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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Incident Detection, Investigation and Response | 15% | - Applying incident response workflows and escalation - Using dashboards and tools for incident investigation |
| Topic 2: Event Collection and Normalization | 20% | - Collecting logs and data from multiple sources - Normalizing, parsing, and standardizing event data |
| Topic 3: Analytics | 30% | - Applying group by and data aggregation - Building queries from search results and events - Performing CMDB and lookup table queries |
| Topic 4: Event Correlation and Rule Management | 20% | - Managing alerts, tuning rules, reducing false positives - Creating and configuring correlation rules |
| Topic 5: Monitoring, Reporting and Integration | 15% | - Generating compliance and operational reports - Configuring dashboards and real-time monitoring - Integrating with security tools and ZTNA |
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NEW QUESTION # 28
How does FortiSIEM update the incident details if the same rule triggers repeatedly?
Answer: A
Explanation:
When the same rule triggers repeatedly for an existing incident, FortiSIEM updates the Incident Count and refreshes the Last Seen timestamp while maintaining the original incident record.
NEW QUESTION # 29
Refer to the exhibit.
What is the Group: FortiSIEM Analysts value referring to?
Answer: C
Explanation:
The correct answer is C. CMDB user group . In FortiSIEM, users and user groups are maintained as CMDB objects and can be referenced in analytics filters and rule logic. The FortiSIEM 7.4 User Guide table of contents explicitly includes CMDB management for users, viewing user information, adding users, editing or deleting users, performing operations on users, and working with user groups. This confirms that user groups are part of the FortiSIEM CMDB data model. The query shown in the exhibit uses the Analytics filter with the User attribute and the value Group: FortiSIEM Analysts . That syntax indicates that FortiSIEM is referencing a FortiSIEM-defined user group from CMDB, not an LDAP group directly and not an Active Directory group directly. LDAP and Active Directory can be used to discover or authenticate users, but once referenced as a FortiSIEM analytics group value, the object is a CMDB user group. FortiSIEM organization groups are tenant/organization constructs and are not the same as CMDB user groups.
NEW QUESTION # 30
Refer to the exhibit. Why is this search not producing any results?
Answer: C
Explanation:
The query contains a nested query attribute type mismatch because the User attribute is being compared against a Device IP group value. The attribute type and referenced group type must match for the search to return results.
NEW QUESTION # 31
In an automation policy, which two methods can you use to notify analysts when an incident is triggered?
(Choose two.)
Answer: C,D
Explanation:
The correct answers are A. Email and B. FortiSIEM Case. FortiSIEM automation policies can notify or route work to analysts when an incident is triggered. The Study Guide describes the incident notification email workflow and explains that when an incident triggers and an automation policy is defined, FortiSIEM can send a notification email using the default template. It also explains that notification frequency is configured per rule and that repeated incident notifications are controlled by the frequency timer. The FortiSIEM 7.4 User Guide also describes automated case creation through automation policy. It states that an automation policy can use the action Create Case when an incident is created, and that a case management policy can assign FortiSIEM Analyst Teams in an ordered handling sequence. Syslog is not listed as one of the analyst notification methods in the automation policy options shown in this question; FortiSIEM supports SNMP and webhook-style actions, but not
"Syslog" as the listed answer. A pop-up window is not an automation policy notification method.
Therefore, the two correct analyst-notification/routing methods are Email and FortiSIEM Case.
NEW QUESTION # 32
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: C
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 # 33
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