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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

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

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q11-Q16):

NEW QUESTION # 11
What are the four incident status values on FortiSIEM?

A. Active, closed, cleared, resolved
B. Active, auto closed, cleared manually, resolved
C. Active, cleared, cleared manually, false positive
D. Active, auto cleared, cleared manually, system cleared

Answer: D

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 # 12
Refer to the exhibit.

How was this incident cleared?

A. The analyst manually cleared the incident from the incident table.
B. The endpoint was rebooted and sent an all-clear signal to FortiSIEM.
C. The incident was cleared automatically by the rule.
D. FortiSIEM cleared the incident automatically after 24 hours.

Answer: C

Explanation:
The Incident Status shows " Auto Cleared " , and the Cleared Reason states: " Rule has not been triggered for
20 minutes. " This indicates that the incident was automatically cleared by the rule logic after a defined period of inactivity.
The correct answer is C because the exhibit shows the incident status as Auto Cleared and the cleared reason indicates that the rule condition was no longer being triggered. The Study Guide explains that FortiSIEM supports clear conditions and auto-clearing behavior at the rule level. It states that if a time-based clear condition is configured, FortiSIEM can auto-clear the incident after the last occurrence if the trigger condition no longer exists. It also explains pattern-based clear behavior: FortiSIEM evaluates clear-condition subpatterns and compares attributes from the clear condition with the original incident attributes. If the configured attributes match, the incident status is set to auto cleared. In the exhibit, the cleared reason says the rule has not been triggered for a defined number of minutes. That is not a manual action by the analyst and not an endpoint-generated all-clear signal. It is FortiSIEM's rule-based clearing logic. Option B is also wrong because the exhibit shows a specific rule inactivity period, not a generic 24-hour timeout.

NEW QUESTION # 13
You need to model for predicting a target based on other fields in the dataset and then trigger an anomaly if the value does not match the prediction.
Which machine learning algorithm will build this type of model?

A. Forecasting
B. Classification
C. Regression
D. Clustering

Answer: C

Explanation:
The correct answer is C. Regression. Regression is the machine learning task used when a model predicts a target value based on other fields in a dataset. In FortiSIEM's machine learning workflow, regression configuration includes selecting Fields to use for Prediction and a Field to Predict. The User Guide explains that during regression training, the analyst chooses the fields used for prediction and the field being predicted, then trains the model with a Train factor. This matches the question exactly:
the model predicts a target based on other fields, and the inference phase can identify anomalies when observed values differ significantly from predicted values. Classification is used to assign records to discrete classes or categories, not to predict a continuous target metric from other variables. Clustering groups similar observations without a predefined target field. Forecasting predicts future values over time, normally based on time-series behavior. Because the question specifically describes predicting a target field from other dataset fields and detecting mismatch from the prediction, the correct machine learning method is Regression.

NEW QUESTION # 14
How can you use the configuration management database (CMDB) in an analytics search?

A. Use devices defined in the CMDB as source IP addresses.
B. Use device IP addresses defined in the CMDB to perform an nmap analytics scan.
C. Perform an AI-assisted analytics search using devices defined in the CMDB.
D. Match passwords defined in the CMDB to look for suspicious logins.

Answer: A

Explanation:
In an analytics search, FortiSIEM can use devices stored in the CMDB as searchable entities, such as source IP addresses. This allows searches and rule logic to reference known assets from the CMDB instead of relying only on manually entered IP values.

NEW QUESTION # 15
A rule that detects network connections to an SSH server is triggering constantly in response to background internet traffic and must be tuned. Which method is used to tune this rule and solve the issue?

A. Block connections from unauthorized networks before they reach the server.
B. Increase the time window on the FortiSIEM rule.
C. Increase the COUNT (Matched Events)value in the subpattern.
D. Update the Group By attribute to include only allowed host IP addresses.

Answer: C

Explanation:
Increasing the matched-event count threshold tunes the rule so that a single or low-volume background connection does not immediately create an incident. The rule will trigger only when the number of SSH connection events reaches the defined threshold within the rule's evaluation window.

NEW QUESTION # 16
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