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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

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

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NSE6_FSM_AN-7.4 Exam Objectives & Testking NSE6_FSM_AN-7.4 Exam Questions

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q66-Q71):

NEW QUESTION # 66
Refer to the exhibit.

An analyst is troubleshooting the rule shown in the exhibit. It is not generating any incidents, but the filter parameters are generating events on the Analytics tab.
What is wrong with the rule conditions?

A. The Group By attributes restricts which events are counted.
B. The Destination Host Name value is not fully qualified.
C. The Event Type refers to a CMDB lookup and should be an Event lookup.
D. The Aggregate attribute is too restrictive.

Answer: A

Explanation:
The Group By attributes - Destination IP and User - cause the aggregation (COUNT(Source IP) >= 2) to apply within each unique combination of those groupings. This restricts the count calculation and can prevent the rule from triggering incidents, even if matching events exist in the Analytics tab.

NEW QUESTION # 67
What can you use to send data to FortiSIEM for user and entity behavior analytics (UEBA)?

A. SSH
B. FortiSIEM agent
C. FortiSIEM worker
D. SNMP

Answer: B

Explanation:
The correct answer is A. FortiSIEM agent. The FortiSIEM Study Guide identifies FortiSIEM agents as the component responsible for "file, log monitoring, and UEBA." It also explains that FortiSIEM agents can be installed on endpoints or servers to provide data collection functions that native syslog may not provide. For Windows systems specifically, the guide states that Windows servers do not natively send syslog messages and that a FortiSIEM Windows agent can be installed to perform that function. The FortiSIEM 7.4 User Guide also confirms that FortiInsight UEBA functionality runs as an integrated module within the FortiSIEM Windows Agent in newer releases. SSH and SNMP are access or monitoring protocols; they can support discovery or performance monitoring, but they are not the UEBA data-sending component. A FortiSIEM worker performs analysis and search functions inside the FortiSIEM architecture; it is not installed on endpoints to collect UEBA telemetry. Therefore, the FortiSIEM agent is the correct mechanism for sending UEBA-relevant endpoint data to FortiSIEM.

NEW QUESTION # 68
Which two types of information can FortiSIEM retrieve from FortiClient EMS through an external connection? (Choose two.)

A. Devices with FortiSIEM agents
B. Vulnerability scan events
C. Zero trust network access (ZTNA) tags
D. Device login credentials

Answer: B,C

Explanation:
FortiSIEM can integrate with FortiClient EMS to retrieve vulnerability scan events and ZTNA tag information. These integrations enhance endpoint visibility and support automated security and access-control workflows.

NEW QUESTION # 69
Refer to the exhibit.

The configuration shown in the exhibit is incorrect.
What must you change to allow this configuration to be successfully applied to FortiSIEM?

A. The Train factor must be 70% or greater.
B. The selection in Fields to use for Prediction and Field to Predict must match.
C. Only one AVG type field must be selected under Fields to use for Prediction.
D. Run Mode must be set to ML.

Answer: A

Explanation:
The correct answer is A . In FortiSIEM machine learning training, the Train factor controls how much of the prepared dataset is used for training and how much is reserved for testing. The FortiSIEM 7.4 User Guide states in the regression training procedure that the analyst must choose the Train factor and that it "should be greater than 70%." It also explains the meaning of the value: 70% of the data is used for training and 30% is used for testing. This directly supports option A. Option B is incorrect because the supported running modes include Local, Local Auto, and AWS; "ML" is not the required run mode. Option C is incorrect because regression can use multiple fields for prediction; the guide instructs the user to choose the fields to use for prediction and the field to predict. Option D is incorrect because prediction input fields and target field should not be the same. Regression builds a model to predict a target field based on other fields, so the configuration must use a valid Train factor rather than matching predictor and target fields.

NEW QUESTION # 70
Refer to the exhibits.

You want the rule shown in the exhibit to trigger when three failed login attempts occur within 3 minutes.
Which condition time window and aggregate values are correct for your objective?

A. Time window 180 seconds, aggregate value 2
B. Time window 540 seconds, aggregate value 3
C. Time window 60 seconds, aggregate value 3
D. Time window 180 seconds, aggregate value 3

Answer: A

Explanation:
Three minutes equals 180 seconds. Because the aggregate operator shown is greater than, the matched-event count must be set to 2 so the rule triggers when the count becomes greater than
2, meaning three or more failed login attempts occur within the condition window.

NEW QUESTION # 71
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