A critical zero-day vulnerability has been disclosed, and the XSIAM team needs to rapidly deploy a new detection rule. Due to the high potential impact, all alerts generated by this rule must immediately be prioritized and assigned the highest possible score, regardless of other contextual factors. Which XSIAM scoring rule configuration element is explicitly designed to achieve this immediate, overriding effect?
Correct Answer: B
Option B is the correct approach. In XSIAM, the 'Set Total Score' action in a scoring rule allows you to explicitly override any previous scoring calculations and set a specific final score. By setting this to the maximum possible score (e.g., 100) and ensuring this scoring rule has a high evaluation 'Order', it guarantees that alerts from the new zero-day rule are immediately prioritized with the highest possible criticality, overriding any other conflicting scoring logic. Options A and C modify scores but don't guarantee an absolute override. Option D only affects the base score from the detection rule, which can still be modified by scoring rules. Option E is impractical and unnecessary.
XSIAM-Engineer Exam Question 32
A large enterprise is implementing XSIAM and has a requirement to detect sophisticated insider threats involving data exfiltration over non-standard ports, correlated with user login activity from unusual geographical locations. The existing XSIAM rule set for data exfiltration is too broad, generating many false positives. Which of the following XSIAM Content Optimization strategies would be most effective in refining these detection rules to meet the specific requirements and reduce false positives, while ensuring high fidelity for actual threats?
Correct Answer: B
Option B is the most effective strategy. It directly addresses the need for correlation by combining disparate event types (network, authentication, data access) to identify a sophisticated threat. Tuning thresholds ensures that the rule is specific enough to reduce false positives while catching true positives. Options A and E are too simplistic and likely to miss threats or generate more false positives. Option C is dangerous as it removes valuable baseline detections. Option D, while IJEBA is powerful, it often benefits from tuned correlation rules for specific, high-priority use cases.
XSIAM-Engineer Exam Question 33
An internal audit identified a gap in detecting privilege escalation attempts using Windows built-in tools like 'seclogon.exe' (RunAs) or psexec.exe' (Sysinternals) when used by non-administrative users. These tools are legitimate but often abused. The goal is to detect Process.Name' 'seclogon.exe' or 'psexec.exe' being invoked from a standard user context, especially when followed by an attempt to execute a sensitive command on another system or elevate privileges locally. Which XQL query would effectively capture this behavior as a BIOC, minimizing false positives from legitimate IT operations?
Correct Answer: B
Option B is the most effective and precise XQL query. Option A is too broad and will generate many false positives from legitimate use of these tools by non-admin users for non-privileged tasks. Option C is too generic for psexec and misses seclogon. Option D is specific but misses other malicious uses. Option E is very broad and will generate many false positives. Option B accurately uses the 'pattern' command to look for the specific sequence: 'seclogon.exe' or 'psexec.exe' being invoked by a non-admin user (stage 1), immediately followed (within 10 seconds, and from the same host/user) by attempts to execute privilege-escalation-related commands (stage 2). The 'where stage_l -Process.Reputation != 'trusted' and stage_2.Process.Reputation != 'trusted'' further refines the detection by excluding known good executables, significantly reducing false positives while catching the intended behavior.
XSIAM-Engineer Exam Question 34
During the planning phase of an XSIAM automation for vulnerability management, the team identifies that new vulnerability scan results from their external scanner are generated daily as XML files. The automation requires these results to be parsed, normalized, and ingested into XSIAM's 'Vulnerabilities' data model. What is the most efficient and scalable approach for this data ingestion, considering XSIAM's capabilities?
Correct Answer: B
XSIAM's 'Parser' and 'Ingestion Pipeline' framework is explicitly designed for efficient and scalable ingestion of various data formats, including custom ones. Developing a custom parser ensures proper field extraction and normalization, while the ingestion pipeline handles the flow from the source (e.g., S3, SFTP, or a custom connector) into XSIAM's data models. Manual uploads are not scalable. Converting to CSV might lose fidelity. A custom Python script is a viable alternative but less integrated and potentially harder to maintain than XSIAM's native ingestion framework. Automatic XML parsing without a custom parser is unlikely to fully normalize complex vulnerability data.
XSIAM-Engineer Exam Question 35
An XSIAM Security Engineer is troubleshooting why certain high-severity alerts, triggered by a custom detection rule, are not consistently enriching with specific asset metadata (e.g., 'asset_owner', 'business_unit') from an external CMDB. The CMDB data is available as a daily CSV export on an SFTP server, and is ingested into a separate Data Lake dataset. The custom detection rule relies on a lookup from the CMDB dataset. The issue appears intermittent. Which factors are most likely contributing to this problem, and what content optimization strategy in XSIAM would be most effective to ensure consistent enrichment?
Correct Answer: A,B,C,E
This is a multiple-response question. All listed options (A, B, C, E) are highly plausible and common reasons for inconsistent lookup enrichment in XSIAM: A: Inconsistent CMDB CSV export: If the source CSV's structure or data types are not stable, the CMDB ingestion Data Flow might partially fail, resulting in an incomplete or corrupted lookup dataset. This directly impacts lookup accuracy. B: Lookup table not 'Live Lookup': For real-time enrichment of active security events, the lookup table derived from CMDB data must be configured as a Live Lookup. If it's a static lookup, it won't reflect recent CMDB updates, leading to stale or missing enrichments for new assets or changes. C: Mismatched Lookup Keys: This is a very common issue. Even minor discrepancies (e.g., '192.168.1.1' vs. '192.168.001.001', or 'hostname' vs. 'HostName') will cause lookup failures. Content optimization here involves ensuring both the CMDB ingestion Data Flow and the security event Data Flow normalize the lookup key format (e.g., to lowercase, remove leading zeros, consistent IP format) before the lookup. E: Intermittent SFTP failure: If the source data for the CMDB dataset (the CSV export) is not reliably ingested due to connectivity issues, the CMDB dataset in XSIAM will become outdated or incomplete, leading to lookup failures. Option D is less likely for lookup performance itself, as XSIAM's lookup capabilities are highly optimized. High volume might impact rule processing overall, but not specifically the lookup mechanism unless the lookup dataset itself is astronomically large and unindexed, which is generally not the case for CMDB data.
