The Palo Alto Networks AI Runtime Security solution, a component of Prisma Cloud, operates in a distinct lifecycle. The process begins with the Discovery phase, where the system automatically identifies all running workloads across the environment. This is followed by the Deployment of enforcers (Defenders) to these workloads to gain visibility and control. Once deployed, the system enters the Detection phase, using machine learning and behavioral analysis to monitor for threats and anomalies. The final phase is Prevention, where the solution actively blocks identified attacks in real-time, protecting applications from exploits, malware, and other runtime threats.

A. Scanning, Isolation, Whitelisting, Logging: These are specific security functions or features, not the overarching operational phases of the entire AI Runtime Security solution's lifecycle.

C. Policy Generation, Discovery, Enforcement, Logging: This option omits the critical initial deployment phase and conflates the distinct detection and prevention stages into a single "enforcement" step.

D. Profiling, Policy Generation, Enforcement, Reporting: While profiling is part of discovery and enforcement is a key outcome, this option misses the explicit deployment and detection phases that define the solution's workflow.

1. Palo Alto Networks. (2023). Prisma® Cloud AI Runtime Security Solution Brief. "Prisma Cloud AI Runtime Security provides comprehensive protection for your cloud native applications... It starts with discovery of all your running workloads... Deploy enforcers... Detect threats... Prevent attacks..." (Page 2).

2. Palo Alto Networks. (2024). Prisma Cloud Administrator's Guide (Compute). The guide's structure for implementing runtime defense follows this model: Deploying Defenders (Deployment)

viewing runtime data (Discovery)

creating runtime rules (Detection)

and setting the rule effect to "Prevent" or "Block" (Prevention). (Sections: "Deploy Defenders"

"Runtime security").