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Palo Alto Networks NetSec-Architect Exam Syllabus Topics:

SectionObjectives
Topic 1: Network Security Platform Architecture- Systems Management and Hardware
  • 1. SSL inspection sizing requirements
  • 2. Hardware deployment trending and scoping
  • 3. Systems management options and considerations
- Next-Generation Firewall Deployment
  • 1. HA architecture
  • 2. Redistribution (ECMP, static routing, BGP, OSPF)
  • 3. Routing design
  • 4. Layer 3 deployment routing considerations
Topic 2: Zero Trust Network Security Design- Zero Trust Architecture Principles
  • 1. Transaction flow mapping
  • 2. Kipling Method for policy creation
  • 3. Protect surface identification
  • 4. Microperimeter design
- SASE vs Traditional Firewall Edge Solutions
  • 1. Prisma Access integration
  • 2. WAN solution design
  • 3. Branch-to-branch traffic architecture
Topic 3: IoT and Endpoint Security Architecture- IoT Security
  • 1. IoT device profiling and coverage
  • 2. DHCP infrastructure integration
  • 3. IoT sensor deployment
Topic 4: Third-Party Integration and Automation- Security Automation
  • 1. Content updates and automation workflows
- Third-Party Integrations
  • 1. Integration with third-party security solutions
  • 2. Panorama templates and centralized management
Topic 5: Log Collection and Monitoring Architecture- Monitoring and Troubleshooting
  • 1. Path checks and rule hit analysis
  • 2. Common fix workflows
- Log Collection Design
  • 1. Large-scale log collection architecture
  • 2. Strata Cloud Manager operations
Topic 6: Cloud and Hybrid Security Architecture- Prisma Browser and Device-ID
  • 1. Integration with identity providers (Entra ID)
  • 2. Device token / Device-ID issued by Prisma Browser
- Cloud-Native Security Solutions
  • 1. Prisma Cloud integration
  • 2. VM-Series virtual firewalls in Azure
  • 3. Hybrid deployment design

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Palo Alto Networks Network Security Architect NetSec-Architect Prüfungsfragen mit Lösungen (Q45-Q50):

45. Frage
A company wants visibility into all traffic, including unknown applications. What feature enables this?

Antwort: D

Begründung:
App-ID identifies applications regardless of port, protocol, or encryption. It provides deep visibility into network traffic, including unknown or evasive applications.


46. Frage
A global manufacturing organization has a strategic plan for rapid growth through mergers and acquisitions Several components the organization has purchased are deemed large deployments with existing IP address schemas and allocations that conflict with the parent organization. The manufacturing organization needs access to the resources before a re-IP initiative can be completed.
All of the deployments include a variety of IoT devices Leadership requires protection of vulnerable assets and identification of any known CVEs associated with the IoT devices. The governance, risk and compliance (GRC) team requires comprehensive non-repudiable logs to identify all IoT devices reporting "Critical (9 0+) CVE scores" for mandatory remediation.
Throughput needs to exceed the current 1 Gbps trending rate, and with expected growth will soon scale to 5 Gbps.
Segmentation is a mandatory requirement with enclaves based on region, device type, and function.
Which architectural component ensures the IoT storage, integrity, and non-repudiation of this granular risk data for auditing purposes?

Antwort: A

Begründung:
Strata Logging Service provides centralized, cloud-based log storage with integrity and non- repudiation guarantees, ensuring that IoT telemetry and security logs are preserved for auditing.
It scales to handle high throughput environments and supports long-term retention and analysis, which is required for tracking devices with critical CVE scores across large, distributed deployments.


47. Frage
A global manufacturing organization with 50,000 employees spanning 35 countries designs advanced industrial equipment and owns significant intellectual property. The organization operates in a highly competitive market where protecting trade secrets is critical to maintaining market advantage.
Over the past 18 months, the CISO discovered that employees across the organization have adopted hundreds of GenAI applications to improve productivity. Engineers use AI coding assistants to accelerate product development sales teams use AI tools to generate proposals, and customer service representatives use chatbots to draft responses. While this adoption has driven innovation, it has also created significant security risks.
A security audit reveals sensitive CAD files uploaded to image-generation services, proprietary source code shared with public coding assistants, and confidential customer information used in prompts. The audit identifies over 300 different GenAI applications in use, most of which had not been formally reviewed or approved.
The customer service department has also been developing internal AI applications, including a customer service copilot built on a cloud large language model (LLM) platform, an internal knowledge management assistant, and a code review tool. These internal applications access sensitive databases, customer records and internal APIs - creating additional security concerns about exploitation or misuse.
The organization has a distributed workforce in which 60% of employees work remotely or in hybrid arrangements, accessing corporate resources and AI applications from various locations using managed and unmanaged devices. Existing network security infrastructure lacks AI-specific security capabilities.
Organization leadership wants to enable AI-driven innovation while implementing comprehensive security controls. The CISO has been tasked with developing an organization-wide GenAI governance program that protects sensitive assets without hindering productivity. The program must address both external AI applications employees are using and internal AI applications being developed by IT.
Which enforcement solution can the CISO recommend to control GenAI data exfiltration?

Antwort: D

Begründung:
AI Access Security is designed to control and govern user interactions with external GenAI applications, including inspecting prompts and responses and applying DLP policies to prevent sensitive data exfiltration. It provides inline enforcement for SaaS-based AI usage across distributed users, which directly addresses the risk of confidential data being exposed through third-party GenAI tools.


48. Frage
A global manufacturing organization with 50,000 employees spanning 35 countries designs advanced industrial equipment and owns significant intellectual property. The organization operates in a highly competitive market where protecting trade secrets is critical to maintaining market advantage.
Over the past 18 months, the CISO discovered that employees across the organization have adopted hundreds of GenAI applications to improve productivity. Engineers use AI coding assistants to accelerate product development sales teams use AI tools to generate proposals, and customer service representatives use chatbots to draft responses. While this adoption has driven innovation, it has also created significant security risks.
A security audit reveals sensitive CAD files uploaded to image-generation services, proprietary source code shared with public coding assistants, and confidential customer information used in prompts. The audit identifies over 300 different GenAI applications in use, most of which had not been formally reviewed or approved.
The customer service department has also been developing internal AI applications, including a customer service copilot built on a cloud large language model (LLM) platform, an internal knowledge management assistant, and a code review tool. These internal applications access sensitive databases, customer records and internal APIs - creating additional security concerns about exploitation or misuse.
The organization has a distributed workforce in which 60% of employees work remotely or in hybrid arrangements, accessing corporate resources and AI applications from various locations using managed and unmanaged devices. Existing network security infrastructure lacks AI-specific security capabilities.
Organization leadership wants to enable AI-driven innovation while implementing comprehensive security controls. The CISO has been tasked with developing an organization-wide GenAI governance program that protects sensitive assets without hindering productivity. The program must address both external AI applications employees are using and internal AI applications being developed by IT.
In which two ways would Prisma AIRS secure AI agents deployed across multiple cloud platforms in this scenario? (Choose two.)

Antwort: C,D

Begründung:
Network Intercept provides inline visibility and control of AI traffic across multicloud environments, enabling consistent infrastructure-level protection regardless of where agents are deployed. API Intercept complements this by acting at the application layer, scanning prompts and responses and embedding security controls directly into AI workflows, ensuring protection before interactions reach the model.


49. Frage
You need to decrypt SSL traffic for inspection while ensuring compliance with privacy regulations.
What should you configure?

Antwort: D

Begründung:
Selective SSL decryption allows inspection of relevant traffic while excluding sensitive or regulated content, ensuring compliance. Decrypting all traffic may violate privacy laws, while disabling decryption reduces visibility into encrypted threats.


50. Frage
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