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| Section | Weight | Objectives |
|---|---|---|
| AI Security | 11% | - Prisma AI Runtime Security and AI Access architecture - AI application classification and security controls - AI security framework and compliance |
| SSE Private Application Access | 11% | - Colo-Connect and cloud connectivity design - Private access and connector architecture - Prisma Access global and regional deployment design |
| Cloud Security Architecture | 12% | - Workload protection and cloud network security - Multi-cloud and hybrid security design - Prisma Cloud and public cloud integration |
| Centralized Management and IAM | 13% | - Directory sync and authentication methods - Panorama and log collector architecture - Strata Cloud Manager, Logging Service and Cloud Identity Engine design |
| IoT and OT Security | 11% | - IoT segmentation and visibility architecture - Device onboarding and lifecycle security - OT security and industrial protocol protection |
| Mobile User Security | 7% | - Prisma Browser and agent-based access - GlobalProtect connection methods and deployment - Explicit proxy and remote access design |
| Zero Trust Enterprise | 8% | - Continuous threat prevention and monitoring - User-ID, Device-ID, HIP and security posture design - Application access control design - Network segmentation and microsegmentation design |
| Automation and Orchestration | 10% | - Integration with third-party tools and workflows - Infrastructure as Code and security orchestration - API and automation framework design |
| High Availability and Resilience | 9% | - Platform HA and redundancy design - Scalability and performance optimization - Failover and disaster recovery planning |
| Compliance and Risk Management | 8% | - Risk assessment and security governance - Audit and reporting architecture - Industry compliance frameworks (NIST, GDPR, PCI, HIPAA) |
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NEW QUESTION # 50
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.)
Answer: A,C
Explanation:
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.
NEW QUESTION # 51
An organization plans to deploy a full SASE architecture consisting of Prisma SD-WAN IONs at branches and data centers alongside Prisma Access remote networks, service connections, and mobile users. The business office team requires that traffic from global remote offices to public cloud is of highest criticality, and this traffic should have the greatest service-level agreement (SLA) and QoS priority while still maintaining a balance of threat inspection. Which recommendation should the architect make to provide the lowest latency, highest throughput, and greatest resilience for the applications?
Answer: B
Explanation:
Deploying Prisma SD-WAN IONs in the public cloud gives remote offices the most direct path to cloud-hosted applications, which is the best fit for lowest latency and highest throughput. Prisma SD-WAN is built around application-aware path selection, QoS, and performance policy so traffic can be prioritized by business criticality and moved to a better path when SLA metrics such as latency, loss, or jitter are violated. Palo Alto Networks also supports BGP on branch and data center ION devices, including public-cloud deployments through its cloud integrations, which provides resilient routing to cloud application environments.
NEW QUESTION # 52
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 architectural approach best aligns with the organization's strategic objectives to enable AI innovation and protect sensitive assets?
Answer: C
Explanation:
A cloud-delivered security platform with AI-aware controls provides centralized visibility and policy enforcement across both sanctioned and unsanctioned AI applications, regardless of user location or device. By integrating identity and device posture, it enables granular Zero Trust access, protects sensitive data from exfiltration, and secures both external and internally developed AI applications without restricting innovation.
NEW QUESTION # 53
A global organization is modernizing its data center and private cloud infrastructure. The environment consists of:
- A Nutanix AHV cluster hosting critical east-west application workloads
- A VMware ESXi cluster with multi-socket hosts, supporting high-throughput workloads (>10 Gbps)
- A new pair of PA-5450 firewalls to secure the perimeter and handle encrypted traffic inspection at scale
- Strict performance service-level agreements (SLAs) for both north-south and east-west flows, with heavy reliance on TLS 1.3 and IPSec
- A Network Functions Virtualization (NFV) environment on KVM to provide high-performance security services to maximize packet throughput and minimize latency The chief architect is tasked with ensuring that the firewall design avoids hypervisor contention optimizes non-uniform memory access (NUMA) and uses hardware features for encrypted traffic.
VM-Series on Nutanix AHV - Resource Allocation
- Because the Nutanix cluster is already heavily used, the architect's main concern is preventing performance degradation of the virtual firewall. Thin provisioning or ballooning could introduce latency and unpredictability which is unacceptable for a security-sensitive workload.
VM-Series on VMware ESXi - NUMA and vCPU Placement
- In the VMware ESXi environment, the architect is deploying VM-Series for workloads pushing >10 Gbps. Assigning vCPUs across NUMA nodes or oversubscribing cores would create latency due to cross-socket memory access and scheduling delays. Similarly, dedicating logical hypethreads does not provide the deterministic data plane performance required.
Operational Integration and High Availability
- With performance guaranteed by correct hypervisor and hardware provisioning, the architect also considers high availability (HA). VM-Series pairs are deployed in active/passive HA across Nutanix and VMware clusters, while PA-5450s form the data center's north-south secure perimeter deployment. This ensures resilience without introducing unnecessary east-west inspection bottlenecks.
- The recommendation must be a scalable, high-performance firewall deployment aligned with enterprise SLAs and the CISO's encrypted traffic concerns.
Which PAN-OS feature will meet the CISO's need for north-south traffic inspection?
Answer: C
Explanation:
Dedicated hardware crypto engines on the PA-5450 offload SSL/TLS decryption and IPSec processing from the main CPU, enabling high-performance inspection of encrypted north-south traffic. This ensures the firewall can meet strict SLAs while handling heavy TLS 1.3 and IPSec workloads efficiently.
NEW QUESTION # 54
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?
Answer: D
Explanation:
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.
NEW QUESTION # 55
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