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XSIAM-Engineer熱門題庫，XSIAM-Engineer資料

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最新的 Security Operations XSIAM-Engineer 免費考試真題 (Q223-Q228):

問題 #223
An XSIAM engineer is tasked with optimizing a large volume of endpoint telemetry data, specifically 'Process Creation' events. The raw logs contain highly granular details, including 'process _ path', 'command_line', 'parent_process_id', 'user_sid', and 'hash_md5'. To improve query performance for common threat hunting queries (e.g., 'find all processes launched from a specific path' or 'identify processes with suspicious command-line arguments'), the engineer decides to normalize and enrich the dat a. Which XSIAM content optimization rule (represented conceptually) would best facilitate efficient querying for the 'process_path' and 'hash_md5' attributes?

答案：D

解題說明：
To improve query performance for common threat hunting queries on 'process_path' and 'hash_md5', normalization and proper indexing are key. Option B suggests normalizing 'process_path' (e.g., consistent casing, removing redundant characters) which aids in exact matching and range queries, and crucially, it explicitly states 'index_field' for 'hash_md5' as a 'keyword'. Indexing 'hash_md5' as a keyword type is highly efficient for exact lookups, which is typical for hash matching in security investigations. Option A is about extraction and enrichment but doesn't directly address query performance for existing fields. Option C is about joining and aggregation. Option D is about filtering and mapping. Option E is about aliasing and tagging, which are useful but don't directly tackle the underlying data structure for query optimization as effectively as normalization and indexing.

問題 #224
A global enterprise has mandated that all incident response playbooks in XSIAM must include a step to log key actions and their outcomes to an external, immutable audit logging service (e.g., Splunk). This includes actions taken by XSIAM's built-in commands (e.g., 'isolate endpoint') and custom commands. The logging must occur regardless of whether the action succeeds or fails. How can an XSIAM engineer efficiently implement this requirement across numerous playbooks while minimizing redundant code and ensuring comprehensive logging?

A. Manually add a 'Send to Splunk' custom command after every critical action in each playbook, with conditional logic for success/failure.
B. Leverage XSIAM's native audit logs export feature to send all playbook execution details to Splunk, then parse the relevant action outcomes.
C. Develop a 'Custom Automation' (e.g., a Pre-Process or Post-Process rule) that monitors all playbook actions and forwards the details to Splunk without explicit calls in the playbook.
D. Modify the source code of XSIAM's built-in commands to include Splunk logging functionality directly.
E. Create a 'Sub-playbook' that encapsulates the 'Send to Splunk' logic and call this sub-playbook after every action in the main playbooks, passing the action's status as an input.

答案：B,E

解題說明：
This question allows for multiple correct answers depending on the interpretation of 'efficiently' and 'comprehensive'. Option B (Sub-playbook): This is highly efficient for targeted logging of specific actions within playbooks. By creating a reusable sub-playbook, you centralize the logging logic. You pass the action's name, status, and any relevant data as inputs to this sub-playbook, and it handles the Splunk integration. This minimizes redundant code within each main playbook and ensures consistency in what's logged for specific actions. Option D (XSIAM's native audit logs export): XSIAM generates extensive audit logs for all platform activities, including playbook executions, command invocations (built-in and custom), and their success/failure status. Exporting these native audit logs to Splunk (via a data connector or API) is the most comprehensive way to capture all actions taken by XSIAM's automation engine without needing to modify individual playbooks. The challenge here is parsing and correlating the relevant action outcomes from the verbose audit log, but it provides a holistic view. This is usually preferred for a 'mandated' enterprise-wide requirement. Option A is highly inefficient and prone to errors. Option C (Custom Automation rules) are more for enforcing pre/post conditions on incidents or alerts , not directly for logging arbitrary playbook command executions. Option E is impossible as XSIAM commands are not open-source or meant for modification in this manner.

問題 #225
An XSIAM Playbook is designed to interact with a custom-built internal application via its REST API for asset management. The API requires a Bearer token, which is obtained by authenticating against an OAuth 2.0 endpoint every 60 minutes. The Playbook needs to store this token securely and refresh it as needed for subsequent API calls. Which XSIAM features are best suited for managing this authentication mechanism within the Playbook workflow? (Select all that apply)

A. Fetch Data task to retrieve the token from the XSIAM Key-Value Store.
B. Create Custom Field to store the token in the incident.
C. Generic API call task to perform the OAuth 2.0 token request.
D. Store Data task to save the token in the XSIAM Key-Value Store.
E. use an Incident Field as a variable to pass the token between tasks.

答案：A,C,D

解題說明：
To manage this, you'd use a 'Generic API Call' (C) to request the OAuth tokem Once received, the 'Store Data' task (B) is crucial for securely persisting the token in the XSIAM Key-Value Store, which is designed for storing sensitive and persistent data across playbook runs or for later retrieval. SubsequentAPI calls would then use a 'Fetch Data' task (D) to retrieve the current token from the Key-Value Store. Storing it in a custom incident field (A) is not suitable for persistence across different incidents or for long-term secure storage, and simply using an incident field (E) doesn't address secure storage or refresh logic. The Key-Value Store is the intended secure storage mechanism for such dynamic credentials.

問題 #226
An XSIAM engineer is performing content optimization on indicator rules. They notice that a rule designed to detect 'suspicious process injections' is generating an alarmingly high number of alerts, primarily from legitimate debugging tools and application updates. The current rule uses a broad XQL query:

To reduce false positives without compromising the detection of malicious injections, which of the following modifications or considerations would be most effective? (Select all that apply)

A. Refine the XQL query to include additional conditions such as 'target_process_integrity_level = 'System" or 'injection_type = 'remote" if the data is available, as these are often indicators of malicious activity.
B. Implement a 'risk_score' threshold for the rule, only generating alerts if the aggregated risk score of the host or user exceeds a certain value.
C. Adjust the rule's 'time window' for correlation to a shorter duration, assuming malicious injections are instantaneous.
D. Add a filter for to exclude injections originating from known legitimate processes like Visual Studio or trusted update services.
E. Create a pre-filtering rule with higher precedence to explicitly suppress alerts for processes with valid digital signatures and known clean hashes.

答案：A,D,E

解題說明：
Options A, C, and D are all effective strategies for reducing false positives in this scenario. A: Filter by parent_process_name: Legitimate debugging or update tools often have predictable parent processes. Excluding injections originating from these known legitimate parents is a highly effective way to reduce noise. C: Refine with additional conditions: Malicious injections often target high-privilege processes or occur remotely. Leveraging fields like or 'injection_type' (if available in XDR data for 'Process Injection' events) makes the rule more precise for malicious intent. D: Pre-filtering with digital signatures/hashes: Legitimate software has valid digital signatures and known hashes. Suppressing alerts for processes matching these criteria is a very strong method to filter out benign events. This often involves creating a separate pre-filtering rule or leveraging XSIAM's trusted signer/hash capabilities. Option B (risk_score threshold) is a reactive measure for alert triage, not a content optimization for the rule itself. It still generates the underlying alert but might not escalate it. Option E (shorter time window) is generally not applicable to instantaneous events like process injection, and might cause detection gaps for multi-stage attacks.

問題 #227
You are integrating a highly specialized Industrial Control System (ICS) log source with XSIAM. The ICS device exports logs using a custom binary protocol over UDP, encapsulating structured XML fragments within a proprietary header and footer. Due to strict operational technology (OT) network segmentation, direct API integration is not feasible. An intermediate Linux gateway is deployed to capture these UDP packets and process them. Which architectural and content optimization decisions are critical for successfully ingesting this data into XSIAM?

A. Deploy a dedicated XSIAM Data Collector on the ICS network segment to directly receive the UDP logs, bypassing the Linux gateway, and use advanced XSIAM parsing features to decode the proprietary binary protocol.
B. On the Linux gateway, install a custom UDP listener and a script that extracts the XML fragments, then forwards these raw XML strings to XSIAM via a Syslog Data Collector. The XSIAM Data Flow then uses parse_xml().
C. Configure the Linux gateway with a IJDP listener that stores the raw binary packets as files. The XSIAM Data Collector is then configured to monitor the gateway's file system, and the XSIAM Data Flow attempts to parse the binary content directly using parse_regex() on the raw binary data.
D. Implement a custom service on the Linux gateway to listen for UDP, extract the XML, transform it into a normalized JSON format, and then send it to XSIAM using the XSIAM HTTP Data Collector endpoint. The XSIAM Data Flow then uses parse_json().
E. On the Linux gateway, use a packet capture tool (e.g., Wireshark/tshark) to extract the binary payloads, then develop a custom CIPython program to parse the proprietary header/footer and XML, finally converting it to CEF and pushing it to an XSIAM Syslog Data Collector.

答案：D

解題說明：
Option D represents the most robust and optimized approach. For proprietary binary protocols and network segmentation constraints, an intermediate gateway is necessary. The best practice is to perform the complex, proprietary parsing outside XSIAM, at the source or an intermediate point, and then normalize the data into a well-structured format like JSON or CEF before sending it to XSIAM. Sending JSON via the XSIAM HTTP Data Collector endpoint is generally preferred for its flexibility and native support in XSIAM's Data Flows (parse_json() is highly efficient). This offloads complex binary parsing from XSIAM and ensures XSIAM receives clean, structured data ready for efficient ingestion and analysis. Option A uses syslog for XML which is less ideal than JSON over HTTP. Option B adds an unnecessary conversion to CEF if JSON is a good fit. Option C attempts binary parsing directly in XSIAM which is not designed for proprietary binary decoding. Option E contradicts the network segmentation constraint and XSIAM is not designed to decode arbitrary binary protocols.

問題 #228
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