Question 81

An XSIAM tenant has a legacy application generating logs in a fixed-width format, where each field occupies a specific character range (e.g., timestamp 1-19, username 20-35, event_id 36-40). The log message itself is a single string. To optimize data ingestion and querying, which Data Flow operation is primarily suited for extracting these fields, and how can they be efficiently assigned appropriate data types?
  • Question 82

    During a rule review, an XSIAM engineer identifies a correlation rule that consistently triggers false positives due to a common, legitimate system process that temporarily matches a suspicious pattern. Simply adding the process name to a global exclusion list is not an option, as the process could still be malicious under different circumstances. How can this specific false positive scenario be mitigated without losing the rule's overall detection capability for actual threats?
  • Question 83

    An application which ingests custom application logs is hosted in an on-premises virtual environment on an Ubuntu server, and it logs locally to a .csv file.
    Which set of actions will allow the ingestion of the .csv logs into Cortex XSIAM directly from the server?
    An application which ingests custom application logs is hosted in an on-premises virtual environment on an Ubuntu server, and it logs locally to a .csv file.
    Which set of actions will allow the ingestion of the .csv logs into Cortex XSIAM directly from the server?
  • Question 84

    A security operations center (SOC) team wants to integrate their existing XDR solution (not XSIAM) with XSIAM to leverage XSIAM's advanced analytics and automation capabilities for threat hunting and incident response. The XDR solution can export security alerts and raw logs in JSON and CEF formats via REST APIs or syslog. Which XSIAM components and integration strategies are best suited for comprehensive data ingestion and automated threat response, considering the need for both structured alerts and unstructured log data?
  • Question 85

    A security engineer is optimizing Broker VM deployment for performance and resilience. The current setup involves a single Broker VM handling a high volume of logs from various sources. To improve fault tolerance and scalability, the engineer plans to deploy an additional Broker VM and distribute log sources between them. What considerations are critical to ensure that log data is not duplicated or lost during this transition, and how can the load be effectively balanced without requiring extensive re-configuration of all log sources?