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| Section | Objectives |
|---|---|
| Topic 1: FortiEDR and Security Policy Integration | - FortiEDR Security Configuration
|
| Topic 2: Rules and Incident Management | - Rules and Alerts
|
| Topic 3: Analytics and Search | - Query and Event Analysis
|
| Topic 4: Advanced Analytics and Integrations | - ML, UEBA, and ZTNA
|
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22. Frage
Which information can FortiSIEM retrieve from FortiClient EMS through an API connection?
Antwort: C
Begründung:
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.
23. Frage
When configuring anomaly detection machine learning, in which step must you select the fields to analyze?
Antwort: B
Begründung:
The correct answer is A. Design. In the FortiSIEM 7.4 User Guide's anomaly detection workflow, the first configuration step is Step 1: Design. In that step, FortiSIEM requires the analyst to identify the fields that will be analyzed by the machine learning job. The guide states that under Design, the analyst must identify Fields to Analyze, and explains that these fields are considered for anomaly detection and must currently be numerical fields. The guide also identifies the time field requirement for statistical deviation algorithms and notes that a FortiSIEM report is used to provide the dataset. The Prepare Data step comes later and is used to load or prepare the data source for training. The Train step runs the algorithm against the prepared dataset. The Schedule step is used after training to run inference.
Therefore, the selection of fields to analyze belongs to the Design phase, not Prepare Data, Train, or Schedule. This sequence matters because FortiSIEM must know which numerical fields are relevant before it can prepare, train, or run inference on the machine learning job.
24. Frage
In an automation policy, which two methods can you use to notify analysts when an incident is triggered?
(Choose two.)
Antwort: B,C
Begründung:
The correct answers are A. Email and B. FortiSIEM Case. FortiSIEM automation policies can notify or route work to analysts when an incident is triggered. The Study Guide describes the incident notification email workflow and explains that when an incident triggers and an automation policy is defined, FortiSIEM can send a notification email using the default template. It also explains that notification frequency is configured per rule and that repeated incident notifications are controlled by the frequency timer. The FortiSIEM 7.4 User Guide also describes automated case creation through automation policy. It states that an automation policy can use the action Create Case when an incident is created, and that a case management policy can assign FortiSIEM Analyst Teams in an ordered handling sequence. Syslog is not listed as one of the analyst notification methods in the automation policy options shown in this question; FortiSIEM supports SNMP and webhook-style actions, but not
"Syslog" as the listed answer. A pop-up window is not an automation policy notification method.
Therefore, the two correct analyst-notification/routing methods are Email and FortiSIEM Case.
25. Frage
Refer to the exhibit. Which section contains settings that determine which attribute associations are used to trigger an incident?
Antwort: C
26. Frage
Refer to the exhibits.
You are troubleshooting why the rule shown in the exhibit is generating incidents for successful Remote Desktop Protocol (RDP) connections with correct logins. It should only be triggering when a person fails to log in three or more times to the target device when connecting with RDP.
What is causing the rule to be triggered by correct login events? (Choose one answer)
Antwort: D
Begründung:
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.
27. Frage
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