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| Section | Objectives |
|---|---|
| Topic 1: Threat Detection and Incident Response | - Incident response lifecycle - Malware analysis fundamentals - Threat intelligence and analysis |
| Topic 2: Threat Hunting and Analytics | - Hypothesis-driven threat hunting - Log analysis and behavioral detection |
| Topic 3: Security Operations Fundamentals | - Security monitoring and alert triage concepts - SOC workflows and operating models |
| Topic 4: Palo Alto Networks Security Operations Platforms | - Cortex XDR detection and response - Cortex XSOAR automation and orchestration concepts - Security data ingestion and correlation |
| Topic 5: Automation and SOAR Processes | - Case management and enrichment - Playbook design and automation logic |
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NEW QUESTION # 36
A new incident in Cortex XSIAM contains WildFire malware and Behavioral Threat Protection (BTP) alertsout an unsigned process attempting to dump the memory of Isass.exe. Which initial verdict applies to this incident?
Answer: C
Explanation:
Alerts from WildFire and Behavioral Threat Protection on an unsigned process dumping LSASS memory indicate malicious activity, making it a true positive.
NEW QUESTION # 37
Your organization uses Cortex XSIAM and has recently integrated a new custom application that generates unique security events not covered by standard XSIAM parsers. You need to ingest these logs, parse them into a structured format, and create a custom BIOC rule to detect a specific sequence of these application events indicative of fraud. Outline the process in XSIAM and identify the key components involved.
Answer: C
Explanation:
This scenario tests the understanding of custom log ingestion, parsing, and custom BIOC creation in XSIAM, which is a crucial skill for a 'Security Operations Professional'. Option B accurately describes the end-to-end process: 1. Data Ingestion : Using appropriate data collectors to get the raw logs into XSIAM. 2. Data Onboarding/Parsing : XSIAM requires a defined schema for custom logs. This involves creating a custom parser (often through regular expressions like GROK or by defining JSON paths) to extract structured fields from the raw, unstructured logs. 3. BIOC Rule Creation : Once the data is normalized and structured, a custom BIOC rule can be written using XQL. The event _ sequence command is specifically designed for detecting multi-stage behavioral patterns, making it perfect for detecting a sequence of application events indicative of fraud. The other options either oversimplify the process, misrepresent XSIAM's capabilities, or suggest incorrect methods.
NEW QUESTION # 38
Which two types of tasks are supported in Cortex XSIAM playbooks? (Choose two.)
Answer: A,B
Explanation:
Cortex XSIAM playbooks utilize a structured workflow to automate SOC processes. The task types define how the logic flows through the playbook:
* Sub-playbook (A): This allows an analyst to call another existing playbook as a single step within a larger workflow. This is crucial for modularity, such as having a standard "IP Enrichment" sub- playbook that is used inside multiple different parent playbooks (e.g., Phishing and Brute Force).
* Conditional (C): These are "decision" nodes (often visualized as Yes/No or multiple-choice branches).
They evaluate data from previous steps to determine which path the playbook should take next.
* Data Collection (D): While "Data Collection" tasks (like surveys/forms) are supported in XSOAR , the core task types in the native XSIAM automation engine emphasize Standard , Conditional , and Sub- playbook tasks.
* Note on Scripting: While you can run an automation script (Python) as a "Standard" task, "Script creation" is a development activity, not a functional task type within an active playbook.
NEW QUESTION # 39
What are two outcomes of threat intelligence in a SOC? (Choose two.)
Answer: A,C
NEW QUESTION # 40
Which response action in Cortex XSIAM would be unavailable to a SOC analyst investigating an incident involving a Linux server?
Answer: A
Explanation:
Cortex XSIAM (and XDR) agents provide a wide array of response actions, but these capabilities vary based on the operating system of the endpoint.
* File Search and Destroy: This specific automated management action-which allows an administrator to search for a file across multiple endpoints and delete it in one click-is currently supported for Windows and macOS endpoints. It is not a native automated response action for Linux in the same
"Search and Destroy" menu context.
* Supported Linux Actions: * Live Terminal (B): Analysts can initiate a remote SSH-like session to Linux endpoints for manual investigation.
* Running a Script (C): Analysts can execute Python scripts on Linux endpoints to gather data or perform custom remediation.
* Halting Network Access (D): Also known as Endpoint Isolation , this allows the analyst to cut off all network traffic to the Linux server except for the connection to the Cortex console.
NEW QUESTION # 41
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