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| Section | Weight | Objectives |
|---|---|---|
| Incident Detection, Investigation and Response | 15% | - Using dashboards and tools for incident investigation - Applying incident response workflows and escalation |
| Analytics | 30% | - Performing CMDB and lookup table queries - Applying group by and data aggregation - Building queries from search results and events |
| Monitoring, Reporting and Integration | 15% | - Configuring dashboards and real-time monitoring - Generating compliance and operational reports - Integrating with security tools and ZTNA |
| Event Correlation and Rule Management | 20% | - Managing alerts, tuning rules, reducing false positives - Creating and configuring correlation rules |
| Event Collection and Normalization | 20% | - Normalizing, parsing, and standardizing event data - Collecting logs and data from multiple sources |
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NEW QUESTION # 47
Refer to the exhibit.
Which value would you expect the FortiSIEM parser to use to populate the Application Name field?
Answer: A
Explanation:
The correct answer is C. SSL . FortiSIEM receives raw logs, processes them through parsers, normalizes the extracted fields, classifies the event, and stores the structured data. The Study Guide explains the FortiSIEM process flow: data is collected, processed by the parsing engine, normalized, classified, and then stored. It further states that normalization extracts individual fields from raw events and maps those fields to a common schema. The FortiSIEM 7.4 User Guide describes a parser as a file containing instructions for the parser module to convert a raw log into event attributes. In the exhibit, the raw FortiGate log includes values such as profiletype= " applist " , appcat= " Network.Service " , and app= " SSL " . The field that directly represents the application value is app= " SSL " . Therefore, the parser would use SSL to populate the normalized Application Name field. applist describes the profile type, Network.Service is the application category, and wan1 is the interface, not the application name.
NEW QUESTION # 48
Refer to the exhibit.
What will happen when a device being analyzed by the machine learning configuration shown in the exhibit has consistently high memory utilization?
Answer: A
Explanation:
The exhibit shows a machine learning Regression configuration. In FortiSIEM regression, selected numerical fields are used as predictors, and another field is selected as the value to predict. The FortiSIEM 7.4 User Guide's Machine Learning section lists Regression separately and describes the training workflow, including selecting fields used by the algorithm. The exhibit shows Memory Utilization, Sent Bytes, and Received Bytes selected under Fields to use for Prediction, while CPU Utilization is selected under Field to Predict. This means Memory Utilization is an input variable used by the model. If memory utilization is consistently high during training or retraining, that higher value becomes part of the learned model pattern. FortiSIEM does not automatically trigger a high-memory incident merely because a regression input value is high; an incident would require inference behavior and an anomaly action or rule configuration. Option C is also wrong because FortiSIEM does not dynamically lower a CPU trigger threshold just because memory is high. The correct behavior is model update based on the higher observed input value.
NEW QUESTION # 49
Refer to the exhibits. Which information will this analytics search display?
Answer: C
Explanation:
The search filters for Event Type values in the Logon Failure group and matches Destination IP addresses against the Device IP values returned from the Server Inventory CMDB report. This displays failed login events involving servers contained in the Server Inventory CMDB report.
NEW QUESTION # 50
Which two data areas can you use for user and entity behavior analytics (EBA) machine learning models?
(Choose two.)
Answer: A,D
Explanation:
The correct answers are A. Process and C. Resources. FortiSIEM UEBA/EBA analytics uses endpoint and behavior-related telemetry to identify abnormal activity. The Study Guide explains that the UEBA incident dashboard shows incidents that the AI module creates based on alerts received from FortiInsight. The UEBA attribute list includes the incident name, host, application, user, tag, and activity. This aligns with process-oriented activity monitoring from endpoint agents. The performance and baseline lessons also explain that FortiSIEM collects performance and availability data from devices and applications, including resource-utilization metrics, and uses that information to build baselines and detect anomalous activity. Resource behavior includes CPU, memory, disk, I/O, and similar utilization patterns, which are valid behavioral-model inputs. Location and Network are important FortiSIEM context areas, but in this question's EBA machine learning model choices, the valid model areas are process behavior and resource behavior. Process reflects what is running or being executed; Resources reflects system or application utilization behavior. Together, these are the two data areas used for EBA machine learning models.
NEW QUESTION # 51
Refer to the exhibit.
A FortiSIEM device is receiving syslog events from a FortiGate firewall. The FortiSIEM analyst is trying to search the raw event logs for the last two hours that contain the keyword " udp " . However, they are getting no results from the search, which they know should be available. Based on the filter shown in the exhibit, why are there no search results?
Answer: C
Explanation:
The operator is set to " = " , which performs an exact match on the entire raw event log, not a substring search. To find logs that contain the keyword " udp " , the analyst should use the CONTAIN operator instead.
This will return all logs where " udp " appears anywhere in the raw log message.
The correct answer is D because the analyst is trying to search for raw logs that contain the keyword udp, but the filter uses the equality operator. The FortiSIEM Study Guide explains keyword searches in terms of Raw Event Log CONTAIN logic. In the keyword phrase search section, the guide states that without quotes, FortiSIEM searches raw event logs by using conditions such as Raw Event Log CONTAIN TCP OR Raw Event Log CONTAIN connection . Another analytics example explains that searching for TCP or UDP events uses the raw event log containing the keyword tcp or udp and that the search returns case-insensitive results for TCP and UDP. This directly eliminates option C. The time range is already set to the last two hours, which is correct for historical raw log searching. The problem is the operator. To find a keyword anywhere inside a raw log message, the analyst should use CONTAIN , not =.
NEW QUESTION # 52
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