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| Section | Objectives |
|---|---|
| Topic 1: Zero Trust Network Security Design | - SASE vs Traditional Firewall Edge Solutions
|
| Topic 2: IoT and Endpoint Security Architecture | - IoT Security
|
| Topic 3: Log Collection and Monitoring Architecture | - Monitoring and Troubleshooting
|
| Topic 4: Network Security Platform Architecture | - Next-Generation Firewall Deployment
|
| Topic 5: Third-Party Integration and Automation | - Third-Party Integrations
|
| Topic 6: Cloud and Hybrid Security Architecture | - Prisma Browser and Device-ID
|
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NEW QUESTION # 64
A global organization has fully adopted Prisma Access to provide security for its mobile workforce and remote offices, and user identity is managed in Okta. The security team wants to create consistent Security policies that grant access to specific SaaS applications based on a users' departments, regardless of whether they work from home or a from branch office connected via an SD-WAN device. Which architecture ensures that consistent user-to-group mapping is available to Prisma Access for policy enforcement in this use case?
Answer: A
Explanation:
Panorama-managed Prisma Access integrates with Cloud Identity Engine to retrieve user and group information for both mobile users and remote networks, which allows consistent user-to- group mapping across work-from-home users and branch offices. Cloud Identity Engine supports Okta as the identity source, so department-based group membership from Okta can be used centrally for Prisma Access policy enforcement.
NEW QUESTION # 65
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: B
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 # 66
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,D
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 # 67
A company needs to securely enable SaaS application usage while preventing data exfiltration.
The solution must provide visibility into application traffic and enforce granular controls. What should be used?
Answer: A
Explanation:
App-ID identifies applications regardless of port or protocol, while Data Filtering prevents sensitive data exfiltration. This combination provides both visibility and control. URL filtering alone cannot inspect application-layer data deeply enough to enforce data protection requirements.
NEW QUESTION # 68
Which factor must be taken into consideration when determining whether an NGFW edge architecture or a SASE architecture is appropriate to recommend to a customer planning to implement a Zero Trust Network Access (ZTNA) solution?
Answer: D
Explanation:
Zero Trust Network Access is a security approach that can be implemented using either traditional NGFW-based architectures or SASE solutions. The key consideration is how identity, policy enforcement, and segmentation are applied, not the deployment model itself, since both architectures are capable of supporting ZTNA principles.
NEW QUESTION # 69
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