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

In FortiAnalyzer,archive logsrefer to logs that have been compressed and stored to save space. This process involves compressing the raw log files into the .gz format, which is a common compression format used in Fortinet systems for archived data. Archiving is essential in FortiAnalyzer to optimize storage and manage long-term retention of logs without impacting performance.

Let’s examine each option for clarity:

Option A: Logs that are indexed and stored in the SQL database

This is incorrect. While some logs are indexed andstored in an SQL database for quick access and searchability, these are not classified asarchive logs. Archived logs are typically moved out of the database and compressed.

Option B: Logs a FortiAnalyzer administrator can access in FortiView

This is incorrect becauseFortiViewprimarily accesses logs that are active and indexed, not archived logs. Archived logs are stored for long-term retention but are not readily available for immediate analysis in FortiView.

Option C: Logs compressed and saved in files with the .gz extension

This is correct. Archive logs on FortiAnalyzer are stored in compressed .gz files to reduce space usage. This archived format is used for logs that are no longer immediately needed in the SQL database but are retained for historical or compliance purposes.

Option D: Logs previously collected from devices that are offline

This is incorrect. Although archived logs may include data from devices that are no longer online, this is not a defining characteristic of archive logs.

In FortiAnalyzer's incident management system, analysts have the option to manually manage incidents, which includes attaching relevant reports to an incident for further investigation and documentation. This feature allows analysts to consolidate information, such as detailed reports on suspicious activity, into an incident record, providing a comprehensive view for incident response.

Let's review the other options to clarify why they are incorrect:

Option A: You can manually attach generated reports to incidents

This is correct. FortiAnalyzer allows analysts to manually attach reports to incidents, which is beneficial for providing additional context, evidence, or analysis related to the incident. This functionality is part of the incident management process and helps streamline information for tracking and resolution.

Option B: The status of the incident is always linked to the status of the attached event

This is incorrect. The status of an incident on FortiAnalyzer is managed independently of the status of any attached events. An incident can contain multiple events, each with different statuses, but the incident itself is tracked separately.

Option C: Severity incidents rated with the level High have an initial service-level agreement (SLA) response time of 1 hour

This is incorrect. While incidents have severity levels, specific SLA response times are typically set according to the organization’s incident response policy, and FortiAnalyzer does not impose a default SLA response time of 1 hour for high-severity incidents.

Option D: Incidents must be acknowledged before they can be analyzed

This is incorrect. Incidents on FortiAnalyzer can be analyzed even if they are not yet acknowledged. Acknowledging an incident is often part of the workflow to mark it as being actively addressed, but it is not a prerequisite for analysis.

In FortiAnalyzer, when a playbook is run, each task’s status impacts the overall playbook status. Here’s what happens based on task outcomes:

Status When All Tasks Succeed:

If all tasks finish successfully, the playbook status ismarked asSuccess.

Status When Some Tasks Fail:

If one or more tasks in the playbook fail, but others succeed, the playbook status generally changes toAttention required. This status indicates that the playbook completed execution but requires review due to one or more tasks failing.

This is different from a completeFailedstatus, which is used if the playbook cannot proceed due to a critical error in an early task, often one that upstream tasks depend on.

Option Analysis:

A. Attention required: This is correct as the playbook has completed, but with partial success and a task requiring review.

B. Upstream_failed: This status is used if a task cannot run because a prerequisite or "upstream" task failed. Since four out of five tasks completed, this is not the case here.

C. Failed: This status would imply that the playbook completely failed, which does not match the scenario where only one task out of five failed.

D. Success: This status would apply if all tasks had completed successfully, which is not the case here.

Conclusion:

Correct Answer:A. Attention required

The playbook status reflects that it completed, but an error occurred in one of the tasks, prompting the administrator to review the failed task.

The exhibit shows a graph that tracks two metrics over time:Receive RateandInsert Rate. These two rates are crucial for understanding the log processing behavior in FortiAnalyzer.

Understanding Receive Rate and Insert Rate:

Receive Rate: This is the rate at which FortiAnalyzer is receiving logs from connected devices.

Insert Rate: This is the rate at which FortiAnalyzer is indexing (inserting) logs into its database for storage and analysis.

Data Point at 21:20:

At 21:20, theInsert Rateline is above theReceive Rateline, indicating that FortiAnalyzer is inserting logs into its database at a faster rate than it is receiving them. This situation suggests that FortiAnalyzer is able to keep up with the incoming logs and is possibly processing a backlog or temporarily received logs faster than new logs are coming in.

Option Analysis:

Option A - FortiAnalyzer is Indexing Logs Faster Than Logs are Being Received: This accurately describes the scenario at 21:20, where the Insert Rate exceeds the Receive Rate. This indicates that FortiAnalyzer is handling logs efficiently at that moment, with no backlog in processing.

Option B - The fortilogd Daemon is Ahead in Indexing by One Log: The data does not provide specific information about the fortilogd daemon’s log count, only the rates. This option is incorrect.

Option C - SQL Database Requires a Rebuild: High receive lag would imply a backlog in receiving and indexing logs, typically visible if the Receive Rate were significantly above the Insert Rate, which is not the case here.

Option D - FortiAnalyzer is Temporarily Buffering Logs to Index Older Logs First: There is no indication of buffering in this scenario. Buffering would usually occur if the Receive Rate were higher than the Insert Rate, indicating that FortiAnalyzer is storing logs temporarily due to indexing lag.

Conclusion:

Correct Answer:A. FortiAnalyzer is indexing logs faster than logs are being received.

The graph at 21:20 shows a higher Insert Rate than Receive Rate, indicating efficient log processing by FortiAnalyzer.

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.

Macros in FortiAnalyzer are used to streamline reporting tasks by automating dataextraction and report generation. Here’s a breakdown of each option to determine the correct answer:

Option A - Macros are Predefined Templates for Reports and Cannot be Customized:

This statement is incorrect. Macros in FortiAnalyzer are not simply fixed templates; they allow for customization to tailor data extraction and reporting based on specific needs and configurations.

Conclusion:Incorrect.

Option B - Macros are Useful in Generating Excel Log Files Automatically Based on the Report Settings:

This statement is accurate. Macros in FortiAnalyzer can be configured to automate the generation of reports, including outputting log data to Excel format based on predefined report settings. This makes them especially useful for scheduled reporting and data analysis.

Conclusion:Correct.

Option C - Macros are ADOM-Specific and Each ADOM Type Has Unique Macros Relevant to that ADOM:

Macros are not limited to specific ADOMs, nor are they ADOM-specific. Macros can be applied across various ADOMs based on report configurations but are not inherently tied to or unique for each ADOM type.

Conclusion:Incorrect.

Option D - Macros are Supported Only on the FortiGate ADOMs:

This is not true. Macros in FortiAnalyzer are not restricted to FortiGate ADOMs; they can be utilized across different ADOMs that FortiAnalyzer manages.

Conclusion:Incorrect.

Conclusion:

Correct Answer:B. Macros are useful in generating excel log files automatically based on the report settings.

This answer correctly describes thefunctionality of macros in FortiAnalyzer, emphasizing their role in automating report generation, especially for Excel log files.

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:

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.

To ensure that reports generated by FortiAnalyzer are automatically sent to an email inbox, you need to set up an output profile for the reports. Output profiles specify where and how reports should be delivered, including the option to send them via email.

Option A - Enable the Option to Email All Reports Under the Mail Server:

The mail server configuration allows FortiAnalyzer to send emails but does not automatically enable email distribution for reports. This setting alone does not specify which reports to send or to whom.

Conclusion:Incorrect.

Option B - Add a mailto:<email address> Option Within the Report Layouts:

Adding an email address within the report layout is not a standard configuration option for report distribution. Report layouts define the format andcontent of the report but not its distribution method.

Conclusion:Incorrect.

Option C - Enable Email Notification Under the Report Calendar:

The report calendar is used to schedule when reports are generated. While it triggers report generation at specific times, it does not handle email distribution. Emailing reports requires a configured output profile.

Conclusion:Incorrect.

Option D - Enable an Output Profile on the Reports:

An output profile can be configured on FortiAnalyzer to define delivery options, including emailing the report to specified recipients. This setup ensures that every time a report is generated according to the schedule, it is automatically emailed to the configured address.

Conclusion:Correct.

Conclusion:

Correct Answer:D. Enable an output profile on the reports.

Configuring an output profile is the correct way to set up automatic email distribution of generated reports in FortiAnalyzer.

In FortiAnalyzer’s SQL query syntax, the typical order for querying the database follows the standard SQL format, which is:

SELECT FROM

GROUP BY

Option Dcorrectly follows this structure:

SELECT devid FROM $log: This specifies that the query is selecting the devid column from the $log table.

WHERE 'user' = ': This part of the query is intended to filter results based on a condition involving the user column. Although there appears to be a minor typographical issue (possibly missing the user value after =), it structurally adheres to the correct SQL order.

GROUP BY devid: This groups the results by devid, which is correctly positioned at the end of the query.

Let’s briefly examine why the other options are incorrect:

Option A: SELECT devid FROM $log GROUP BY devid WHERE 'user', 'users1'

This is incorrect because the GROUP BY clause appears before the WHERE clause, which is out of order in SQL syntax.

Option B: SELECT FROM $log WHERE devid 'user', USER1' GROUP BY devid

This is incorrect because it lacks a column in the SELECT statement and the WHERE clause syntax is malformed.

Option C: SELCT devid WHERE 'user' - 'USER1' FROM $log GROUP BY devid

This is incorrect because the SELECT keyword is misspelled as SELCT, and the WHERE condition syntax is invalid.

[: FortiAnalyzer documentation for SQLqueries indicates that the standard SQL order should be followed when querying logs in FortiAnalyzer. Queries should follow the format SELECT ... FROM ... WHERE ... GROUP BY ..., as demonstrated in option D​., ]

Questions 20

Which two statements about exporting and importing playbacks are true? (Choose two.)

Options:

A.

A playbook that was disabled when it was exported mil be disabled when it is imported.

B.

Playbooks can soimported 10 a different FortiAnayzer device, but only if the connectors already exist

C.

You can import a playbook even if there is another one win the same name in the destination

D.

You can export only one playbook at a time.

Show Answer Buy Now

Answer:

A, B

Exam Code: FCP_FAZ_AN-7.6

Exam Name: Fortinet NSE 5 - FortiAnalyzer 7.6 Analyst

Last Update: Dec 28, 2025

Questions: 67

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