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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: XSOAR Automation and Orchestration | 30% | - Integration Management - Playbook Development - Incident Classification and Severity |
| Topic 2: Security Operations Foundations | 20% | - Incident Response Lifecycle - SOC Roles and Responsibilities - Threat Intelligence Frameworks |
| Topic 3: Reporting and Metrics | 20% | - Incident Reporting - SOC Performance Metrics - Dashboard Customization |
| Topic 4: Detection and Analysis | 30% | - Endpoint and Network Forensics - Malware Triage - Log Analysis (XSIAM/Prisma) |
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NEW QUESTION # 110
A Security Operations Center (SOC) analyst is performing threat hunting based on an observed surge in outbound DNS requests to unusual top-level domains (TLDs) from internal hosts, specifically from a segment traditionally used by financial analysts. These TLDs are not typically seen in legitimate business traffic. The threat intelligence team has recently reported an increase in Cobalt Strike beaconing activity leveraging DNS over HTTPS (DOH) to obscure C2 communications. Which of the following Splunk Search Processing Language (SPL) queries would be most effective in identifying suspicious DNS-related indicators of compromise (IOCs) aligned with this threat, assuming 'pan_logS is the relevant sourcetype for Palo Alto Networks firewall logs?
Answer: C
Explanation:
The scenario specifically mentions 'DNS over HTTPS (DOH)' and 'unusual TLDs' and 'Cobalt Strike beaconing'. Option C directly addresses DOH by filtering for (common for HTTPS) and then correlates it with or , which are strong indicators of DOH traffic attempting to bypass traditional DNS monitoring. While other options might identify general DNS anomalies, Option C is the most targeted and effective for the described threat given the specific indicators. Option B is good for unusual TLDs but misses the DOH aspect and relies on a pre-defined lookup. Option A is too broad and only looks for specific TLDs rather than anomalies. Option D looks for non-standard DNS ports, but DOH uses 443. Option E relies on an undefined macro.
NEW QUESTION # 111
What is involved in the day-to-day role of a triage specialist?
Answer: B
Explanation:
Triage specialists manage and configure monitoring tools, reviewing alerts and determining which incidents require escalation.
NEW QUESTION # 112
A security incident, 'MalwareDetectedOnEndpoint', is triggered in Cortex XSIAM. The associated playbook, P -malware-Response
, is initiated. An analyst observes that while the playbook successfully quarantined the endpoint, the subsequent 'Fetch File Hash for Threat Intel' task failed due to network connectivity issues from the affected endpoint. The next task, 'Check Threat Intelligence Platforms', is a dependent task. What is the most appropriate Playbook design or operational consideration to ensure resilience and effective progression in such a scenario?
Answer: D
Explanation:
Option B demonstrates robust playbook design for resilience. A retry mechanism addresses transient issues like network connectivity. Making 'Check Threat Intelligence Platforms' a 'Conditional' task, dependent on the successful acquisition of the hash, prevents the playbook from proceeding with incomplete data, while allowing other independent, successful actions (like quarantine) to stand. Option A can lead to proceeding with incomplete or incorrect information. Option C is overly aggressive and reduces automation benefits. Option D removes a critical step. Option E can lead to incomplete incident handling.
NEW QUESTION # 113
During the 'Post-lncident Activity' phase of the NIST Incident Response Plan, an organization discovers that a complex multi-stage attack involving advanced persistent threat (APT) techniques successfully exfiltrated highly sensitive dat a. The post-mortem analysis reveals gaps in threat intelligence integration and automated response capabilities. Which of the following improvements, aligning with Palo Alto Networks security practices, would best address these identified gaps to strengthen future 'Preparation' and 'Detection and Analysis' phases for similar advanced threats?
Answer: A
Explanation:
The 'Post-lncident Activity' phase includes lessons learned and improvements. The scenario specifically points to 'gaps in threat intelligence integration and automated response capabilities' for complex multi-stage attacks. - A: Implementing Cortex XSOAR playbooks with AutoFocus and WildFire integration directly addresses both gaps. XSOAR automates the enrichment of alerts with context from global threat intelligence (AutoFocus, WildFire) and orchestrates automated responses, significantly enhancing the 'Detection and Analysis' accuracy and the speed/efficiency of 'Preparation' by defining automated actions for future similar incidents. This is precisely about integrating intelligence and automating responses. - B, C, D, and E are all valid security improvements, but they do not directly address the specific gaps identified (threat intelligence integration and automated response) as effectively as XSOAR and its capabilities. Patching (B), scans (C), and micro-segmentation (D) are about reducing attack surface and improving network controls, while email security (E) focuses on one attack vector. While beneficial, none specifically enhance the integration of threat intelligence for analysis or automate complex, multi-tool responses to APTs like XSOAR does.
NEW QUESTION # 114
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: A
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 # 115
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