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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Event Correlation and Rule Management | 20% | - Managing alerts, tuning rules, reducing false positives - Creating and configuring correlation rules |
| Topic 2: Incident Detection, Investigation and Response | 15% | - Using dashboards and tools for incident investigation - Applying incident response workflows and escalation |
| Topic 3: Monitoring, Reporting and Integration | 15% | - Generating compliance and operational reports - Integrating with security tools and ZTNA - Configuring dashboards and real-time monitoring |
| Topic 4: Analytics | 30% | - Performing CMDB and lookup table queries - Applying group by and data aggregation - Building queries from search results and events |
| Topic 5: Event Collection and Normalization | 20% | - Collecting logs and data from multiple sources - Normalizing, parsing, and standardizing event data |
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NEW QUESTION # 89
When using user and entity behavior analytics (UEBA) on FortiSIEM, what must you use to dynamically supply a list of IP addresses to a FortiGate device for blocking purposes?
Answer: D
NEW QUESTION # 90
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?
Answer: B
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 # 91
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 # 92
Refer to the exhibits.
Three events are collected over 10 minutes from two servers: Server A and Server B.
Based on the settings for the rule subpattern and a 10-minute condition window, how many incidents will the servers generate?
Answer: C
Explanation:
The rule triggers when the average CPU utilization (AVG(CPU Util)) exceeds the device's CMDB critical threshold and there are at least two matching events within the 10-minute window.
Server A: Average CPU = (90 + 95) / 2 = 92.5, which is greater than its critical threshold of 90, and it has two events, so one incident is generated.
Server B: Average CPU = (70 + 60) / 2 = 65, which is below its critical threshold of 70, so no incident is generated.
So, Server A generates one incident, and Server B generates none.
NEW QUESTION # 93
Which rule logic should you use to apply a user entity and behavior analytics (UEBA) tag to an event for a failed login incident by the account JSmith?
Answer: B
Explanation:
To apply a UEBA tag to events for a specific failed-login account, the rule logic should match the username field exactly. Using an exact username match ensures the tag is applied only to events associated with the JSmith account.
NEW QUESTION # 94
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