FCP_FAZ_AN-7.6 Fortinet NSE 5 - FortiAnalyzer 7.6 Analyst Questions and Answers

When a new playbook is created on FortiAnalyzer, the system requires some time toparse and validatethe playbook before it can be executed. Parsing involves checking the playbook's structure, ensuring that all syntax and logic are correct, and preparing the playbook for execution within FortiAnalyzer’s automation engine. This initial parsing step is necessary for FortiAnalyzer to load the playbook into its operational environment correctly.

Here’s why the other options are incorrect:

Option A: FortiAnalyzer needs that time to parse the new playbook

This is correct. The delay is due to the parsing and setup process required to prepare the new playbook for execution. FortiAnalyzer’s automation engine checks for any issues or dependencies within the playbook, ensuring that it can run without errors.

Option B: FortiAnalyzer needs that time to debug the new playbook

This is incorrect.Debugging is not an automatic process that FortiAnalyzer undertakes after playbook creation. Debugging, if necessary, is a manual task performed by the administrator if there are issues with the playbook execution.

Option C: FortiAnalyzer needs that time to back up the current playbooks

This is incorrect. FortiAnalyzer does not automatically back up playbooks every time a new one is created. Backups of configuration and playbooks are typically scheduled as part of routine maintenance and are not triggered by playbook creation.

Option D: FortiAnalyzer needs that time to ensure there are no other playbooks running

This is incorrect. FortiAnalyzer can manage multiple playbooks running simultaneously, so it does not require waiting for other playbooks to finish before initiating a new one. The waiting time specifically relates to the parsing process of the newly created playbook.

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

FortiAnalyzer 7.6 stores on-premises logs in aClickHouse SQL database(not MySQL, Postgres, or Elasticsearch). Fortinet’s FortiAnalyzer 7.6 SQL Query documentation explicitly states that log data is inserted into the SQL database and that“FortiAnalyzer uses a ClickHouse SQL database.”

This is consistent with how the study guide describes the storage/analytics pipeline in 7.6: it explains that FortiAnalyzer indexes incoming raw logs (insert rate)“by the SQL database and the sqlplugind daemon.”This “SQL database” in 7.6 corresponds to the ClickHouse-backed log database described in the Fortinet documentation.

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 FortiAnalyzer study guide states that blocking suspicious indicators is performed by integrating FortiAnalyzer withFortiManager(not by directly pushing a block list to FortiGate). Specifically:“To use this feature, you must set up an authorized FortiManager connector for the FortiAnalyzer on the Fabric Connector page of FortiAnalyzer.”

It then explains the backend mechanism:“In the back end, a playbook called Block_indicator runs every 5 minutes to send the information to FortiManager.”After a successful run,“the blocked indicator is pushed to the FortiManager External Resource list.”From there, FortiManager can create threat feeds/security profiles/policy blocks and push policies to FortiGate as needed—however, the study guide clarifies:“The Blocked status on FortiAnalyzer confirms that the list is updated on FortiManager, but it is not synced to FortiGate.”

Therefore, FortiAnalyzer blocks indicators by using aFortiManager connectorand sending the block information to FortiManager (Option B).

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.

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.

In this output, we see two diagnostic commands executed on a FortiAnalyzer device:

diagnose fortilogd lograte: This command shows the rate at which logs are being processed by the FortiAnalyzer in terms of log entries per second.

diagnose fortilogd msgrate: This command displays the message rate, or the rate at which individual messages are being processed.

The values provided in the exhibit output show:

Log rate (lograte): Consistently high, showing values such as 70.0, 132.1, and 133.3 logs per second over different time intervals.

Message rate (msgrate): Lower values, around 1.4 to 1.6 messages per second.

Explanation

Interpretation of log rate vs. message rate: In FortiAnalyzer, the log rate typically refers to the rate of logs being stored or indexed, while the message rate refers to individual messages within these logs. Given that a single log entry can contain multiple messages, it's common to see a lower message rate relative to the log rate.

Understanding normal operation: In this case, the message rate being lower than the log rate is expected and typical behavior. This discrepancy can arise because each log entry may bundle multiple related messages, reducing the message rate relative to the log rate.

Conclusion

Correct Answer:A. The message rate being lower than the log rate is normal.

This aligns with thenormal operational behavior of FortiAnalyzer in processing logs and messages.

There is no indication that both logs and messages are nearly finished indexing, as that would typically show diminishing rates toward zero, which is not the case here. Additionally, there’s no information in this output about specific ADOMs or a comparison between traffic logs and event logs. Thus, options B, C, and D are incorrect.

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

FortiAnalyzer’s ingestion pipeline does not “drop” logs simply because a parser is unavailable. The study guide states that when devices send logs,“Logs received are decompressed and saved in a log file on the FortiAnalyzer disk”(with a .log extension). This establishes that the raw log is still accepted and stored on disk as part of the normal workflow.

Normalization, however, depends on having a suitable parser. The study guide explains that“FortiAnalyzer uses predefined parsers to extract key fields from ingested logs and maps them to a consistent, standardized set of field names.”It further emphasizes that“Log parsers … are central to log normalization”because they convert unstructured/native logs into a standardized schema.

Therefore, ifno matching parserexists for a given device log, FortiAnalyzer can stillstore the incoming log(it is received, decompressed, and written to disk), but it cannot perform the “extract key fields” and “map to standardized field names” steps required for normalization. In practical terms, the log remains in its native/unstructured form (not normalized), which aligns exactly with optionC.

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

In the exhibit, theEvent Statusshown isUnhandled(Event Type: Web Filter; Severity: Critical). The FortiAnalyzer study guide definesUnhandledevents as events whose security risk has not been addressed and is therefore still active/open. Specifically, it states:“Unhandled: The security risk is considered open.”

This directly matches optionD.

The other options correspond to different statuses or actions:

Isolated/Containedapplies when the risk source is isolated (statusContained), notUnhandled.

Escalatedrefers to events moved/raised for further action (statusEscalated), notUnhandled.

Whether an incident was created cannot be concluded solely from the status “Unhandled” in the exhibit; the study guide ties incident creation to incident management workflows rather than equating “Unhandled” with an incident being created.