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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

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

>> Question NSE6_FSM_AN-7.4 Explanations <<

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q93-Q98):

NEW QUESTION # 93
Which two ways are rule tags used on FortiSIEM? (Choose two.)

Answer: B,C

Explanation:
Rule tags help classify and organize rules so analysts can search events or incidents associated with tagged rules. They can also be used to filter playbooks, making it easier to associate the appropriate playbook workflows with specific categories of rule-triggered incidents.


NEW QUESTION # 94
What feature defines when an incident is created by FortiSIEM?

Answer: A


NEW QUESTION # 95
Refer to the exhibit.

Which value would you expect the FortiSIEM parser to use to populate the Application Name field?

Answer: A

Explanation:
The correct answer is C. SSL . FortiSIEM receives raw logs, processes them through parsers, normalizes the extracted fields, classifies the event, and stores the structured data. The Study Guide explains the FortiSIEM process flow: data is collected, processed by the parsing engine, normalized, classified, and then stored. It further states that normalization extracts individual fields from raw events and maps those fields to a common schema. The FortiSIEM 7.4 User Guide describes a parser as a file containing instructions for the parser module to convert a raw log into event attributes. In the exhibit, the raw FortiGate log includes values such as profiletype= " applist " , appcat= " Network.Service " , and app= " SSL " . The field that directly represents the application value is app= " SSL " . Therefore, the parser would use SSL to populate the normalized Application Name field. applist describes the profile type, Network.Service is the application category, and wan1 is the interface, not the application name.


NEW QUESTION # 96
Which analytics search can be used to apply a user and entity behavior analytics (UEBA) tag to an event for a failed login by the user JSmith?

Answer: D

Explanation:
The best matching analytics search is Username CONTAIN smit. The FortiSIEM Analytics lesson explains keyword and attribute matching by using the CONTAIN operator for searching values inside raw logs or attributes. The Study Guide gives a direct example of FortiSIEM translating keyword logic into a condition such as "Raw Event Log CONTAIN TCP." That shows the operator is designed for substring-style matching rather than full-value equality. For a user such as JSmith, the string fragment smit is contained inside the username value, so the condition can match events where the username appears as JSmith, jsmith, or possibly in a longer identity string such as a domain-qualified username.
Option A is wrong because smith is not the complete username and uses an equality-style comparison.
Option B is wrong because it excludes usernames ending in jsmith. Option C uses the wrong operator form for this context. Therefore, the practical FortiSIEM analytics condition that can match the target failed-login event is Username CONTAIN smit.


NEW QUESTION # 97
Which items are used to define a subpattern?

Answer: D

Explanation:
The correct answer is A. Filters, Aggregate, Group By definitions. FortiSIEM rule subpatterns are built from three main configuration areas. The Study Guide states that rule conditions are built from subpatterns of event attribute filters and aggregation functions. It also explains that the single- subpattern rule example in the FortiSIEM GUI demonstrates how "filters, aggregate, and group by" come together to form a subpattern rule. Filters define which events are eligible for matching, such as Event Type, Source IP, Destination IP, or other event attributes. Aggregate defines the threshold or statistical calculation, such as COUNT(Matched Events) > = 3 or an average metric threshold. Group By defines how FortiSIEM partitions matching events into separate evaluation groups, such as by User, Source IP, Destination IP, Host Name, or Reporting Device. Time Window is part of the higher-level rule condition, not one of the three subpattern definition sections. Therefore, the exact components used to define a subpattern are Filters, Aggregate, and Group By.


NEW QUESTION # 98
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