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Palo Alto Networks XSIAM Engineer Sample Questions:

1. A Security Operations Center (SOC) team is leveraging Palo Alto Networks XSIAM for Attack Surface Management (ASM). They've identified a new critical vulnerability (CVE-2023-XXXX) affecting a specific version of Apache Tomcat running on several of their internal servers. The existing ASM detection rules do not specifically cover this CVE. Which of the following XSIAM capabilities would be most effective for a Security Engineer to quickly deploy a custom detection rule to identify instances of this vulnerable Tomcat version, considering both network-based and host-based telemetry?

A) Configuring a new alert profile in XSIAM to trigger on any network traffic destined for known Apache Tomcat ports.
B) Implementing a new SOAR playbook in XSIAM that integrates with a vulnerability scanner to automatically scan and report on Tomcat instances.
C) Developing a custom XQL query within the XSIAM Query Builder that identifies the Tomcat version from network session logs and endpoint inventory data, then saving it as a new ASM rule.
D) Creating a new custom indicator of compromise (IOC) in the XSIAM IOC Management module and associating it with existing threat feeds.
E) Modifying an existing XSIAM out-of-the-box rule to include the new CVE ID as a string match in its detection logic.

2. A Security Operations Center (SOC) team using Palo Alto Networks XSIAM needs a custom dashboard to monitor anomalous login attempts and compare them against a baseline of typical user behavior over the last 30 days. The dashboard must alert on deviations exceeding 3 standard deviations from the mean. Which XSIAM dashboard components and data sources are most appropriate for this requirement?

A) Cortex XDR incident response playbooks configured to send email alerts, bypassing the need for a dashboard.
B) XQL queries on authentication_logs with timechart and stdev functions, visualized using 'Trend' widgets.
C) Manual review of raw event collector data exported to a CSV and analyzed in an external spreadsheet.
D) Log forwarding to a SIEM for correlation, as XSIAM dashboards lack advanced statistical anomaly detection.
E) Pre-built 'User Behavior Analytics' widgets without custom modifications, as they automatically handle baselining.

3. A company is automating Cortex XSIAM agent deployment using Ansible. The challenge is to install the agent and ensure it's registered with the correct agent group dynamically, without hardcoding group names into the playbook, as new groups are frequently created. The XSIAM API documentation provides endpoints for retrieving agent group information. Which of the following Ansible playbook snippets best demonstrates the concept of dynamic agent group assignment using the XSIAM API during installation?

A)

B)

C)

D)

E)

4. A financial institution is deploying XSIAM and intends to automate its privileged access management (PAM) integration. Specifically, when a critical XSIAM alert indicates potential compromise of a privileged account, the workflow should automatically initiate a password rotation for that account via their Delinea Secret Server PAM solution. The critical challenge is securely authenticating XSIAM to the Delinea API without hardcoding credentials in playbooks. Which secure integration method should be prioritized?

A) Relying on IP whitelisting alone for Delinea API access, without any API key.
B) Manually inputting the Delinea API key into each playbook run.
C) Passing the Delinea API key as a plaintext parameter in the XSIAM playbook's trigger.
D) Using a dedicated XSIAM 'App' or 'Connection' configured with an API token retrieved from a secure secret management solution like HashiCorp Vault, accessed via an XSIAM connector.
E) Storing the Delinea API key directly within the XSIAM playbook's action configuration.

5. A large enterprise is migrating its legacy SIEM data into Palo Alto Networks XSIAM. The original SIEM data schema is highly denormalized, leading to redundant information and inefficient querying for threat hunting. To optimize content and improve query performance, a data normalization strategy is critical. Which of the following data modeling rules, when applied within XSIAM's content optimization framework, would be most effective in achieving Third Normal Form (3NF) for event data, specifically for a 'Login Event' dataset?

A) Consolidate 'user_id', 'username', 'email', and 'department' into a single 'user_profile' field using a JSON object to minimize join operations.
B) Store all 'login_attempts' for a user within a nested array directly inside the 'user_profile' field to maintain contextual integrity.
C) Apply a rule to automatically normalize 'country_code' and 'city' from 'source_ip' using an external geo-IP database, storing them as separate attributes.
D) Create a separate lookup table for 'device_info' containing 'device_id', 'device_name', 'os_version', and 'device_owner', and link it to the main 'Login Event' table via 'device id'.
E) Ensure that 'login_type' (e.g., 'SSO', 'Local', 'VPN') is directly dependent only on the 'event_id' and not on any other non-key attributes like 'source_ip'.

Solutions: