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.)

• A. By providing Network Intercept inline in multicloud network architectures to monitor AI agent traffic, and API Intercept as Security as Code (SaC) to scan prompts and responses before they reach models.
• B. By offering Network Intercept for infrastructure-level protection across any cloud platform and API Intercept for application-level security embedded directly in agent code.
• C. By supporting API Intercept for Multicloud deployments since Network Intercept cannot be deployed in the network architectures of different cloud providers.
• D. By requiring separate product installations for each cloud platform with AWS-specific agents for Bedrock and GCP-specific agents for Vertex AI that cannot share policies.

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?

• A. Deploy a cloud-delivered security platform with AI-aware controls integrated with identity and device posture
• B. Rely on existing perimeter firewalls and VPN concentrators applying standard URL filtering and data loss prevention (DLP) policies for AI traffic
• C. Block external GenAI applications at the firewall and empower employees to use internally developed AI applications.
• D. Segment network zones within each data center to isolate AI workloads from critical IP address repositories and monitor east-west traffic

A company experiences lateral movement attacks within the internal network. Which feature helps mitigate this risk?

• A. QoS policies
• B. NAT rules
• C. Internal segmentation with NGFW
• D. Static routes

An enterprise deploys Palo Alto NGFWs across multiple regions. They require consistent security policy enforcement and centralized management while minimizing configuration drift. Which solution should be implemented?

• A. Local firewall configuration only
• B. Panorama with device groups and templates
• C. Manual policy synchronization
• D. Separate management per region