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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

SectionObjectives
Analytics and Search- Query and Event Analysis
  • 1. Perform CMDB and lookup table queries
  • 2. Perform nested query lookups
  • 3. Build queries from search results and events
  • 4. Apply group by and data aggregation
Rules and Incident Management- Rules and Alerts
  • 1. Configure FortiSIEM analytics rules
  • 2. Identify various rule components
  • 3. Utilize rule subpatterns, aggregation, group by
- Incidents and Notifications
  • 1. Configure remediation options
  • 2. Manage and tune incidents
  • 3. Configure notification policies
Advanced Analytics and Integrations- ML, UEBA, and ZTNA
  • 1. Describe ZTNA integration in FortiSIEM operations
  • 2. Configure machine learning (ML) settings
  • 3. Integrate UEBA data into rules and dashboards
FortiEDR and Security Policy Integration- FortiEDR Security Configuration
  • 1. Configure playbooks
  • 2. Explain Fortinet Cloud Service (FCS)
  • 3. Configure security policies
  • 4. Configure communication control policy

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q48-Q53):

NEW QUESTION # 48
Refer to the exhibit.

What is the Group: VPN Gateway value a reference to?

Answer: D

Explanation:
In FortiSIEM analytics filters, a value shown as Group: VPN Gateway refers to a CMDB device group. The query uses that CMDB group to match events where the Source IP belongs to devices in the VPN Gateway group.


NEW QUESTION # 49
Refer to the exhibit. You want to use a machine learning (ML) model to train data with the following characteristics shown in the exhibit. Which ML model is the best fit to match the data in the exhibit?

Answer: B

Explanation:
The data points form several distinct groups, so a clustering model is the best fit for identifying natural groupings within the dataset.


NEW QUESTION # 50
Which two data areas can you use for user and entity behavior analytics (UEBA) machine learning models? (Choose two.)

Answer: A,D

Explanation:
FortiSIEM's UEBA models analyze user and entity behavior by correlating data such as location (for detecting unusual logins or access patterns) and network activity (for identifying abnormal communication or traffic behaviors). These data areas enable the system to build baseline profiles and detect anomalies indicating potential insider threats or compromised accounts.


NEW QUESTION # 51
What are the four incident status values on FortiSIEM?

Answer: A

Explanation:
FortiSIEM incidents can have four status values: Active, Auto Cleared, Cleared Manually, and System Cleared. These statuses track the lifecycle of an incident-from detection (Active) to resolution - whether it's cleared automatically by correlation logic or manually by an analyst.


NEW QUESTION # 52
Which information can FortiSIEM retrieve from FortiClient EMS through an API connection?

Answer: B

Explanation:
The correct answer is D. ZTNA tags. FortiSIEM 7.4 includes FortiEMS endpoint tagging integration.
The FortiSIEM 7.4 User Guide states that FortiSIEM supports discovery of FortiEMS servers by using the FortiEMS Management Server API with basic username/password authentication. It also explains that after FortiEMS discovery, FortiSIEM can tag or untag a host by using classification tags on the FortiEMS server. In a ZTNA deployment, those tags are imported by member Fortinet devices, especially FortiGate firewalls, and are referenced in ZTNA firewall rules. The guide gives a common use case in which a host is tagged as suspicious or potentially compromised so firewall rules can isolate it or allow only minimal traffic. Host software versions, FortiSIEM license information, and host login credentials are not the FortiEMS API information relevant to this ZTNA tagging workflow. The API integration supports retrieving FortiEMS-managed host context and using classification/ZTNA tags for automated response and policy enforcement.


NEW QUESTION # 53
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