strata Logging Service in the first place, and log generation in Prisma Access is not automatic for every policy by default - it requires that a log forwarding profile be explicitly attached to each Security policy rule, directing the relevant log types to Strata Logging Service. If any remote network policies are missing this attachment, whether due to an oversight during rule creation or a rule cloned from a template that lacked the profile, traffic matching those rules simply never generates the logs ACC depends on, producing exactly the gap in visibility described in the scenario. Systematically auditing and ensuring every Prisma Access policy has an appropriate log forwarding profile pointed at Strata Logging Service is therefore the correct, root-cause remediation, making option D correct. Reconfiguring remote networks to log directly to Panorama instead (option A) moves away from the documented, scalable Prisma Access logging architecture, in which Strata Logging Service is the authoritative log repository that ACC and other analytics surfaces query - this is a regression, not a fix. Option B describes a log aggregation setting that does not correct missing logs caused by absent forwarding profiles; Panorama does not independently aggregate logs from RN-SPNs outside of the Strata Logging Service pipeline. Option C ' s setting relates to whether historical data feeds predefined report templates, not to whether logs are being generated and forwarded from policy in the first place, so it does not address a genuine data gap.
Reference:Prisma Access - Log Forwarding Profiles and Strata Logging Service Integration with ACC.
NEW QUESTION # 25
Where are tags applied to control access to Generative AI when implementing AI Access Security?
Answer: D
Explanation:
AI Access Security extends Prisma Access ' s existing App-ID-based application classification model to the generative AI space, and the mechanism it uses to let organizations differentiate their risk tolerance across the rapidly growing number of AI applications in use is to apply status tags - sanctioned, tolerated, or unsanctioned - directly to the identified Generative AI applications themselves, mirroring the same governance pattern long used for SaaS Security application risk classification. Once an AI application carries one of these tags, Security policy rules and dashboards can reference that classification consistently across the environment, giving administrators a scalable way to express organizational policy (which AI tools are approved, which are tolerated with monitoring, and which are explicitly prohibited) without having to hand- build a separate access rule for every individual AI application discovered. This makes option A the correct answer, since the tag is applied at the application object level, not any of the other locations listed. Applying tags to Security rules (option B) inverts the actual relationship: rules reference the application ' s tag
/classification, they are not themselves the object being tagged. Tagging user devices (option C) would conflate device posture management with application classification, which are separate control domains in Prisma Access. Tagging Generative AI URL categories (option D) misattributes the classification mechanism to URL Filtering category objects, when AI Access Security ' s sanctioned/tolerated/unsanctioned tagging is applied to the discovered applications themselves via App-ID, not to a URL category construct.
Reference:AI Access Security - Sanctioned, Tolerated, and Unsanctioned Application Tagging.
NEW QUESTION # 26
A company has four branch offices between Canada Central and Canada East which use the same IPSec termination node and have QoS configured with customized bandwidth per site. An engineer wants to onboard a new branch office on the same IPSec termination node. What is the QoS behavior for the new branch office?
Answer: D
Explanation:
Once an administrator has moved away from Prisma Access ' s default, automatic bandwidth-sharing behavior and explicitly customized bandwidth allocation per site on a shared IPSec termination node, the platform respects that deliberate, manual configuration rather than silently recalculating or redistributing percentages whenever a new site is added to the same node. Onboarding a fifth branch office onto a termination node where the existing four sites already have customized, fixed bandwidth values does not trigger an automatic rebalancing to a new even split; instead, the new site simply has no bandwidth allocation defined for it and will remain unallocated, effectively receiving no guaranteed or prioritized QoS treatment, until the engineer explicitly assigns it a bandwidth value as part of onboarding. This makes option B the accurate description of default platform behavior. Options A and C both describe an automatic, evenly-redistributed percentage outcome (25% and 20% respectively, which would correspond to five equal shares or four equal shares) that does not reflect how customized QoS interacts with new site onboarding - automatic even redistribution is the behavior only when no manual customization has been introduced in the first place, and once customization exists, the platform does not silently override or reflow it. Option D is incorrect because new branch offices absolutely can be added to an IPSec termination node with existing customized QoS; the addition itself is fully supported, it simply requires the administrator to manually define that site ' s bandwidth.
Reference:Prisma Access Remote Networks - QoS Bandwidth Allocation per IPSec Termination Node.
NEW QUESTION # 27
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