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SecOps-Pro Probesfragen & SecOps-Pro Lerntipps

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SecOps-Pro Probesfragen & SecOps-Pro Lerntipps

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Palo Alto Networks Security Operations Professional SecOps-Pro Prüfungsfragen mit Lösungen (Q132-Q137):132. Frage
Your organization utilizes Palo Alto Networks XDR for unified security operations. An alert indicates a suspicious PowerShell script executing on a critical server, with an observed network connection to an uncommon external IP address. The XDR alert provides the following details:

Given this information, what is the most immediate and critical next step in the incident response process, and why? Assume '192.0.2.100' is an untrusted external IP.
  • A. Collect forensic artifacts (memory dumps, disk images) from the server for in-depth analysis later.
  • B. Decode the PowerShell encoded command to understand the malware's full functionality and then update antivirus signatures.
  • C. Initiate a full vulnerability scan on the server to identify the initial compromise vector.
  • D. Isolate the compromised server from the network using XDR's containment capabilities to prevent further compromise or lateral movement.
  • E. Notify senior management and legal counsel about the potential breach before taking any action.
Antwort: D
Begründung:
The encoded PowerShell command and external network connection strongly suggest active compromise and C2 communication. The most immediate and critical step is containment to prevent further damage. Isolating the server (B) using XDR's capabilities directly addresses this by stopping the threat's spread. Decoding the command (A) and collecting forensics (D) are important but come after containment. Vulnerability scanning (C) is a post-incident activity or part of proactive security, not an immediate response to an active compromise. Notifying management (E) is part of communication but not the first technical response.

133. Frage
An organization relies heavily on Palo Alto Networks Cortex XSOAR for security orchestration, automation, and response. A major incident involving ransomware has encrypted critical data across multiple departments. During the eradication phase, the incident response team needs to deploy a custom script to remove persistence mechanisms left by the ransomware and distribute a decryption tool. This script needs to run on hundreds of affected endpoints. Which XSOAR playbook command or integration would be most suitable and efficient for this task, ensuring proper execution and feedback?
  • A.
  • B. Manually log into each affected endpoint and run the cleanup script.
  • C.
  • D.
  • E.
Antwort: E
Begründung:
Option D is the most suitable and efficient. XSOAR excels at automating tasks across a large number of endpoints. The '!exec- remote-command' (or similar endpoint-management integration command, depending on the specific endpoint integration) allows for remote execution of scripts on designated systems, which is exactly what's needed for eradication. Option A is for communication. Option B is for incident creation, not execution. Option C shows a generic API call, but without a specific integration handling 'endpoint.execute_script' , it's not as direct as 'exec-remote-command'. Option E is highly inefficient and impractical for hundreds of endpoints.

134. Frage
Your organization uses Cortex XSIAM and has a strict policy that all high-severity incidents impacting sensitive data (categorized by a specific tag 'sensitive_data_impact') must immediately trigger a robust data leak prevention (DLP) workflow. This workflow involves: 1) Escalating the incident to a dedicated 'Data Incident Response' team, 2) Archiving all associated evidence to a secure, immutable storage, 3) Generating a compliance report with specific fields for auditing, and 4) Initiating a legal hold on affected user accounts. Select ALL Cortex XSIAM Playbook components and design principles that are essential to effectively implement this multi-faceted, high-assurance DLP workflow.
  • A. Leveraging a built-in 'Active Directory' or 'HR System' integration within a playbook task to identify the user's manager for legal hold notification and then using a 'ServiceNow' integration to initiate the legal hold request ticket.
  • B. Utilizing a 'Conditional' task at the beginning of the playbook to check for the 'sensitive_data_impact' tag, ensuring the DLP workflow only executes when necessary.
  • C. Implementing a custom JavaScript automation script within a playbook task to dynamically construct the compliance report by pulling incident data and populating pre-defined templates, then uploading it to a SharePoint site.
  • D. Employing 'Parallel' tasks to concurrently trigger the escalation to the 'Data Incident Response' team (e.g., via integration with a ticketing system) and initiate the evidence archiving process (e.g., via integration with a secure cloud storage API).
  • E. Relying solely on 'Manual Tasks' for each step of the DLP workflow to ensure human oversight and approval due to the sensitive nature of data.
Antwort: A,B,C,D
Begründung:
All options A, B, C, and D are essential for implementing such a robust, high-assurance DLP workflow in Cortex XSIAM, illustrating advanced playbook capabilities: A (Conditional Task): Absolutely critical. This ensures the complex DLP workflow is only triggered for incidents that truly meet the 'sensitive_data_impact' criteria, preventing unnecessary execution and false alarms. B (Parallel Tasks): Essential for efficiency. Escalation, archiving, and compliance reporting can largely happen concurrently, significantly speeding up response time for high-severity incidents. XSIAM's parallel task capability is key here. C (Custom Script for Compliance Report): For highly specific compliance reports with dynamic data and specific formatting requirements, a custom script (e.g., JavaScript) is often necessary to pull, process, and format data beyond what standard integrations might offer. Uploading to SharePoint also requires integration capabilities. D (Built-in Integrations for Legal Hold): Leveraging existing integrations (AD/HR for manager, ServiceNow for legal hold request) automates critical parts of the legal hold process, tying into existing IT/legal workflows. E (Manual Tasks): This option is incorrect as relying solely on manual tasks would defeat the purpose of automated incident response for a high-severity, policy-driven requirement, introducing delays and human error. While some review steps might be manual, the core triggering and execution should be automated.

135. Frage
A global financial institution uses Cortex XDR to protect its distributed environment. They encounter an incident where an insider, using legitimate credentials, accesses a sensitive database from an unusual location (geographical anomaly), executes a series of complex SQL queries to extract financial data, and then attempts to upload it to an unauthorized cloud storage service. The SOC analyst is presented with multiple alerts from different sources: a Prisma Access (SASE) alert for unusual login, a database activity monitoring (DAM) alert for suspicious queries, and a Cortex XDR endpoint alert for an unusual outbound network connection from the database server. Assume a scenario where Cortex XDR needs to integrate with a custom, in-house built application logging system for detailed SQL query data, which is not natively supported by a standard XDR connector. Which of the following options represents the most effective technical strategy to leverage Cortex XDR's Log Stitching for a complete, correlated incident story, including the custom log source?
  • A. Purchase a third-party SIEM solution that has a native connector for the custom application, and then integrate the SIEM with Cortex XDR only for alert forwarding, not raw log stitching.
  • B. Disable Log Stitching for the incident and manually investigate each alert from Prisma Access, DAM, and Cortex XDR endpoint alerts separately.
  • C. Develop a Cortex XDR Custom Ingestion API integration point. This would involve writing a custom parser (e.g., using a Lambda function or a dedicated log forwarder) to transform the in-house application logs into the XDR Common Information Model (CIM) format and pushing them to the XDR API, enabling real-time Log Stitching with other XDR data sources.
  • D. Implement a custom Python script to export the in-house application logs to a CSV file daily, then manually upload this CSV to Cortex XDR's Data Explorer for retrospective analysis, without real-time stitching.
  • E. Configure the in-house application to forward logs directly to a syslog server, and then configure Cortex XDR to ingest all syslog traffic for stitching.
Antwort: C
Begründung:
This question specifically targets the ability to extend Cortex XDRs Log Stitching capabilities to non-natively supported log sources in a sophisticated manner. Option A is retrospective and lacks real-time stitching. Option C might work for basic syslog, but without proper parsing and mapping to XDR's CIM, the data won't be contextually rich enough for effective stitching, especially for complex SQL queries. Option D introduces another complex system and only forwards alerts, not raw logs for deep stitching. Option E defeats the purpose of XDR. The most effective technical strategy is Option B: developing a custom ingestion pipeline using the Cortex XDR Custom Ingestion API. By transforming the custom logs into the XDR Common Information Model (CIM), these logs become first-class citizens within Cortex XDR, allowing the platform's advanced Log Stitching engine to seamlessly correlate them with endpoint, network, and cloud alerts, providing a complete and actionable incident timeline in real-time.

136. Frage
A financial institution uses Cortex XSOAR to manage threat intelligence. They have a strict requirement that all newly ingested indicators from external feeds must undergo a human review process before being pushed to enforcement points (e.g., firewalls, EDR). However, indicators with a 'critical' reputation (e.g., from highly trusted private feeds) should bypass this review for immediate blocking. Furthermore, the review process for 'high' reputation indicators should involve a specific team, while 'medium' reputation indicators can be reviewed by a different, larger team. How can Cortex XSOAR be configured to efficiently manage these complex workflows, leveraging indicator playbooks and reputation management?
  • A. Use 'Indicator Tags' to mark indicators for different review teams. Implement a 'Scheduled Job' that periodically queries indicators with specific tags and automatically assigns them to corresponding review queues. Critical indicators are not tagged for review.
  • B. Set up different 'Threat Intelligence Feeds' for each reputation level (Critical, High, Medium). Each feed would have a different 'Ingestion Playbook' configured to handle the specific review requirements and enforcement actions. Critical feeds' ingestion playbook would push directly to enforcement, others would include review tasks.
  • C. The only way to achieve this is to manually adjust the reputation of each indicator post-ingestion, which then triggers predefined automations for blocking or review. Critical indicators would be manually set to 'critical' to bypass review.
  • D. Create three separate 'Indicator Playbooks': one for 'Critical', one for 'High', and one for 'Medium' reputation. Manually trigger the correct playbook after each indicator ingestion. Critical indicators' playbook would have no review, others would include manual review tasks assigned to specific user groups.
  • E. Configure a single 'Indicator Playbook' with conditional tasks based on indicator reputation. Use 'Manual Task' for human review, and 'Conditional Branches' to assign tasks to different teams using 'Task Assignee' based on reputation. Critical reputation indicators would follow a branch that bypasses manual tasks.
Antwort: B,E
Begründung:
Both A and C are viable and robust solutions for this complex scenario, demonstrating advanced XSOAR capabilities. Option A (Single Indicator Playbook with Conditionals): This is a highly efficient way to manage varied workflows within a single playbook. Upon indicator ingestion (which can be from any feed), a single indicator playbook is triggered. Inside this playbook: A 'Conditional Branch' (e.g., indicator.reputation 'Critical") directs critical indicators to a path that immediately pushes to enforcement, bypassing any manual review tasks. Other branches Celif indicator.reputation 'High" and 'elif indicator.reputation 'Medium") would contain 'Manual Task' steps. The 'Task Assignee' for these manual tasks can be dynamically set to different user groups or roles based on the indicator's reputation, achieving team-specific reviews. Option C (Multiple Feeds with Dedicated Ingestion Playbooks): This approach leverages the flexibility of feed-specific ingestion playbooks. If the source feeds themselves reliably categorize reputation: You could configure separate 'Threat Intelligence Feeds' for sources known to provide 'Critical', 'High', or 'Medium' reputation indicators (or simply categorize the feeds themselves). Each feed would then be configured with a distinct 'Ingestion Playbook'. The 'Critical Feed's Ingestion Playbook' would immediately push to enforcement. The 'High Feed's Ingestion Playbook' would include a 'Manual Task' assigned to 'Team High'. The 'Medium Feed's Ingestion Playbook' would include a 'Manual Task' assigned to 'Team Medium'. Both approaches are valid and the choice might depend on how the threat intelligence is received and categorized upstream. Option B is inefficient due to manual triggering. Option D is reactive and less immediate. Option E is entirely manual and defeats the purpose of automation.

137. Frage
......
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