Fortinet Fortinet NSE 7 - Security Operations 7.6 Architect NSE7_SOC_AR-7.6 Exam Dumps: Updated Questions & Answers (January 2026)

Comprehensive and Detailed Explanation From FortiSOAR 7.6., FortiSIEM 7.3 Exact Extract study guide:

InFortiSOAR 7.6, theWar Roomis a collaborative space designed for high-priority incident investigation. TheEvidencestab within theInvestigateview (as shown in the exhibit) is specifically designed to highlight critical findings found during the investigation process.

Evidence Tagging:To populate theAction Logs Marked As Evidencesection, an analyst must specifically tag a relevant log entry, a playbook output, or a comment within the collaboration workspace with the system-defined keyword"Evidence".

Automatic Categorization:Once the tag is applied, FortiSOAR automatically parses these entries and displays them in this centralized view. This allows team members and stakeholders to quickly view substantiated facts and proof gathered during the "Root Cause Analysis" phase without sifting through all raw action logs.

Manual vs. Action Logs:The exhibit shows two distinct areas: "Manually Upload Evidences" (where files like the CSLAB document shown can be dragged and dropped) and "Action Logs Marked As Evidence." The latter is reserved exclusively for system-generated logs or comments that have been promoted to evidence status via tagging.

Why other options are incorrect:

By linking an indicator to the war room (B):Linking indicators associates technical artifacts (like IPs or hashes) with the record, but it does not automatically classify them as evidence within the War Room action log view.

By creating an evidence collection task and attaching a file (C):While this is a valid step in an investigation, attaching a file to a task typically places it in the "Attachments" or "Manually Upload Evidences" area, rather than the "Action Logs" section specifically.

By executing a playbook with the Save Execution Logs option enabled (D):Saving execution logs ensures a trail of what the playbook did, but it does not mark the output as "Evidence" unless the specific logic or a manual analyst action applies the "Evidence" tag to the resulting log entry.

Understanding the Custom Event Handler Configuration:

The event handler is set up to generate events based on specific log data.

The goal is to generate events specifically for spam emails detected by FortiMail.

Analyzing the Issue:

The event handler is currently generating events for both spam emails and clean emails.

This indicates that the rule's filtering criteria are not correctly distinguishing between spam and non-spam emails.

Evaluating the Options:

Option A:Selecting the "Anti-Spam Log (spam)" in the Log Type field will ensure that only logs related to spam emails are considered. This is the most straightforward and accurate way to filter for spam emails.

Option B:Typing type==spam in the Log filter by Text field might help filter the logs, but it is not as direct and reliable as selecting the correct log type.

Option C:Disabling the rule to use the filter in the data selector to create the event does not address the issue of filtering for spam logs specifically.

Option D:Selecting "Within a group, the log field Spam Name (snane) has 2 or more unique values" is not directly relevant to filtering spam logs and could lead to incorrect filtering criteria.

Conclusion:

The correct change to make in the rule is to select "Anti-Spam Log (spam)" in the Log Type field. This ensures that the event handler only generates events for spam emails.

Comprehensive and Detailed Explanation From FortiSOAR 7.6., FortiSIEM 7.3 Exact Extract study guide:

InFortiSOAR 7.6, the playbook engine utilizes Jinja2 expressions to handle dynamic data. When a playbook is configured with aManual Trigger, the administrator can define input fields (such as text, picklists, or checkboxes) that an analyst must fill out when executing the playbook from a record.

Input Parameter Mapping:Any data entered by the user during this manual trigger phase is automatically mapped to the input.params dictionary within the vars object. Therefore, the syntax to retrieve a specific input value is {{ vars.input.params.variable_name }}.

Scope of Variables:This specific path ensures that the variable is pulled from the initial user input rather than from the output of a subsequent step (vars.steps) or a globally defined variable (globalVars).

Understanding Automation Processes in FortiAnalyzer:

FortiAnalyzer can automate responses to detected security events, such as running commands on FortiGate devices.

Analyzing the Customer Requirement:

The customer wants to run a CLI command on FortiGate to block predefined URLs when a botnet C&C server IP is detected.

This requires an automated response triggered by a specific event.

Evaluating the Options:

Option A:Playbooks orchestrate complex workflows but are not typically used for direct event-triggered automation processes.

Option B:Data selectors filter logs based on criteria but do not initiate automation processes.

Option C:Event handlers can be configured to detect specific events (such as detecting a botnet C&C server IP) and trigger automation stitches to execute predefined actions.

Option D:Connectors facilitate communication between FortiAnalyzer and other systems but are not the primary mechanism for initiating automation based on log events.

Conclusion:

To start the automation process when a botnet C&C server IP is detected, you must use anEvent handlerin FortiAnalyzer.

Understanding Playbook Variables:

Playbook tasks in Security Operations Center (SOC) playbooks use variables to pass and manipulate data between different steps in the automation process.

Variables help in dynamically handling data, making the playbook more flexible and adaptive to different scenarios.

Types of Variables:

Input Variables:

Input variables are used to provide data to a playbook task. These variables can be set manually or derived from previous tasks.

They act as parameters that the task will use to perform its operations.

Output Variables:

Output variables store the result of a playbook task. These variables can then be used as inputs for subsequent tasks.

They capture the outcome of the task's execution, allowing for the dynamic flow of information through the playbook.

Other Options:

Create:Not typically referred to as a type of variable in playbook tasks. It might refer to an action but not a variable type.

Trigger:Refers to the initiation mechanism of the playbook or task (e.g., an event trigger), not a type of variable.

Conclusion:

The two types of variables used in playbook tasks areinputandoutput.

Comprehensive and Detailed Explanation From FortiSOAR 7.6., FortiSIEM 7.3 Exact Extract study guide:

InFortiSOAR 7.6, step utilities are advanced configurations applied to individual playbook steps to control logic, timing, and data processing. According to the Playbook Engine architecture:

Timeout (A):TheTimeoututility allows an administrator to define a maximum duration for a step to complete. If the step does not finish within this designated window, the playbook engine terminates the step and the overall playbook execution to prevent hung processes and resource exhaustion.

Loop (B):TheLooputility is used for iterative processing (e.g., performing a lookup for every IP in a list). A playbook step can only containone Loop utility configuration. If multiple iterations are required across different data sets, they must be handled in separate steps or nested child playbooks.

Condition (D):TheConditionutility (Decision Step logic) behaves differently when aLoopis present. If there is no loop, the condition determines if the step executes once. If a loop is present, the condition is evaluated foreach itemin the loop, effectively acting as a filter for which iterations proceed.

Why other options are incorrect:

Variables (C):TheVariablesutility (Set Variable) is used to define new custom variables within the scope of that step for later use. It does not "store the output of the step directly in the step itself"; step outputs are automatically stored in the vars.steps. object by the engine regardless of the utility used.

Mock Output (E):TheMock Outpututility is used for testing and development to simulate successful data returns without actually executing a connector. It usesJSON format, not HTML, to ensure the simulated data structure matches what the playbook engine expects for downstream Jinja processing.

Comprehensive and Detailed Explanation From FortiSOAR 7.6., FortiSIEM 7.3 Exact Extract study guide:

InFortiAnalyzer 7.6and related SOC versions, incidents serve as centralized containers for tracking and analyzing security events. There are two primary automated and manual methods to initiate an incident:

Using a custom event handler (A):In FortiAnalyzer, event handlers are used to generate events from raw logs.1A critical feature in recent versions is theAutomatically Create Incidentsetting within a custom event handler.2When enabled, the system automatically elevates a triggered event into a new incident record, allowing analysts to bypass the manual review of every individual event before an incident is raised.3

By running a playbook (D):Playbooks provide a powerful way to automate the incident lifecycle.4A playbook can be configured with anEvent Trigger, meaning it executes as soon as an event matches specific criteria. One of the core actions available within these playbooks is theCreate Incidentaction, which can automatically populate incident details, severity, and category based on the triggering event's data.5This ensures high-fidelity events are consistently captured for investigation.

Why other options are incorrect:

Using a connector action (B):While connectors allow FortiAnalyzer to communicate with external systems (like ITSM or Security Fabric devices), the act of "creating an incident"insideFortiAnalyzer is a function of the internal event engine or playbook automation, not a standalone connector action used for external integration.

Manually, on the Event Monitor page (C):While you can view, filter, and acknowledge events on theEvent Monitorpage, the process ofmanuallyraising an incident typically occurs from theIncidentsmodule or by right-clicking an event to "Raise Incident" in the Log View or FortiView, rather than being a core function defined as occurring "on the Event Monitor page" in the same architectural sense as handlers and playbooks.

NIST Cybersecurity Framework Overview:

The NIST Cybersecurity Framework provides a structured approach for managing and mitigating cybersecurity risks. Incident handling is divided into several phases to systematically address and resolve incidents.

Incident Handling Phases:

Preparation: Establishing and maintaining an incident response capability.

Detection and Analysis: Identifying and investigating suspicious activities to confirm an incident.

Containment, Eradication, and Recovery:

Containment: Limiting the impact of the incident.

Eradication: Removing the root cause of the incident.

Recovery: Restoring systems to normal operation.

Containment Phase:

The primary goal of the containment phase is to prevent the incident from spreading and causing further damage.

Quarantining a Compromised Host:

Quarantining involves isolating the compromised host from the rest of the network to prevent adversaries from moving laterally and causing more harm.

Techniques include network segmentation, disabling network interfaces, and applying access controls.

Understanding Event Generation in FortiAnalyzer:

FortiAnalyzer generates events based on predefined rules and conditions to help in monitoring and responding to security incidents.

Analyzing the Options:

Option A:Data selectors filter logs based on specific criteria but do not generate events on their own.

Option B:Connectors facilitate integrations with other systems but do not generate events based on log matches.

Option C:Event handlers are configured with rules that define the conditions under which events are generated. When a log matches a rule in an event handler, FortiAnalyzer generates an event.

Option D:Tasks in playbooks execute actions based on predefined workflows but do not directly generate events based on log matches.

Conclusion:

FortiAnalyzer generates an event when a log matches a rule in an event handler.

Slot 1:dataSlot 2:json_querySlot 3:("results[?type=='FileHash-MD5']")Slot 4:value

Final Expression: {{ vars.artifacts.data | json_query("results[?type=='FileHash-MD5']") .value }}

Comprehensive and Detailed Explanation From FortiSOAR 7.6., FortiSIEM 7.3 Exact Extract study guide:

InFortiSOAR 7.6, advanced data manipulation within playbooks often requires the use ofJMESPathqueries via the json_query Jinja filter. To extract specific data from a complex JSON object (like the vars.artifacts dictionary shown in the exhibit), the analyst must follow the structural hierarchy:

Slot 1 (data):Based on the exhibit, the root of the artifact information is located under vars.artifacts.data. Therefore, "data" is the starting point for the filter.

Slot 2 (json_query):To perform advanced filtering (searching for a specific type), the json_query filter must be applied. This allows the playbook to traverse the list and find items matching a specific key-value pair.

Slot 3 ("results[?type=='FileHash-MD5']"):This is the JMESPath expression. It looks into the results array and applies a filter [?...] to find only those objects where the type attribute exactly matches FileHash-MD5.

Slot 4 (value):Once the correct object(s) are found, the expression needs to return the actual hash. In the JSON exhibit, the MD5 string is stored in the key named value.

Why other options are incorrect:

tojson:This filter converts a dictionary/list into a JSON string, which would break the ability to further query the object for the "value" field.

results (as a standalone slot):While "results" is part of the path, it is handledinsidethe json_query string to allow for conditional filtering.