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Palo Alto Networks Systems Engineer Professional - Hardware Firewall Sample Questions (Q59-Q64):

NEW QUESTION # 59
Which use case is valid for Palo Alto Networks Next-Generation Firewalls (NGFWs)?

A. Serverless NGFW code security provides public cloud security for code-only deployments that do not leverage virtual machine (VM) instances or containerized services.
B. IT/OT segmentation firewalls allow operational technology resources in plant networks to securely interface with IT resources in the corporate network.
C. Code-embedded NGFWs provide enhanced internet of things (IoT) security by allowing PAN-OS code to be run on devices that do not support embedded virtual machine (VM) images.
D. PAN-OS GlobalProtect gateways allow companies to run malware and exploit prevention modules on their endpoints without installing endpoint agents.

Answer: B

Explanation:
Palo Alto Networks Next-Generation Firewalls (NGFWs) provide robust security features across a variety of use cases. Let's analyze each option:
A: Code-embedded NGFWs provide enhanced IoT security by allowing PAN-OS code to be run on devices that do not support embedded VM images.
This statement is incorrect. NGFWs do not operate as "code-embedded" solutions for IoT devices. Instead, they protect IoT devices through advanced threat prevention, device identification, and segmentation capabilities.
B: Serverless NGFW code security provides public cloud security for code-only deployments that do not leverage VM instances or containerized services.
This is not a valid use case. Palo Alto NGFWs provide security for public cloud environments using VM- series firewalls, CN-series (containerized firewalls), and Prisma Cloud for securing serverless architectures.
NGFWs do not operate in "code-only" environments.
C: IT/OT segmentation firewalls allow operational technology (OT) resources in plant networks to securely interface with IT resources in the corporate network.
This is a valid use case. Palo Alto NGFWs are widely used in industrial environments to provide IT/OT segmentation, ensuring that operational technology systems in plants or manufacturing facilities can securely communicate with IT networks while protecting against cross-segment threats. Features like App-ID, User- ID, and Threat Prevention are leveraged for this segmentation.
D: PAN-OS GlobalProtect gateways allow companies to run malware and exploit prevention modules on their endpoints without installing endpoint agents.
This is incorrect. GlobalProtect gateways provide secure remote access to corporate networks and extend the NGFW's threat prevention capabilities to endpoints, but endpoint agents are required to enforce malware and exploit prevention modules.
Key Takeaways:
* IT/OT segmentation with NGFWs is a real and critical use case in industries like manufacturing and utilities.
* The other options describe features or scenarios that are not applicable or valid for NGFWs.
References:
* Palo Alto Networks NGFW Use Cases
* Industrial Security with NGFWs

NEW QUESTION # 60
Device-ID can be used in which three policies? (Choose three.)

A. SD-WAN
B. Policy-based forwarding (PBF)
C. Quality of Service (QoS)
D. Decryption
E. Security

Answer: C,D,E

Explanation:
The question asks about the policies where Device-ID, a feature of Palo Alto Networks NGFWs, can be applied. Device-ID enables the firewall to identify and classify devices (e.g., IoT, endpoints) based on attributes like device type, OS, or behavior, enhancing policy enforcement. Let's evaluate its use across the specified policy types.
Step 1: Understand Device-ID
Device-ID leverages the IoT Security subscription and integrates with the Strata Firewall to provide device visibility and control. It uses data from sources like DHCP, HTTP headers, and machinelearning to identify devices and allows policies to reference device objects (e.g., "IP Camera," "Medical Device"). This feature is available on PA-Series firewalls running PAN-OS 10.0 or later with the appropriate license.

NEW QUESTION # 61
In addition to Advanced DNS Security, which three Cloud-Delivered Security Services (CDSS) subscriptions utilize inline machine learning (ML)? (Choose three)

A. Advanced Threat Prevention
B. Advanced WildFire
C. Enterprise DLP
D. Advanced URL Filtering
E. IoT Security

Answer: A,C,D

Explanation:
To answer this question, let's analyze each Cloud-Delivered Security Service (CDSS) subscription and its role in inline machine learning (ML). Palo Alto Networks leverages inline ML capabilities across several of its subscriptions to provide real-time protection against advanced threats and reduce the need for manual intervention.
A: Enterprise DLP (Data Loss Prevention)
Enterprise DLP is a Cloud-Delivered Security Service that prevents sensitive data from being exposed. Inline machine learning is utilized to accurately identify and classify sensitive information in real-time, even when traditional data patterns or signatures fail to detect them. This service integrates seamlessly with Palo Alto firewalls to mitigate data exfiltration risks by understanding content as it passes through the firewall.
B: Advanced URL Filtering
Advanced URL Filtering uses inline machine learning to block malicious URLs in real-time. Unlikelegacy URL filtering solutions, which rely on static databases, Palo Alto Networks' Advanced URL Filtering leverages ML to identify and stop new malicious URLs that have not yet been categorized in static databases.
This proactive approach ensures that organizations are protected against emerging threats like phishing and malware-hosting websites.
C: Advanced WildFire
Advanced WildFire is a cloud-based sandboxing solution designed to detect and prevent zero-day malware.
While Advanced WildFire is a critical part of Palo Alto Networks' security offerings, it primarily uses static and dynamic analysis rather than inline machine learning. The ML-based analysis in Advanced WildFire happens after a file is sent to the cloud for processing, rather than inline, so it does not qualify under this question's scope.
D: Advanced Threat Prevention
Advanced Threat Prevention (ATP) uses inline machine learning to analyze traffic in real-time and block sophisticated threats such as unknown command-and-control (C2) traffic. This service replaces the traditional Intrusion Prevention System (IPS) approach by actively analyzing network traffic and blocking malicious payloads inline. The inline ML capabilities ensure ATP can detect and block threats that rely on obfuscation and evasion techniques.
E: IoT Security
IoT Security is focused on discovering and managing IoT devices connected to the network. While this service uses machine learning for device behavior profiling and anomaly detection, it does not leverage inline machine learning for real-time traffic inspection. Instead, it operates at a more general level by providing visibility and identifying device risks.
Key Takeaways:
* Enterprise DLP, Advanced URL Filtering, and Advanced Threat Prevention all rely on inline machine learning to provide real-time protection.
* Advanced WildFire uses ML but not inline; its analysis is performed in the cloud.
* IoT Security applies ML for device management rather than inline threat detection.

NEW QUESTION # 62
Which two files are used to deploy CN-Series firewalls in Kubernetes clusters? (Choose two.)

A. PAN-CN-MGMT-CONFIGMAP
B. PAN-CNI-MULTUS
C. PAN-CN-MGMT
D. PAN-CN-NGFW-CONFIG

Answer: A,D

Explanation:
CN-Series firewalls are Palo Alto Networks' containerized NGFWs designed for protecting Kubernetes environments. These firewalls provide threat prevention, traffic inspection, and compliance enforcement within containerized workloads. Deploying CN-Series in a Kubernetescluster requires specific configuration files to set up the management plane and NGFW functionalities.
* Option A (Correct):PAN-CN-NGFW-CONFIGis required to define the configurations for the NGFW itself. This file contains firewall policies, application configurations, and security profiles needed to secure the Kubernetes environment.
* Option B (Correct):PAN-CN-MGMT-CONFIGMAPis a ConfigMap file that contains the configuration for the management plane of the CN-Series firewall. It helps set up the connection between the management interface and the NGFW deployed within the Kubernetes cluster.
* Option C:This option does not represent a valid or required file for deploying CN-Series firewalls. The management configurations are handled via the ConfigMap.
* Option D:PAN-CNI-MULTUSrefers to the Multus CNI plugin for Kubernetes, which is used for enabling multiple network interfaces in pods. While relevant for Kubernetes networking, it is not specific to deploying CN-Series firewalls.
References:
* CN-Series Deployment Guide: https://docs.paloaltonetworks.com/cn-series
* Kubernetes Integration with CN-Series Firewalls:https://www.paloaltonetworks.com

NEW QUESTION # 63
Which three use cases are specific to Policy Optimizer? (Choose three.)

A. Enabling migration from port-based rules to application-based rules
B. Discovering 5-tuple attributes that can be simplified to 4-tuple attributes
C. Automating the tagging of rules based on historical log data
D. Converting broad rules based on application filters into narrow rules based on application groups
E. Discovering applications on the network and transitions to application-based policy over time

Answer: A,D,E

Explanation:
* Discovering Applications on the Network (Answer A):
* Policy Optimizeranalyzes traffic logs to identifyapplications running on the networkthat are currently being allowed by port-based or overly permissive policies.
* It providesvisibilityinto these applications, enabling administrators to transition to more secure, application-based policies over time.
* Converting Broad Rules into Narrow Rules (Answer B):
* Policy Optimizer helps refine policies byconverting broad application filters(e.g., rules that allow all web applications) intonarrower rules based on specific application groups.
* This reduces the risk of overly permissive access while maintaining granular control.
* Migrating from Port-Based Rules to Application-Based Rules (Answer C):
* One of the primary use cases for Policy Optimizer is enabling organizations tomigrate from legacy port-based rules to application-based rules, which are more secure and aligned with Zero Trust principles.
* Policy Optimizer identifies traffic patterns and automatically recommends the necessary application-based policies.
* Why Not D:
* 5-tuple attributes (source IP, destination IP, source port, destination port, protocol)are used in traditional firewalls. Simplifying these attributes to 4-tuple (e.g., removing the protocol) is not a use case for Policy Optimizer, as Palo Alto Networks NGFWs focus onapplication-based policies, not just 5-tuple matching.
* Why Not E:
* Automating tagging of rules based on historical log data is not a specific feature of Policy Optimizer. While Policy Optimizer analyzes log data to recommend policy changes, tagging is not its primary use case.
References from Palo Alto Networks Documentation:
* Policy Optimizer Overview
* Transitioning to Application-Based Policies

NEW QUESTION # 64
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Chris Fox Chris Fox

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