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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

Section	Objectives
Topic 1: Machine Learning, UEBA, and ZTNA	- Advanced analytics integration 1. Describe ZTNA integration in FortiSIEM operations 2. Integrate UEBA data into rules and dashboards 3. Configure ML configuration tasks
Topic 2: Analytics	- Query and event analysis 1. Apply group by and data aggregation on search results 2. Perform CMDB and lookup table queries 3. Perform nested query lookups 4. Build queries from search results and events
Topic 3: FortiEDR Security Settings and Policies	- Security configuration 1. Configure security policies 2. Configure playbooks 3. Explain Fortinet Cloud Service (FCS) 4. Configure communication control policy
Topic 4: Rules and Subpatterns	- Analytics rules configuration 1. Configure FortiSIEM analytics rules 2. Use rule subpatterns, aggregation, and group by 3. Identify rule components
Topic 5: Incidents, Notifications, and Remediation	- Incident management 1. Manage and tune incidents 2. Configure remediation options 3. Configure notification policies

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q85-Q90):

NEW QUESTION # 85
What must match when referencing an inner query from an outer query?

A. Both must be CMDB lookups.
B. Both must be event queries.
C. Both must reference IP addresses.
D. Both must have the same data type.

Answer: D

Explanation:
When creating an inner query in FortiSIEM, the referenced attribute in the outer and inner queries must share the same data type (for example, IP address, string, or integer). This ensures the system can properly correlate and filter results between the two queries during execution.

NEW QUESTION # 86
How does FortiSIEM update the incident table if a performance rule triggers repeatedly?

A. FortiSIEM generates a new incident based on the Rule Frequency value, and updates the First Seen and Last Seen timestamps.
B. FortiSIEM generates a new incident each time the rule triggers, and updates the First Seen and Last Seen timestamps.
C. FortiSIEM updates the Incident Count value and Last Seen timestamp.
D. FortiSIEM changes the incident status to Repeated, and updates the Last Seen timestamp.

Answer: C

Explanation:
The correct answer is B. FortiSIEM does not create a separate incident every time the same rule condition repeats. The FortiSIEM Study Guide explains that rules process events based on time periods, and if the same rule with the same incident conditions triggers repeatedly, FortiSIEM increases the count instead of creating a new incident. The incident list view includes the incident Count field for this purpose. The guide further explains that when an incident triggers for the first time, FortiSIEM sets First Occurred and Last Occurred to the same value. When the incident triggers again within the rule evaluation period, FortiSIEM increases the count and updates Last Occurred, while the triggered Events view displays the latest event data. This behavior prevents duplicate incident flooding while preserving evidence that the condition is recurring. Option A is incorrect because FortiSIEM does not use a "Repeated" incident status. Option C and D are incorrect because FortiSIEM does not generate a new incident for every repeated trigger when the incident conditions match an already active incident.

NEW QUESTION # 87
Refer to the exhibit.

What is the Group: FortiSIEM Analysts value referring to?

A. CMDB user group
B. Windows Active Directory user group
C. FortiSIEM organization group
D. LDAP user group

Answer: A

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 # 88
Refer to the exhibit. Why would the two entries shown in the exhibit be included in an incident action history?

A. An administrator has enabled the Notify on Incident Cleared option.
B. The system cleared the incident and is configured to Send Email/SMS/Webhook to the target users.
C. Multiple new incidents have occurred and have triggered the rule threshold.
D. An analyst resolved and cleared the incident and the Do not notify when an incident is cleared by system option is not enabled in the automation policy.

Answer: B

Explanation:
The action history shows that the system cleared the incident and then sent an email notification.
This occurs when the automation policy is configured to send an Email/SMS/Webhook notification to the target users when the incident is cleared by the system.

NEW QUESTION # 89
When configuring anomaly detection machine learning, in which step must you select the fields to analyze?

A. Prepare Data
B. Design
C. Train
D. Schedule

Answer: B

Explanation:
The correct answer is A. Design. In the FortiSIEM 7.4 User Guide's anomaly detection workflow, the first configuration step is Step 1: Design. In that step, FortiSIEM requires the analyst to identify the fields that will be analyzed by the machine learning job. The guide states that under Design, the analyst must identify Fields to Analyze, and explains that these fields are considered for anomaly detection and must currently be numerical fields. The guide also identifies the time field requirement for statistical deviation algorithms and notes that a FortiSIEM report is used to provide the dataset. The Prepare Data step comes later and is used to load or prepare the data source for training. The Train step runs the algorithm against the prepared dataset. The Schedule step is used after training to run inference.
Therefore, the selection of fields to analyze belongs to the Design phase, not Prepare Data, Train, or Schedule. This sequence matters because FortiSIEM must know which numerical fields are relevant before it can prepare, train, or run inference on the machine learning job.

NEW QUESTION # 90
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