Pass the Fortinet Certified Professional Security Operations FCP_FAZ_AN-7.6 Questions and answers with ExamsMirror

In the exhibit, the playbook configuration shows the analyst working with the "Attach Data" action within a playbook. Here’s a breakdown of key aspects:

Incident ID: This field is linked to the "Playbook Starter," which indicates that the playbook will attach data to an existing incident.

Attachment: The analyst is configuring an attachment by selecting Run_REPORT with a placeholder ID for report_uuid. This suggests that the report’s UUID will dynamically populate as part of the playbook execution.

Analysis of Options:

Option A - Creating a Trigger Variable:

A trigger variable would typically be set up in the playbook starter or initiation configuration, not within the "Attach Data" action. The setup here does not indicate a trigger, as it’s focusing on data attachment.

Conclusion:Incorrect.

Option B - Creating an Output Variable:

The field Attachment with a report_uuid placeholder suggests that the analyst is defining an output variable that will store the report data or ID,allowing it to be attached to the incident. This variable can then be referenced or passed within the playbook for further actions or reporting.

Conclusion:Correct.

Option C - Creating a Report in the Playbook:

While Run_REPORT is selected, it appears to be an attachment action rather than a report generation task. The purpose here is to attach an existing or dynamically generated report to an incident, not to create the report itself.

Conclusion:Incorrect.

Option D - Creating a SOC Report:

Similarly, this configuration is focused on attaching data, not specifically generating a SOC report. SOC reports are generally predefined and generated outside the playbook.

Conclusion:Incorrect.

Conclusion:

Correct Answer:B. The analyst is trying to create an output variable to be used in the playbook.

The setup allows the playbook to dynamically assign the report_uuid as an output variable, which can then be used in further actions within the playbook.

The FortiSOAR management extension is designed as an independent security orchestration, automation, and response (SOAR) solution that integrates with other Fortinet products but requires its own dedicated device or virtual machine (VM) environment. FortiSOAR is not natively integrated as a container or service within FortiAnalyzer or FortiManager, and it operates separately to manage complex security workflows and incident responses across various platforms.

Let’s examine each option to determine the correct answer:

Option A: It requires a FortiManager configured to manage FortiGate

This is incorrect. FortiSOAR operates independently of FortiManager. While FortiSOAR can receive input or data from FortiGate (often managed by FortiManager), it does not require FortiManager to be part of its setup.

Option B: It runs as a docker container on FortiAnalyzer

This is incorrect. FortiSOAR does not run as a container within FortiAnalyzer. It requires its own dedicated environment, either as a physical device or a virtual machine, due to the resource requirements and specialized functions itperforms.

Option C: It requires a dedicated FortiSOAR device or VM

This is correct. FortiSOAR is deployed as a standalone device or VM, which enables it to handle the intensive processing needed for orchestrating security operations, integrating with third-party tools, and automating responses across an organization’s security infrastructure.

Option D: It does not include a limited trial by default

This is incorrect. FortiSOAR installations may come with trial options or demos in specific scenarios, especially for evaluation purposes. This depends on licensing and deployment policies.

Comprehensive and Detailed Explanation From Exact Extract of knowledge of FortiAnalyzer 7.6 Study guide documents:

The exhibit shows the eventEvent Status = MitigatedandEvent Type = Web Filter, with the event message indicating the web request wasblocked.

The study guide definesMitigatedevents as follows:“Mitigated: The security risk is mitigated by being blocked or dropped.”This means a mitigated status corresponds to enforcement that prevented the risk (block/drop), not a condition where the source is isolated.

It also distinguishesContainedevents from mitigated ones:“Contained: The risk source is isolated.”Since the exhibit clearly showsMitigated(not Contained), optionBis incorrect.

Additionally, the study guide notes:“Generally, you can acknowledge mitigated events because the related traffic was blocked by the firewall.”This aligns directly with the exhibit’s “blocked” wording and supports that the correct interpretation is that the security risk was blocked.

Finally, the event type displayed isWeb Filter, not application control, so optionDis incorrect.

Therefore, the correct statement isC. The security risk was blocked.

Comprehensive and Detailed Explanation From Exact Extract of knowledge of FortiAnalyzer 7.6 Study guide documents:

The study guide explains that FortiAnalyzer playbook tasks rely on connectors, and that the FortiOS connector will not show its available actions until FortiGate is configured with the correct automation trigger. The guide states:“For example, the FortiOS connector will be listed as soon as the first FortiGate device is added to FortiAnalyzer. However, to see the actions related to that FortiOS connector, you must enable an automation rule using the Incoming Webhook Call trigger on FortiGate.”

This is why the required FortiGate trigger type isIncoming webhook(option B): it is the specific trigger FortiOS must use so FortiAnalyzer can expose and use the FortiOS connector actions within the playbook workflow.

In the exhibit, the data structure shows a checksum field and a data field with a long, seemingly encoded string. This format is indicative of a file that has been compressed or encoded for storage and transfer.

Export Data Type:

The data field is likely a base64-encoded string, which is commonly used to represent binary data in text format. Base64 encoding is often applied to data that has been compressed (zipped) for easier handling and transfer. The checksum field, with an MD5 hash, provides a way to verify the integrity of the data after decompression.

Option Analysis:

A. The export data type is zipped: Correct. The compressed and encoded format of the data suggests that the export is in a zipped format, allowing for efficient storage and transfer.

B. The playbook is misconfigured: There is no indication of misconfiguration in this exhibit. The presence of the checksum and data fields aligns with standard export practices.

C. The option to include the connector was not selected: There is no evidence in the output to conclude that connectors are missing. Connectors are typically listed separately and would not directly affect the checksum and encoded data structure.

D. Your colleague put a password on the export: There’s no indication of password protection in the exhibit. Password protection would likely alter the data structure, and there would be some mention of encryption.

Conclusion:

Correct Answer:A. The export data type is zipped.

This answer is consistent with the typical use of base64 encoding for compressed (zipped) data exports in FortiAnalyzer.

Comprehensive and Detailed Explanation From Exact Extract of knowledge of FortiAnalyzer 7.6 Study guide documents:

The study guide explains that FortiAI token usage includesboth the prompt (input) and the response (output), and that “generally, more text in the query and response results in using more tokens.” It provides two comparison examples and concludes that the more verbose request for “all the log entries” consumes more tokens because it hasmore textand also triggers alarger response; whereas limiting the query to a time range (for example, “(past week)”) reduces output volume and therefore token usage.

Applying that guidance to the options:

Cis the most verbose and explicitly requests “all the log entries,” which drives higher input and output token usage.

Brequests “all logs” for the week (broad scope), which typically increases output tokens.

Dis short, but it doesnotconstrain the time range, which can increase the response size (output tokens).

Ais concise and includes a time constraint “(past week),” matching the study guide’s example of a lower-token query pattern.

The objective is to create a filter that identifies all login attempts to the FortiAnalyzer web interface (GUI) coming fromLaptop1(IP 10.1.1.100) and excludes the admin user. This filter should match any user other than admin.

Filter Components Analysis:

Operation-login: This portion of the filter will target login actions specifically, which is correct for filtering login attempts.

performed_on==’’GUI(10.1.1.100)’: This indicates that the login attempt must occur on the GUI interface and originate from the specified IP, which matches Laptop1's IP address (10.1.1.100). This ensures that the filter only matches GUI logins from this specific device.

user!=admin: This part excludes logins by the admin user, meeting the requirement to capture only non-admin users.

Option Analysis:

Option A: Correctly specifies theOperation-login,performed_on==’’GUI(10.1.1.100)’, anduser!=admin. This setup effectively filters login attempts to the GUI from Laptop1, excluding the admin user.

Option B: Uses the incorrect IP 10.1.1.120 in the performed_on filter, which does not match Laptop1's IP (10.1.1.100).

Option C: This option includessrcip==10.1.1.100anddstip==10.1.1.210but incorrectly specifiesuser==admininstead ofuser!=admin, which does not match the requirement to exclude admin users.

Option D: This option does not specify theperformed_onfield to restrict it to the GUI and only includesdstip(destination IP) withoutsrcip. It also incorrectly uses user!-admin instead of the correct syntaxuser!=admin.

Conclusion:

Correct Answer:A. Operation-login and performed_on==’’GUI(10.1.1.100)’ and user!=admin

This filter precisely captures the required conditions: login attempts from Laptop1 to the GUI interface by any user except admin.

Comprehensive and Detailed Explanation From Exact Extract of knowledge of FortiAnalyzer 7.6 Study guide documents:

The exhibit shows the log as a single-line key/value entry (not a columnar/table display), which aligns with FortiAnalyzer’sraw log formatview option. The study guide states:“You can toggle between viewing formatted and raw logs.”This directly supports observationD.

At the same time, what you are viewing in FortiAnalyzer Log View isnormalizeddata (FortiAnalyzer parses and maps device logs into standardized fields for consistent searching and analysis). The study guide explicitly states:“The log view allows you to view all log types received by FortiAnalyzer in normalized log format.”It also explains that FortiAnalyzer “uses predefined parsers to extract key fields from ingested logs and maps them to a consistent, standardized set of field names,” then stores them as normalized logs in the SIEM database. This supports observationA.

Finally, the study guide clarifies that even when you switch to raw log format in FortiAnalyzer, you are still observing the normalized-field representation produced by FortiAnalyzer’s parser/normalization process (rather than the untouched original device message). It notes that a FortiGate event log “has been normalized by FortiAnalyzer,” and when you switch “to raw log format,” you can observe the effect of normalization on common fields. This is whyCis not the best description for the exhibit.