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| Section | Objectives |
|---|---|
| Analytics and Search | - Query and Event Analysis
|
| Rules and Incident Management | - Incidents and Notifications
|
| Advanced Analytics and Integrations | - ML, UEBA, and ZTNA
|
| FortiEDR and Security Policy Integration | - FortiEDR Security Configuration
|
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NEW QUESTION # 27
Refer to the exhibit.
Which two conditions will match this rule and subpatterns? (Choose two.)
Answer: B,C
Explanation:
The user initiates an RDP session (Subpattern 1) and then fails to log in multiple times (Subpattern 2 with COUNT(Matched Events) > = 3) - both from the same Source IP and User within 300 seconds.
The brute force attempts typically involve a successful RDP connection followed by multiple failed logins, satisfying the sequence and grouping conditions in the rule.
The correct answers are A and B because the rule uses multiple subpatterns and requires them to occur in a defined relationship within the configured time window. The FortiSIEM Study Guide states that rule conditions specify the event attributes and thresholds that trigger the rule and create an incident. It also explains that the time window is the period "within which the subpattern(s) must match for the rule condition to be satisfied," and that when there is more than one subpattern, FortiSIEM requires logic between the subpatterns plus subpattern relationship constraints. In the exhibit, the first subpattern detects an RDP connection and the second detects failed logons. The rule condition uses a sequence relationship, so the failed logon activity must follow the RDP connection and match the relationship constraints, such as same user and source IP. A user using RDP over SSL VPN who fails repeatedly satisfies this logic. A brute-force attack against an RDP server also satisfies the repeated failed-logon requirement after an RDP connection. Failing only twice does not meet the aggregate threshold, and connecting to the wrong IP is not the failed-logon sequence being detected.
NEW QUESTION # 28
Which information can FortiSIEM retrieve from FortiClient EMS through an API connection?
Answer: B
Explanation:
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.
NEW QUESTION # 29
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?
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 # 30
Refer to the exhibit. If you group these events by the Reporting IP, Event Type, and User attributes, how many results will FortiSIEM display?
Answer: C
Explanation:
All events share the same Reporting IP and Event Type. Grouping by User produces three distinct groups: Mike, Bob, and Alice. Therefore, FortiSIEM displays three results.
NEW QUESTION # 31
Refer to the exhibit. What does the Group: Windows value refer to?
Answer: D
Explanation:
In FortiSIEM, the value Group: Windows refers to a CMDB device group containing devices categorized as Windows systems. It is used to match event attributes such as Source IP against devices in that CMDB group.
NEW QUESTION # 32
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