Paloalto Networks Updated PSE-Strata-Pro-24 Exam Questions and Answers by azlan

To answer this question, let’s analyze each Cloud-Delivered Security Service (CDSS) subscription and its role in inline machine learning (ML). Palo Alto Networks leverages inline ML capabilities across several of its subscriptions to provide real-time protection against advanced threats and reduce the need for manual intervention.

A. Enterprise DLP (Data Loss Prevention)

Enterprise DLP is a Cloud-Delivered Security Service that prevents sensitive data from being exposed. Inline machine learning is utilized to accurately identify and classify sensitive information in real-time, even when traditional data patterns or signatures fail to detect them. This service integrates seamlessly with Palo Alto firewalls to mitigate data exfiltration risks by understanding content as it passes through the firewall.

B. Advanced URL Filtering

Advanced URL Filtering uses inline machine learning to block malicious URLs in real-time. Unlike legacy URL filtering solutions, which rely on static databases, Palo Alto Networks' Advanced URL Filtering leverages ML to identify and stop new malicious URLs that have not yet been categorized in static databases. This proactive approach ensures that organizations are protected against emerging threats like phishing and malware-hosting websites.

C. Advanced WildFire

Advanced WildFire is a cloud-based sandboxing solution designed to detect and prevent zero-day malware. While Advanced WildFire is a critical part of Palo Alto Networks’ security offerings, it primarily uses static and dynamic analysis rather than inline machine learning. The ML-based analysis in Advanced WildFire happens after a file is sent to the cloud for processing, rather than inline, so it does not qualify under this question’s scope.

D. Advanced Threat Prevention

Advanced Threat Prevention (ATP) uses inline machine learning to analyze traffic in real-time and block sophisticated threats such as unknown command-and-control (C2) traffic. This service replaces the traditional Intrusion Prevention System (IPS) approach by actively analyzing network traffic and blocking malicious payloads inline. The inline ML capabilities ensure ATP can detectand block threats that rely on obfuscation and evasion techniques.

E. IoT Security

IoT Security is focused on discovering and managing IoT devices connected to the network. While this service uses machine learning for device behavior profiling and anomaly detection, it does not leverage inline machine learning for real-time traffic inspection. Instead, it operates at a more general level by providing visibility and identifying device risks.

Key Takeaways:

Enterprise DLP, Advanced URL Filtering, and Advanced Threat Prevention all rely on inline machine learning to provide real-time protection.

Advanced WildFire uses ML but not inline; its analysis is performed in the cloud.

IoT Security applies ML for device management rather than inline threat detection.

To prevent malicious actors from abusing file-sharing applications for data exfiltration,App-IDprovides a granular approach to managing application traffic. Palo Alto Networks'App-IDis a technology that identifies applications traversing the network, regardless of port, protocol, encryption (SSL), or evasive tactics. By leveraging App-ID, security engineers can implement policies that restrict the use of specific applications or functionalities based on job functions, ensuring that only authorized users or groups can use file-sharing applications while blocking unauthorized or malicious usage.

Here’s why the options are evaluated this way:

Option A:DNS Security focuses on identifying and blocking malicious domains. While it plays a critical role in preventing certain attacks (like command-and-control traffic), it is not effective for managing application usage. Hence, this is not the best approach.

Option B (Correct):App-ID provides the ability to identify file-sharing applications (such as Dropbox, Google Drive, or OneDrive) and enforce policies to restrict their use. For example, you can create a security rule allowing file-sharing apps only for specific job functions, such as HR or marketing, while denying them for other users. This targeted approach ensures legitimate business needs are not disrupted, which aligns with the requirement of not impacting valid users.

Option C:Blocking all file-sharing applications outright using DNS Security is a broad measure that will indiscriminately impact legitimate users. This does not meet the requirement of allowing specific users to continue using file-sharing applications.

Option D:While App-ID can block file-sharing applications outright, doing so will prevent legitimate usage and is not aligned with the requirement to allow usage based on job functions.

How to Implement the Solution (Using App-ID):

Identify the relevant file-sharing applications using App-ID in Palo Alto Networks’ predefined application database.

Create security policies that allow these applications only for users or groups defined in your directory (e.g., Active Directory).

Use custom App-ID filters or explicit rules to control specific functionalities of file-sharing applications, such as uploads or downloads.

Monitor traffic to ensure that only authorized users are accessing the applications and that no malicious activity is occurring.

References:

Palo Alto Networks Admin Guide: Application Identification and Usage Policies.

Best Practices for App-ID Configuration: https://docs.paloaltonetworks.com

DNS-based threats, such as DNS tunneling, phishing, or malware command-and-control (C2) activities, are commonly used by attackers to exfiltrate data or establish malicious communications. Palo Alto Networks firewalls provide several mechanisms to address these threats, and the correct method isDNS sinkholing.

Why "DNS sinkholing" (Correct Answer D)?DNS sinkholing redirects DNS queries for malicious domains to an internal or non-routable IP address, effectively preventing communication with malicious domains. When a user or endpoint tries to connect to a malicious domain, the sinkhole DNS entry ensures the traffic is blocked or routed to a controlled destination.

DNS sinkholing is especially effective for blocking malware trying to contact its C2 server or preventing data exfiltration.

Why not "DNS proxy" (Option A)?A DNS proxy is used to forward DNS queries from endpoints to an upstream DNS server. While it can be part of a network's DNS setup, it does not actively stop DNS-based threats.

Why not "Buffer overflow protection" (Option B)?Buffer overflow protection is a method used to prevent memory-related attacks, such as exploiting software vulnerabilities. It is unrelated to DNS-based threat prevention.

Why not "DNS tunneling" (Option C)?DNS tunneling is itself a type of DNS-based threat where attackers encode malicious traffic within DNS queries and responses. This option refers to the threat itself, not the method to stop it.