Fortinet NSE6_FSM_AN-7.4 Dumps

The rule is triggering on successful RDP connection events because the Next operator between the two subpatterns is set to OR . The FortiSIEM Study Guide explains that multiple subpattern rules are used when patterns must occur within a specific time period or when one of several patterns proves that an incident condition exists. It lists the OR operator as: “Subpattern X OR Subpattern Y occurred within the Time Window.” The same Study Guide further explains that if multiple patterns are used, FortiSIEM requires a next operator, and in the OR example, “an event that matches either” subpattern will trigger. It also states that because the next operator is OR, the constraint between the two subpatterns is not enforced.

In the exhibit, Subpattern 1 matches RDP traffic on TCP/UDP port 3389 from FortiGate traffic-forward events, while Subpattern 2 matches logon failure events with COUNT(Matched Events) > = 3. Because the rule uses OR, FortiSIEM can trigger when only the RDP connection subpattern matches, even if the failed-logon subpattern does not match. The correct logic should require both subpatterns to match with the intended relationship constraints, not either subpattern independently.

The correct answers are D. Run Remediation/Script and E. Run Playbook on Incident Trigger . FortiSIEM can block an IP address on a FortiGate through a remediation script or through a FortiSOAR playbook/connector workflow. The FortiSIEM Analyst Study Guide explains that for automatic remediation, you define a remediation script for a scenario, and that mitigation scripts can “block an IP address in a firewall” or disable a user in Active Directory. It also states that, when an automation policy is triggered and the remediation script option is enabled, FortiSIEM uses incident data and runs the script to quarantine or block the offending IP address on FortiGate.

FortiSIEM 7.4 also supports automatic playbook execution from an automation policy. The 7.4 User Guide states that under Admin > Settings > Automation Policy , you can choose Run Playbook on Incident Trigger and select a playbook. The same guide explains that FortiSOAR playbooks can call connectors, and the Fortinet FortiOS connector can perform actions such as Block IP Address on a FortiGate firewall.

Email, Remedy tickets, and generic integration policies are notification/ticketing workflows, not the direct FortiGate IP-block actions.

The attribute must be selected as a Triggered Attribute so that it becomes available for incident generation and incident-title substitution. In the FortiSIEM Study Guide’s rule action configuration section, FortiSIEM separates incident attributes from triggered attributes. Triggered attributes are taken from the events that cause the rule to trigger and are then available for incident display and incident context. The guide explains that the rule action step is where an analyst defines the incident generated by a rule and chooses which attributes are carried forward. If Destination Host Name is not selected in the Triggered Attributes list, FortiSIEM cannot use it as an incident attribute in the generated incident title. Option B is wrong because aggregate items are used for calculations such as COUNT, AVG, or SUM, not for making a text attribute available in the incident title. Option C is wrong because Destination Host Name is an event attribute, not an event type. Option D is unrelated; removing Destination IP would not make Destination Host Name selectable.

The automation policy is configured to run a remediation script named " Fortinet FortiOS - Block Source IP FortiOS via API " . It specifies enforcement on two FortiGate devices: FortiGate508 and FortiGate90D. Therefore, associated source IP addresses will be blocked on those two FortiGate firewalls only.

The correct answer is D because the remediation configuration defines specific enforcement targets. The FortiSIEM Study Guide explains that automation policies can run remediation scripts automatically when an incident occurs. It also explains the remediation options: Enforce On determines which devices the script runs against, while Run On identifies whether the script is launched from the supervisor or a collector. The Study Guide further states that mitigation scripts can block an IP address in a firewall or disable a user in Active Directory, and recommends specifying the Enforce On value because it controls the target device used by the remediation script. In the exhibit, the selected script is a Fortinet FortiOS block-source-IP remediation script, and the Enforce On field lists two FortiGate devices. That means the block action is targeted only at those two named FortiGate firewalls. The Aviation organization limits the automation policy context, but it does not mean every device in the organization receives the block. It is also not all FortiGate firewalls or the whole Network CMDB group.

Grouping by User, Source IP, and Count means that each unique combination of those three attributes will be treated as a separate result. In the table, all six rows have distinct combinations of User, Source IP, and Count - so FortiSIEM will display 6 results.

Six because grouping by User , Source IP , and Count creates a separate result for every unique combination of those three selected attributes. The FortiSIEM Study Guide explains this grouping behavior in the single-subpattern rule example: “If multiple VPN login failure events have the same source IP address, reporting device, reporting IP address, and user, they are grouped together in one row, and the count column tracks the number of events for each of those rows.” Applying that rule here, FortiSIEM compares all selected Group By fields together. In the exhibit, every row has a unique Source IP address, even where the same user appears more than once. For example, Mike appears twice, but the Source IP and Count values are different. Alice appears twice with Count 2, but the Source IP values are different. Bob appears twice, but both Source IP and Count are different. Since no row has the same User, Source IP, and Count combination as another row, FortiSIEM displays all six rows.

The fields are highlighted in red because unique values such as Event Receive Time and Raw Event Log cannot be used in group-by operations. Grouping requires aggregatable or consistent values across events, while these fields are unique to each event, making them incompatible for grouping.

The correct answer is A because the highlighted fields are not valid for that grouped/aggregated display configuration. The FortiSIEM 7.4 User Guide notes that some event attributes, functions, and queries are not supported in specific analytics result-filter and display contexts. It lists date fields, including examples such as Event Receive Time , and also lists Raw Event Log and Binary Raw Event Log among unsupported fields for that context. The reason is practical: grouping requires stable values that can combine multiple events into meaningful grouped rows. Attributes such as Event Receive Time and Raw Event Log are highly specific to individual events. If every event has its own receive timestamp or unique raw log content, grouping by those fields defeats aggregation and can create one row per event rather than meaningful grouped output. COUNT(Matched Events) itself is a valid aggregate expression when used correctly. Event Receive Time is available in logs, but it is not appropriate as a grouped field in the configuration shown. Therefore, the red highlighting indicates invalid grouped fields caused by unique/non-groupable values.

The correct answer is B because the configuration groups results by Source IP and Destination IP , while using COUNT(Matched Events) as a display/aggregate value. FortiSIEM’s grouping logic combines events only when the selected Group By attributes match. The Study Guide explains that Group By attributes determine how matching events are placed into rows, and that when multiple events share the same grouped values, “they are grouped together in one row.” The count column then tracks the number of events represented by that row. In the exhibit, Source IP and Destination IP are the grouping fields, so FortiSIEM displays each unique connection pair once. The count shows how many matching allowed firewall connection events were seen for each pair. Option A is not correct because the exhibit does not show sorting by destination IP hit count. Option C ignores the source and destination grouping. Option D would require grouping by source IP alone or by distinct destination counts per source, which is not the shown configuration.

The correct answer is Local Auto. The uploaded answer was right, but its explanation was sloppy because it incorrectly described Local mode as the most time-consuming mode. In FortiSIEM machine learning, Local Auto mode selects the best algorithm by evaluating multiple candidate algorithms. The User Guide states that in Local Auto mode, “FortiSIEM picks the best algorithm” and that the Max Run Time parameter limits how long the job can run; longer runtime can produce better results. That is why Local Auto can take the most time. Forecasting and Regression are task types, not run modes.

The correct answers are A. Process and C. Resources. FortiSIEM UEBA/EBA analytics uses endpoint and behavior-related telemetry to identify abnormal activity. The Study Guide explains that the UEBA incident dashboard shows incidents that the AI module creates based on alerts received from FortiInsight. The UEBA attribute list includes the incident name, host, application, user, tag, and activity. This aligns with process-oriented activity monitoring from endpoint agents. The performance and baseline lessons also explain that FortiSIEM collects performance and availability data from devices and applications, including resource-utilization metrics, and uses that information to build baselines and detect anomalous activity. Resource behavior includes CPU, memory, disk, I/O, and similar utilization patterns, which are valid behavioral-model inputs. Location and Network are important FortiSIEM context areas, but in this question’s EBA machine learning model choices, the valid model areas are process behavior and resource behavior. Process reflects what is running or being executed; Resources reflects system or application utilization behavior. Together, these are the two data areas used for EBA machine learning models.

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.

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.

The correct answer is D. The exhibit shows an outer event query using the Event Attribute filter Source IP NOT IN Device IP: Approved Devices. The outer query time range is set to Relative — Last 10 Minutes, so FortiSIEM searches only the event data from the last 10 minutes. The exhibit also shows a separate Nested Time Range set to Relative — Last 30 Days. In FortiSIEM nested searches, the nested time range applies to the inner report/subquery, not to the outer event search. The FortiSIEM 7.4 User Guide states that nested query functionality lets one query refer to results from another query, and for outer event / inner event nested searches, it instructs the user to “choose the time range for outer query” and separately “choose Nested Time Range for the inner query.” It also states that when an existing query is used as an inner query, “time range would be set separately” in the outer query configuration. Therefore, FortiSIEM searches the last 10 minutes of outer events and compares their Source IP values against the Device IP values returned by the Approved Devices report using the last 30 days nested time range.

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.

The FortiSIEM Study Guide defines a nested query as a query that has another query embedded within it, where the embedded query is known as the subquery. The FortiSIEM 7.4 User Guide lists the supported nested search scenarios: Outer CMDB Query, Inner Event Query ; Outer Event Query, Inner Event Query ; and Outer Event Query, Inner CMDB Query . These supported combinations prove that the inner or subquery can be either an Event Query or a CMDB Query. LDAP Query and SNMP Query are not listed as supported nested analytics subquery types. LDAP may be used for user discovery or authentication, and SNMP may be used for monitoring or discovery, but neither is referenced as a nested analytics query type. The User Guide also explains that the outer query uses Select from Report to reference the saved inner query and that the matching attribute data types must align between the outer query and the selected display column in the inner query.