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Palo Alto Networks NetSec-Analyst Reliable Mock Test, NetSec-Analyst Test Simulator Fee

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Palo Alto Networks Network Security Analyst Sample Questions (Q118-Q123):

NEW QUESTION # 118
A large enterprise uses a Palo Alto Networks firewall to manage Internet access. They have multiple internal networks, each with its own egress NAT requirements. The network team has defined the following:
1. 'Internal _ Dev' (10.0.10.0/24) needs to Source NAT to a dedicated public IP 203.0.113.100.
2. 'Internal _ Prod' (10.0.20.0/24) needs to Source NAT to a pool of public IPs (203.0.113.101-203.0.113.105) for high concurrency.
3. 'Internal_Guest' (10.0.30.0/24) needs to Source NAT to the firewall's egress interface IP.
All three internal zones egress through the 'External' zone. You need to design the NAT policy order to ensure these requirements are met without conflicting. Which of the following ordered NAT policy sets (top to bottom) would achieve the desired outcome, assuming the External interface IP is 203.0.113.1?

A.
B.
C. The order of Source NAT policies does not matter; only Destination NAT policy order is critical.
D.
E.

Answer: A

Explanation:
Palo Alto Networks firewalls process NAT rules from top to bottom, applying the first match. In this scenario, all three networks have specific NAT requirements. Since none of the networks overlap in IP address space or source zone, the order of these specific rules doesn't inherently cause a conflict among themselves IF they are placed before any broader 'catch-all' NAT rules. However, following a logical order of more specific to less specific (or just ensuring specific rules are above broad ones) is good practice.
All three options A, B, and D correctly define the individual NAT rules. The question asks for an order that achieves the desired outcome without conflicting . Since each rule targets a distinct source network (10.0.10.0/24, 10.0.20.0/24, 10.0.30.0/24), any order of these three specific rules (A, B, or D) will work, as long as there isn't a broader rule above them that would match their traffic prematurely. Option A presents a valid order. Option C is incorrect because placing a 'Catch-all Interface NAT' at the top would match all traffic from the specific zones before their dedicated rules are hit, leading to incorrect translation for Dev and Prod. Option E is incorrect; the order of Source NAT policies absolutely matters, just as with any policy type on the firewall, due to the top-down matching logic.

NEW QUESTION # 119
Consider an environment where new IoT devices are frequently onboarded. The security team wants to automate the process of categorizing these devices and applying appropriate security policies. Which Palo Alto Networks feature, often integrated with an IoT Security Profile, allows for dynamic device classification and policy enforcement without manual intervention for each new device?

A. IoT Security with Device-ID and IoT Device Groups, dynamically populated by the firewall's visibility engine or third-party IoT security platforms (e.g., Zingbox, now part of Palo Alto Networks).
B. Static MAC Address Filtering and a default 'Any-Any' security rule.
C. User-ID and Group Mapping to assign IoT devices to specific user groups.
D. Security profiles based on Source/Destination IP addresses and Service ports only.
E. External Dynamic Lists (EDLs) populated with known IoT device IP addresses.

Answer: A

Explanation:
Option C is the most effective. Palo Alto Networks' IoT Security solution, powered by Device-ID and integration with specialized IoT security platforms, can automatically discover, classify, and group IoT devices based on their attributes (vendor, model, OS, observed behavior, etc.). These dynamically populated 'IoT Device Groups' can then be used as source/destination objects in security policies, allowing for automated and context-aware policy enforcement as new devices are onboarded. Options A, B, D, and E are either manual, lack device context, or are not designed for dynamic IoT device classification.

NEW QUESTION # 120
A critical vulnerability (CVE-2023-XXXX) affecting a widely used web server application has been announced, and the CISO demands immediate identification of all internal systems that have communicated with known malicious IPs associated with this vulnerability over the last 30 days. The incident response team needs to rapidly query Strata Logging Service, cross-reference with an external threat intelligence feed (TAXII/STIX), and generate a list of affected internal hosts and the specific firewall sessions. Describe the MOST effective workflow and necessary technical components.

A. Integrate the external threat intelligence feed into Palo Alto Networks WildFire and Threat Prevention. Query Strata Logging Service for 'threat' logs where 'action' is 'alert' or 'drop' and the 'signature' matches the CVE, or 'traffic' logs where 'destination_ip' or 'source_ip' are categorized as 'malicious' by Palo Alto Networks Dynamic Updates. Use the Strata Logging Service API for programmatic querying.
B. Programmatically fetch the malicious IPs from the TAXII/STIX feed using Python. Construct a dynamic SLQL query that filters 'traffic' logs for 'source_ip' or 'destination_ip' matching any of the fetched malicious IPs, and filter by 'time_generated' for the last 30 days. Execute the query via the Strata Logging Service API. Process the JSON response to extract 'source_ip', 'destination_ip', 'app', 'time_generated', and 'session_id'.
C. Manual export of traffic logs from Strata Logging Service, import into a local database, and then run SQL queries against the malicious IP list.
D. Configure syslog forwarding from Strata Logging Service to a separate SIEM. In the SIEM, ingest the TAXII/STIX feed and create correlation rules to identify matches between internal IPs and the malicious IPs.
E. Utilize the Strata Logging Service Query Language (SLQL) directly from the Strata Logging Service I-Jl. Manually paste each malicious IP into the query for 'destination_ip' or 'source_ip' fields and filter for the last 30 days. Export results to CSV.

Answer: B

Explanation:
This scenario demands automation and efficiency for rapid response. Option D outlines the most effective and programmatic approach: 1. Programmatically fetching the threat intelligence (malicious IPs) ensures the list is always up-to-date. 2. Dynamically constructing the SLQL query allows for searching against a large and potentially changing list of IPs. 3. Using the Strata Logging Service API is essential for automated, high-volume querying and structured data retrieval (JSON). 4. Filtering 'traffic' logs directly with the malicious IPs is the most direct way to find communication. While Option C mentions integrating TI into WildFire/Threat Prevention, this is for prevention and detection, not direct retrospective querying of all past communications with a newly identified malicious IP list. Option E is viable but less direct if the primary log source is already Strata Logging Service; it adds an extra layer of complexity. Options A and B are manual and inefficient for large datasets or dynamic threat intel.

NEW QUESTION # 121
A large enterprise uses Palo Alto Networks Panorama for centralized management of over 500 Next-Generation Firewalls (NGFWs) across various geographical locations. An incident response team identifies a new, highly evasive malware variant spreading rapidly. A critical security policy update needs to be deployed to block this threat across all firewalls within 30 minutes. Which of the following Panorama features and automation capabilities would be most effective in achieving this objective while minimizing human error?

A. Manual configuration pushes to individual device groups after creating a new security rule on each group.
B. Creating a new Security Profile Group, attaching it to existing security rules, and then performing a scheduled commit and push at the next maintenance window.
C. Implementing a new Decryption Policy across all firewalls to inspect all traffic, which will inherently block the malware.
D. Directly modifying the firewall configurations via SSH on each device and then manually pushing the changes from Panorama.
E. Utilizing a pre-defined Security Policy Rule that leverages Dynamic Address Groups (DAGs) updated via an external API feed from a threat intelligence platform, followed by an immediate commit and push to relevant device groups.

Answer: E

Explanation:
Option B is the most effective. Dynamic Address Groups (DAGs) allow for automatic updates of IP addresses or FQDNs based on external feeds (e.g., threat intelligence). When integrated with a security policy, changes to the DAG immediately affect the policy without requiring a manual commit/push for every IP update. A Panorama commit and push to relevant device groups then propagates the policy update efficiently. This minimizes human error and significantly reduces deployment time, crucial in a rapid response scenario. Options A, C, and D are less efficient and prone to error, especially at scale. Option E is not directly related to blocking a specific malware variant in a targeted, rapid manner and could have performance implications.

NEW QUESTION # 122
A multinational corporation uses Panorama for centralized management. A recent compliance audit highlighted that several regional firewalls have overly permissive 'any-any' rules that are rarely, if ever, used, creating unnecessary attack surface. The security team wants to systematically address these. Which sequence of operations, leveraging Policy Optimizer, would be most efficient and ensure minimal disruption?

A. 1. In Policy Optimizer, run a 'Rule Usage' report across all Device Groups. 2. For rules with zero or very low hit count, change action to 'Deny' and commit. 3. Monitor logs for complaints.
B. 1. In Policy Optimizer, identify all 'any-any' rules across relevant Device Groups using the 'Rule Browser'. 2. For each identified rule, change its action to 'Alert' and observe traffic patterns for a week. 3. If no legitimate traffic is logged, change action to 'Deny' and commit.
C. 1. Manually review each firewall's security policy for 'any-any' rules. 2. Delete the rules if they appear unused. 3. Push commits.
D. 1. Use Activity Insights to find the least used applications. 2. Create new policies to block these applications. 3. Push to firewalls.
E. 1. In Policy Optimizer, utilize the 'Security Policy Rule Optimization' dashboard. 2. Filter for 'Any-Any' rules with low hit counts. 3. For each candidate rule, use the 'Convert to specific' feature (if applicable) or change its action to 'Deny' after a validation period. 4. Push updates to respective firewalls.

Answer: E

Explanation:
Policy Optimizer's 'Security Policy Rule Optimization' dashboard specifically targets identifying and refining overly broad or unused rules. Filtering for 'Any-Any' with low hit counts directly addresses the auditor's concern. The 'Convert to specific' feature within Policy Optimizer is key for refining these rules rather than just deleting them, and if conversion isn't suitable, changing to 'Deny' after a validation period (which Policy Optimizer helps facilitate by showing usage over time) ensures minimal disruption while improving posture. The Panorama push ensures centralized enforcement.

NEW QUESTION # 123
......

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