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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Monitoring, Reporting and Integration | 15% | - Generating compliance and operational reports - Configuring dashboards and real-time monitoring - Integrating with security tools and ZTNA |
| Topic 2: Event Collection and Normalization | 20% | - Collecting logs and data from multiple sources - Normalizing, parsing, and standardizing event data |
| Topic 3: Analytics | 30% | - Applying group by and data aggregation - Performing CMDB and lookup table queries - Building queries from search results and events |
| Topic 4: Event Correlation and Rule Management | 20% | - Creating and configuring correlation rules - Managing alerts, tuning rules, reducing false positives |
| Topic 5: Incident Detection, Investigation and Response | 15% | - Using dashboards and tools for incident investigation - Applying incident response workflows and escalation |
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NEW QUESTION # 71
Refer to the exhibit. Which value will the FortiSIEM parser use to populate the Application Name field?
Answer: C
Explanation:
The raw FortiGate event includes app="SSL", and the parser uses this value to populate the Application Name field.
NEW QUESTION # 72
Refer to the exhibit.
An analyst wants the rule shown in the exhibit to trigger when three failed login attempts occur within three minutes.
What should the values be for the condition time window and aggregate count?
Answer: D
Explanation:
To detect three failed login attempts within three minutes, you must set the aggregate count to 3 in the subpattern and the time window to 180 seconds in the rule condition. This ensures the rule triggers only if three or more failed logins occur in that timeframe.
The correct answer is A because three minutes equals 180 seconds, and the aggregate threshold must be set to three matching events. The FortiSIEM Study Guide explains that rule conditions specify event attributes and thresholds that trigger the rule and create an incident. It further states that the time window defines the period within which the subpattern must match for the rule condition to be satisfied. The Study Guide's single- subpattern rule example shows the same principle: the condition has a configured time window, and the Aggregate section uses a function such as COUNT(Matched Events) to require a minimum number of matching events. In this question, the analyst wants the rule to trigger when three failed login attempts happen within three minutes . Therefore, the rule condition time window must be 180 seconds , and the aggregate count must be 3 . A 90-second window would detect only events inside one and a half minutes, not the required three minutes. An aggregate count of 2 would trigger too early because the requirement is three failed attempts.
NEW QUESTION # 73
You need a model that predicts a target field based on other fields in a dataset and then triggers an anomaly if the value does not match the prediction. Which machine learning (ML) algorithm will you use to build this type of model?
Answer: A
NEW QUESTION # 74
Refer to the exhibit. If a user account is locked after five failed login attempts, how many times will this rule be triggered if three individual users all fail their login 10 times?
Answer: A
Explanation:
The rule groups matching account lockout events by User, along with the reporting device attributes. Each user account produces one account lockout event after the failed-login threshold is reached, so three individual users trigger the rule three times.
NEW QUESTION # 75
Refer to the exhibit. Which section contains settings that determine which attribute associations are used to trigger an incident?
Answer: A
NEW QUESTION # 76
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