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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Incident Response | 25% | - Roles and responsibilities in incident response - Incident response lifecycle and frameworks - SOAR, EDR, XDR technologies - Documentation, reporting, and post-incident review - Containment, eradication, and recovery procedures |
| Topic 2: Proactive Threat Detection | 12% | - Threat hunting methodologies and techniques - Threat intelligence types and sources - Integrating threat intelligence into SOC workflows - UEBA and advanced detection methods |
| Topic 3: Security Operations and Management | 5% | - SOC components: people, processes, technology - SOC implementation and operational models - SOC fundamentals and objectives |
| Topic 4: Incident Detection with SIEM | 25% | - SIEM architecture, components, and deployment models - Data ingestion, parsing, and normalization - SIEM dashboards and reporting - Correlation rules and alert generation - Alert triage, prioritization, and false positive reduction |
| Topic 5: Forensic Investigation and Malware Analysis | 5% | - IoC extraction and evidence handling - Digital forensics fundamentals in SOC context - Malware types, behavior, and analysis techniques |
| Topic 6: SOC for Cloud Environments | 5% | - Cloud security monitoring challenges - Cloud log collection and analysis - Cloud threat detection and response |
| Topic 7: Log Management | 15% | - Log normalization, correlation, and retention policies - Events vs incidents vs logs - Log sources, types, and collection methods - Centralized logging architecture |
| Topic 8: Understanding Cyber Threats, IoCs, and Attack Methodology | 8% | - Types of cyber threats and threat actors - Network, host, and application-level attacks - Attack frameworks and methodologies - Indicators of Compromise (IoCs) and Indicators of Attack (IoAs) |
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問題 #58
What does [-n] in the following checkpoint firewall log syntax represents?
fw log [-f [-t]] [-n] [-l] [-o] [-c action] [-h host] [-s starttime] [-e endtime] [-b starttime endtime] [-u unification_scheme_file] [-m unification_mode(initial|semi|raw)] [-a] [-k (alert name|all)] [-g] [logfile]
答案：A
問題 #59
John, a SOC analyst, while monitoring and analyzing Apache web server logs, identified an event log matching Regex /(\.|(%|%25)2E)(\.|(%|%25)2E)(\/|(%|%25)2F|\\|(%|%25)5C)/i.
What does this event log indicate?
答案：D
解題說明：
問題 #60
An organization with a complex IT infrastructure is planning to implement a SIEM solution to improve its threat detection and response capabilities. Due to the scale and complexity of its systems, the organization opts for a phased deployment approach to ensure a smooth implementation and reduce potential risks. Which of the following should be the first phase in their SIEM deployment strategy?
答案：D
解題說明：
The first phase should establish reliable log ingestion and storage-log management-before attempting advanced detection content or automation. A SIEM is only as effective as the data it receives. In a complex environment, initial success depends on building a stable pipeline: collecting logs from priority sources, normalizing timestamps, ensuring consistent parsing, defining retention, and validating data quality (completeness, latency, duplication, and integrity). Without this foundation, analytics will produce blind spots, false positives, and missed detections, and automation may take disruptive actions based on incomplete data. UEBA and security analytics are valuable but require sufficient historical, high-quality telemetry to build baselines and correlations. Similarly, incident response automation should come after the organization has validated detections, tuning, and operational workflows; otherwise, playbooks may amplify errors at scale. A phased approach typically starts with identifying key data sources (identity, endpoint, network, cloud), onboarding them into log management, confirming visibility and schema consistency, and only then layering detection rules, correlations, and response workflows. Therefore, setting up log management first is the correct starting phase for a low-risk, high-success SIEM deployment.
問題 #61
SecureTech Solutions, a managed security service provider (MSSP), is optimizing its log management architecture to enhance log storage, retrieval, and analysis efficiency. The SOC team needs logs stored in a structured or semi-structured format for easy parsing, querying, and correlation. They choose a format that organizes data in a text file in a tabular structure, where each log entry is stored in rows and columns, and that supports easy export to databases or spreadsheet analysis while maintaining readability. Which log format should they choose?
答案：B
解題說明：
CSV is a structured, tabular text format where each record is a row and fields are separated by commas, making it easy to parse, import into spreadsheets, and export into databases. The scenario specifically calls for a text file with rows and columns, readability, and easy export to databases or spreadsheet-based analysis- these are classic CSV strengths. Cloud storage is a storage location/architecture, not a log format. Syslog is a transport and message format family used for sending event messages from systems and network devices; it is often semi-structured but not inherently "rows and columns" in a tabular file structure. A database is a storage system rather than a file format; while logs can be stored in databases, the question asks specifically for a text file format. In SOC practice, CSV is commonly used for exporting specific datasets for reporting, offline analysis, and sharing with stakeholders, especially when interoperability is needed. For high-scale SIEM ingestion, formats like JSON are often preferred, but given the explicit requirement for a tabular text file compatible with spreadsheets, CSV is the correct choice.
問題 #62
A newly hired SOC analyst at a fast-growing multinational organization must quickly assess the company's external exposure and identify potential security risks. Techniques considered include analyzing publicly available information, scanning exposed services, reviewing DNS records, and gathering external intelligence.
Due to the scale across subsidiaries, cloud environments, and third-party integrations, some methods may not scale well and may lead to delays or incomplete insights. Which technique is less practical for handling large or diverse data sets in this scenario?
答案：D
解題說明：
Stack counting is less practical for large, diverse infrastructures because it is often a manual, piecemeal method of identifying and categorizing technology stacks across many assets. In complex multinationals, external exposure spans multiple domains, cloud tenants, third parties, and business units; a "stack counting" approach can become slow, incomplete, and quickly outdated without automation and authoritative asset inventories. DNS lookups can be automated at scale to map domains, subdomains, and records, making them practical for large environments. Web enumeration can also be scaled using automated scanners and discovery tooling (with appropriate authorization), though it may require careful rate limits and scoping.
OSINT can scale through specialized tooling and feeds, though validation is necessary. Compared to these, stack counting is typically the least scalable approach because it relies heavily on manual inference and continuous revalidation. From a SOC standpoint, scalable exposure assessment depends on automated asset discovery, DNS and certificate transparency analysis, cloud inventory, and controlled scanning-methods that can cover breadth without relying on manual "counting stacks" across thousands of assets.
問題 #63
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