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NEW QUESTION # 89
Refer to the exhibit.
You notice that the custom event handler you configured to detect SMTP reconnaissance activities is creating a large number of events. This is overwhelming your notification system.
How can you fix this?
Answer: C
Explanation:
* Understanding the Issue:
* The custom event handler for detecting SMTP reconnaissance activities is generating a large number of events.
* This high volume of events is overwhelming the notification system, leading to potential alert fatigue and inefficiency in incident response.
* Event Handler Configuration:
* Event handlers are configured to trigger alerts based on specific criteria.
* The frequency and volume of these alerts can be controlled by adjusting the trigger conditions.
* Possible Solutions:
* A. Increase the trigger count so that it identifies and reduces the count triggered by a particular group:
* By increasing the trigger count, you ensure that the event handler only generates alerts after a higher threshold of activity is detected.
* This reduces the number of events generated and helps prevent overwhelming the notification system.
* Selected as it effectively manages the volume of generated events.
* B. Disable the custom event handler because it is not working as expected:
* Disabling the event handler is not a practical solution as it would completely stop monitoring for SMTP reconnaissance activities.
* Not selected as it does not address the issue of fine-tuning the event generation.
* C. Decrease the time range that the custom event handler covers during the attack:
* Reducing the time range might help in some cases, but it could also lead to missing important activities if the attack spans a longer period.
* Not selected as it could lead to underreporting of significant events.
* D. Increase the log field value so that it looks for more unique field values when it creates the event:
* Adjusting the log field value might refine the event criteria, but it does not directly control the volume of alerts.
* Not selected as it is not the most effective way to manage event volume.
* Implementation Steps:
* Step 1: Access the event handler configuration in FortiAnalyzer.
* Step 2: Locate the trigger count setting within the custom event handler for SMTP reconnaissance.
* Step 3: Increase the trigger count to a higher value that balances alert sensitivity and volume.
* Step 4: Save the configuration and monitor the event generation to ensure it aligns with expected levels.
* Conclusion:
* By increasing the trigger count, you can effectively reduce the number of events generated by the custom event handler, preventing the notification system from being overwhelmed.
Fortinet Documentation on Event Handlers and Configuration FortiAnalyzer Administration Guide Best Practices for Event Management Fortinet Knowledge Base By increasing the trigger count in the custom event handler, you can manage the volume of generated events and prevent the notification system from being overwhelmed.
NEW QUESTION # 90
You want to use the queue and shift management feature to automatically assign newly created low-priority tasks to members of the L1 queue. However, you are unable to add the Tasks module to the Module Types list. What is the problem? Choose one answer.
Answer: B
Explanation:
Exact Extract: "The first step in creating a queue occurs on the Queue Definition page, where you define a name and description, and specify the modules that you want to associate with the queue... Note that for the module to be selectable under Module Types, you must enable the Queueable setting under Application Editor
> Modules."
The correct answer is A because FortiSOAR only allows a module to appear in the queue Module Types list when that module has the Queueable setting enabled under Application Editor > Modules . The issue is not the task priority or queue priority. A higher priority queue only affects tie-breaking when multiple queues match the same record criteria; it does not prevent a module from being selected. The Tasks module can be used as a FortiSOAR record module, so C is not the best answer. Shift-based assignment is also separate: it controls whether assignment follows shift availability after the queue exists, but it does not control whether the module appears in the Module Types list.
Technical Deep Dive: Queue and shift management is metadata-driven. First, the module must be queue-enabled. Then queue rules can match records, such as newly created low- priority tasks. After that, user assignment logic can assign records to the queue lead, leave them unassigned, or distribute them by round robin, optionally using shift-based availability. So the first fix is: Application Editor > Modules > Tasks > enable Queueable.
NEW QUESTION # 91
Refer to the exhibit.
What is the correct Jinja expression to filter the results to show only the MD5 hash values?
{{ [slot 1]|[slot 2] [slot 3].[slot 4] }}
Select the jinja expression in the left column, hold and drag it to a blank position on the right. Place the four correct steps in order, placing the first step in the first slot. Once you place an expression, you can move it again if you want to change your answer before moving to the next question. You need to drop four jinja expressions in the work area.
Select and drag the screen divider to change the viewable area of the source and work areas.
Answer:
Explanation:
Explanation:
Slot 1: vars.artifacts
Slot 2: json_query
Slot 3: ( " data.results[?type== ' FileHash-MD5 ' ]
Slot 4: value
Exact Extract: "You can assign specific fields from your connector action output to their own variables and further manipulate the data using Jinja filters. This approach allows you to efficiently extract, clean, and prepare information for use in later steps of your automation." Exact Extract: The guide shows the same Jinja pattern:
{{ vars.steps.Advanced_Search_Query.data.events | json_query( ' [].attributes.srcIpAddr ' ) | unique }} and explains that similar Jinja logic applies to extracting other variables from structured output.
The correct expression is {{ vars.artifacts | json_query( " data.results[?type== ' FileHash-MD5 ' ].value " ) }} because the JSON object stores artifact records under vars.artifacts.data.results. Each object in results has a type and a value. The filter condition [?type== ' FileHash-MD5 ' ] selects only records whose type is FileHash-MD5 , and .value returns only the MD5 hash strings, not the full objects.
tojson is unnecessary because the data is already structured and queryable. results, data, and value alone are incomplete because they do not filter by artifact type. The key operation is json_query , which uses a JMESPath-style expression to filter a list and project only the required field.
Technical Deep Dive: This is a classic FortiSOAR playbook parsing pattern. Use json_query when the object is already JSON-like and you know the path. The expression returns a list such as:
[ " 6aad63bcc3dd4e148f3724808955f912 " , " 9fd2b1c0e4a37658bca9d0f1e2c34567 " ] This is automation-layer data extraction. FortiGate NP/CP offloading is irrelevant because no packet inspection or firewall data-plane forwarding is involved.
NEW QUESTION # 92
You need to create a nested query in FortiSIEM that satisfies the following conditions:
* Find all devices discovered by any FortiSIEM Windows Agent.
* From those devices, identify those that have generated Windows Login Failure events.
Which two query components should be used for this nested query? Choose two answers.
Answer: C,D
Explanation:
Exact Extract: "The example on this slide shows a structured search that references the CMDB...
Attribute: Reporting IP Operator: IN Value: Devices: Windows... Attribute: Event Type Operator: IN Value: EventTypes: Logon Failure." Exact Extract: "FortiSIEM agents: File, log monitoring, and UEBA." The guide also explains that Windows systems can use the FortiSIEM Windows agent for log forwarding and monitoring.
The correct answers are A and C. The first requirement is CMDB-based: identify devices discovered by a FortiSIEM Windows Agent. That belongs in an inner CMDB query because it produces the device set. The second requirement is event-based: from that device set, find devices that generated Windows Login Failure events. That belongs in the outer Event Query, where the event condition can reference the device results from the inner CMDB query.
Technical Deep Dive: The clean nested-query logic is: inner query defines the population of relevant assets; outer query tests whether that population has produced the target events. FortiSIEM commonly uses CMDB-backed device groups with event filters such as Event Type IN EventTypes: Logon Failure.
This avoids manually maintaining long IP lists and keeps detection tied to live inventory.
NEW QUESTION # 93
Refer to the exhibit.
What are the two mistakes in the incident subpattern rule configuration? Choose two answers.
Answer: B,D
Explanation:
Exact Extract: "Rule subpatterns consist of a filter, aggregate, and group by condition. In the Filters section, you must specify the criteria for determining which event attributes and values the rule monitors... Next, in the Aggregate section, you must define the number of event matches required for the rule to trigger. Finally, in the Group By section, you must define which event attributes will be used to group the events before the group constraints are applied." Exact Extract: "FortiSIEM always sets the Aggregate condition to COUNT(Matched Events) > = 1." The two mistakes are B and D . In the exhibit, the aggregate condition is configured as COUNT(Matched Events) < 1 , which is logically wrong for an incident rule that should trigger when a matching event occurs.
It should be COUNT(Matched Events) > = 1 or another positive threshold, depending on the detection objective. The second problem is that the filter uses Windows Event Category = Win-Security-517 instead of defining the mandatory Event Type condition. FortiSIEM rules should match the normalized event type, such as Event Type = Win-Security-517 , because Event Type identifies the parsed event FortiSIEM is correlating. The Group By fields-Reporting IP, Computer, and Service Name-do not conflict; they define how matching events are grouped. The time window is normally configured at the rule condition level, not necessarily inside this subpattern edit view, so A is not the best answer.
Technical Deep Dive: FortiSIEM correlation logic works in three layers: the Filter selects candidate events, the Aggregate decides whether enough matching events exist, and Group By controls per-entity correlation. Here, using < 1 means the rule is effectively looking for zero matching events, which is not how a Windows service-event detection should be triggered. Also, Windows Event Category is not the normalized FortiSIEM event identity; Event Type is the key normalized field used for rule accuracy.
This is SIEM correlation logic only; FortiGate NP/CP offloading is irrelevant because no packet- forwarding or ASIC inspection path is involved.
NEW QUESTION # 94
......
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