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Palo Alto Networks XSIAM Engineer Sample Questions (Q370-Q375):

NEW QUESTION # 370
A Security Operations Center (SOC) using Palo Alto Networks XSIAM has implemented a new set of detection rules. After initial deployment, they observe a high volume of low-fidelity alerts for legitimate administrative activities, leading to alert fatigue. Which of the following content optimization strategies involving scoring rules would be most effective in mitigating this issue without completely suppressing valuable security alerts?

A. Configure all alerts to automatically be suppressed for 24 hours after their initial generation.
B. Create a new scoring rule that assigns a lower reputation score to alerts originating from known, whitelisted administrative IPs or specific service accounts when associated with 'successful login' events, effectively reducing their overall criticality.
C. Modify the global alert threshold in XSIAM to only show alerts with a score above 90, ignoring all others.
D. Increase the severity score of all newly generated alerts across the board to ensure critical events are prioritized.
E. Disable all detection rules that are generating excessive alerts, regardless of their potential security value.

Answer: B

Explanation:
Option B is the most effective content optimization strategy. By using scoring rules to assign lower reputation scores to known benign activities (e.g., successful logins from whitelisted administrative IPs), the overall criticality of these alerts is reduced. This helps in de-prioritizing noise without completely suppressing the underlying detection rules, allowing the SOC to focus on higher-fidelity threats. Option A would exacerbate alert fatigue. Option C would lead to significant blind spots. Option D is a temporary band-aid and could hide legitimate threats. Option E is too blunt and would likely miss important alerts below the arbitrary threshold.

NEW QUESTION # 371
Which step must be taken to enable Cloud Identity Engine on Cortex XSIAM?

A. Enable SSO integration.
B. Activate it on HUB.
C. Activate it in the Customer Support Portal.
D. Enable Active Directory log collection.

Answer: B

Explanation:
To enable Cloud Identity Engine on Cortex XSIAM, it must first be activated on HUB, Palo Alto Networks' centralized service management platform. Once activated, it can be configured and integrated with Cortex XSIAM for identity-based visibility and enforcement.

NEW QUESTION # 372
During a Red Team exercise, a lateral movement technique using WMI (Windows Management Instrumentation) was successfully executed but went undetected by existing XSIAM indicator rules. The technique involved creating a WMI permanent event subscription to execute a malicious script when a specific event occurs (e.g., system startup). The SOC needs a new indicator rule to detect this specific activity. Which XDR dataset and fields are crucial for building this rule, and what XQL operator would be most appropriate for matching the malicious WMI actions?

Answer: B

Explanation:
Option C is the most accurate for detecting WMI permanent event subscriptions. XSIAM collects specific ' WMI Permanent Event Subscription' event types that directly capture this activity. The key fields to look for are (which indicates what action the subscription will take, e.g., running a command line) and (which defines the triggering event). Using an exact match for the event type and 'contains' or 'regex' for the specific consumer and filter values provides high fidelity. Options A, B, D, and E are too generic or focus on indirect indicators rather than the direct WMI event subscription. While 'wmic.exe' can be used to manage WMI, direct WMI event logging is more reliable for detecting persistent subscriptions.

NEW QUESTION # 373
An XSIAM engineer is tasked with optimizing a 'Phishing Email Received' detection rule. The SOC observes that while the rule correctly identifies phishing attempts, those targeting entry-level employees are often over-prioritized compared to those targeting C-level executives. The engineer decides to leverage XSIAM's User Criticality feature, populated from HR data'. Which approach using scoring rules will effectively de-prioritize alerts for low-criticality users while boosting those for high-criticality users?

A. Modify the 'Phishing Email Received' detection rule directly by embedding an XQL subquery to fetch and dynamically adjust the rule's 'rule_weight' based on it.
B. Create a single scoring rule that uses the 'Set Total Score' action with an XQL 'case' statement to assign a fixed score (e.g., 20 for low, 90 for high) based on alert.user_criticality' .
C. Create a scoring rule for 'alert.user_criticality = 'High" with a 'Multiplicative Score Change' of xl .8, and another for 'alert.user_criticality = 'Low" with a 'Multiplicative Score Change' of x0.6. Ensure the 'High' rule has a higher 'Order'.
D. Configure a single scoring rule where the condition is always true, and the action applies a 'Multiplicative Score Change' using a lookup table to fetch the multiplier based on 'alert.user_criticality' (e.g., Low: 0.6, Medium: 1.0, High: 1.8).
E. Implement two separate scoring rules: one for 'alert.user_criticality = 'Low'' with an 'Additive Score Change' of -30, and another for = 'High" with an 'Additive Score Change' of +40, ensuring the 'High' rule has a lower 'Order' to apply first.

Answer: B,C

Explanation:
Options A and C are effective ways to achieve the goal using XSIAM scoring rules. Option A (Set Total Score with 'case' statement): This is a powerful method for directly setting the final score based on a specific attribute. By using a 'case' statement, you can assign precise score values (e.g., 20 for low, 90 for high) based on user criticality, effectively overriding prior scoring and establishing a clear prioritization. This is suitable when you want a strong, decisive impact on the final score. Option C (Separate Multiplicative Rules): This is also a highly effective and common approach. Using multiplicative changes (xl .8 for High, x0.6 for Low) allows you to proportionately increase or decrease the alert's score based on user criticality, while still considering the initial base score and other factors. This provides flexibility and maintains the relative impact of the original detection. Ensuring the 'High' rule has a higher 'Order' is crucial if its multiplier is meant to be applied after other potential additive changes, or if it needs to take precedence in the multiplicative chain. Option B (Separate Additive Rules with Misplaced Order): While additive changes are good, placing the 'High' rule with a lower order than potentially other rules that might reduce the score could lead to an unintended final score. Generally, rules meant to have a strong final impact (like asset/user criticality) are placed with higher orders or use 'Set Total Score'. Option D (Lookup Table for Multiplicative Change in a Single Rule): While lookup tables are valuable for enriching data, directly fetching a 'multiplier' for a 'Multiplicative Score Change' action from a lookup table within a single scoring rule's action logic in this exact dynamic way isn't typically how XSIAM's scoring rule UI functions for dynamic action values (it usually expects fixed values or simple field references). Option E (Modify Detection Rule): Modifying the detection rule directly to dynamically adjust 'rule_weight' based on user_criticality' is not a standard or supported way to leverage 'rule_weight' in XSIAM. 'rule_weight' is generally a static property of the rule, and dynamic score adjustments are managed through scoring rules.

NEW QUESTION # 374
A large enterprise's XSIAM deployment is generating a high volume of alerts. The SOC manager needs a dashboard to help prioritize incident investigations. This dashboard should display: 1) Alerts grouped by 'Threat Category' (e.g., Malware, Phishing), 2) A breakdown of 'Alert Severity' within each category, and 3) A 'Normalized Score' for each alert, calculated as (Severity_Weight Asset_Criticality_Score). The 'Asset_Criticality_Score' is derived from an external CMDB imported as a custom lookup. Which XQL operations and dashboard widget types are required to construct this prioritization dashboard? (Select all that apply)

A. Option D
B. Option E
C. Option C
D. Option B
E. Option A

Answer: A,B,D,E

Explanation:

NEW QUESTION # 375
......

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