FCP_FAZ_AN-7.4 FCP - FortiAnalyzer 7.4 Analyst Questions and Answers

Option A - Purging Log Entries:

A SELECT query in SQL is used to retrieve data from a database and does not have the capability to delete or purge log entries. Purging logs typically requires a DELETE or TRUNCATE command.

Conclusion: Incorrect.

Option B - WHERE Clause Requirement:

In SQL, a SELECT query does not require a WHERE clause. The WHERE clause is optional and is used only when filtering results. A SELECT query can be executed without it, meaning this statement is false.

Conclusion: Incorrect.

Option C - Displaying Database Schema:

A SELECT query retrieves data from specified tables, but it is not used to display the structure or schema of the database. Commands like DESCRIBE, SHOW TABLES, or SHOW COLUMNS are typically used to view schema information.

Conclusion: Incorrect.

Option D - Usage in Macros:

FortiAnalyzer and similar systems often use macros for automated functions or specific query-based tasks. SELECT queries are typically not included in macros because macros focus on procedural or repetitive actions, rather than simple data retrieval.

Conclusion: Correct.

Conclusion:

Correct Answer: D. They are not used in macros.

This aligns with typical SQL usage and the specific functionalities of FortiAnalyzer.

When a new playbook is created on FortiAnalyzer, the system requires some time to parse and validate the 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.

In FortiAnalyzer, event handlers can be configured to trigger specific notifications when an event matches defined criteria. These notifications are designed to alert administrators in real time about critical events.

Option B - Send SNMP Trap:

FortiAnalyzer supports sending SNMP traps as one of the notification methods when an event matches an event handler. This allows integration with SNMP-enabled network management systems, which can then trigger further alerts or actions based on the trap received.

Conclusion: Correct.

Option C - Send SMS Notification:

FortiAnalyzer also supports SMS notifications, enabling alerts to be sent via SMS to predefined recipients. This method is useful for administrators who require immediate alerts but may not have access to email or other notification systems at all times.

Conclusion: Correct.

Option A - Send Alert through Fabric Connectors:

While Fabric Connectors allow FortiAnalyzer to interact with other parts of the Security Fabric, they are primarily used for data sharing and automation rather than directly for sending alerts or notifications.

Conclusion: Incorrect.

Option D - Send Alert through FortiSIEM MEA:

FortiSIEM integration allows for data sharing and further analysis within the Fortinet ecosystem, but it does not directly act as a notification method from FortiAnalyzer itself.

Conclusion: Incorrect.

Conclusion:

Correct Answer: B. Send SNMP trap and C. Send SMS notification

These options represent valid notification methods for FortiAnalyzer’s event handler configuration.

In FortiOS 7.4.1 and FortiAnalyzer 7.4.1, the "Unhandled" status in logs typically signifies that the FortiGate encountered a security event but did not take any specific action to block or alter it. This usually occurs in the context of Intrusion Prevention System (IPS) logs.

IPS logs with action=pass: When the IPS engine inspects traffic and determines that it does not match any known attack signatures or violate any configured policies, it assigns the action "pass". Since no action is taken to block or modify this traffic, the status is logged as "Unhandled."

Let's look at why the other options are incorrect:

An AV log with action=quarantine: Antivirus (AV) logs with the action "quarantine" indicate that a file was detected as malicious and moved to quarantine. This is a definitive action, so the status wouldn't be "Unhandled."

A WebFilter log will action=dropped: WebFilter logs with the action "dropped" indicate that web traffic was blocked according to the configured web filtering policies. Again, this is a specific action taken, not an "Unhandled" event.

An AppControl log with action=blocked: Application Control logs with the action "blocked" mean that an application was denied access based on the defined application control rules. This is also a clear action, not "Unhandled."

In the exhibit, we see a playbook in FortiAnalyzer designed to retrieve events based on specific criteria, create an incident, and attach relevant data to that incident. The "Get Event" task configuration specifies filters to match any of the following conditions:

Severity = High

Event Type = Web Filter

Tag = Malware

Analysis of Events:

In the FortiAnalyzer Event Monitor list:

We need to identify events that meet any one of the specified conditions (since the filter is set to "Match Any Condition").

Events Matching Criteria:

Severity = High:

There are two events with "High" severity, both with the "Event Type" IPS.

Event Type = Web Filter:

There are two events with the "Event Type" Web Filter. One has a "Medium" severity, and the other has a "Low" severity.

Tag = Malware:

There are two events tagged with "Malware," both with the "Event Type" Antivirus and "Medium" severity.

After filtering based on these criteria, there are four distinct events:

Two from the "Severity = High" filter.

One from the "Event Type = Web Filter" filter.

One from the "Tag = Malware" filter.

Conclusion:

Correct Answer: D. Four events will be added.

This answer matches the conditions set in the playbook filter configuration and the events listed in the Event Monitor.

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 the normal 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.

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.

The command diagnose sql status sqlreportd is used in FortiAnalyzer to obtain specific information about the SQL reporting process and caching status. Here’s what this command accomplishes and an analysis of each option:

Command Functionality:

sqlreportd is the FortiAnalyzer daemon responsible for managing SQL-based reporting processes.

The diagnose sql status sqlreportd command provides information on active SQL query connections and the hcache (historical cache) status, which helps in monitoring and troubleshooting SQL report generation.

Option Analysis:

Option A - To View a List of Scheduled Reports:

This option is incorrect because the command does not list scheduled reports. Instead, it focuses on SQL reporting processes and cache details.

Option B - To List the Current SQL Processes Running:

While the command may show active SQL connections, its primary focus is not a detailed list of all SQL processes but rather the connections and cache status for reporting.

Option C - To Display the SQL Query Connections and hcache Status:

This is correct. The command specifically provides information on SQL query connections related to the reporting process (sqlreportd) and displays the hcache status.

Option D - To Identify the Database Log Insertion Status:

This is incorrect. The command does not provide details on log insertion status. Log insertion status is typically monitored through different diagnostic commands focused on database processes and log handling.

Conclusion:

Correct Answer: C. To display the SQL query connections and hcache status

This command is used to monitor SQL reporting activities and cache status, aiding in the analysis of report generation performance and connection health.

When you frequently use the same search parameters in FortiAnalyzer’s Log View, setting up a reusable filter or view can save considerable time. Here’s an analysis of each option:

Option A - Configure a Custom Dashboard:

Custom dashboards are useful for displaying a variety of widgets and summaries on network activity, performance, and threat data, but they are not designed for storing specific search filters for log views.

Conclusion: Incorrect.

Option B - Configure a Custom View:

Custom views in FortiAnalyzer allow analysts to save specific search filters and configurations. By setting up a custom view, you can retain your frequently used search parameters and quickly access them without needing to reapply filters each time. This option is specifically designed to streamline the process of recurring log searches.

Conclusion: Correct.

Option C - Configure a Data Selector:

Data selectors are used to define specific types of data for FortiAnalyzer reports and widgets. They are useful in reports but are not meant for saving and reusing log search parameters in Log View.

Conclusion: Incorrect.

Option D - Configure a Macro and Apply It to Device Groups:

Macros in FortiAnalyzer are generally used for automation tasks, not for saving log search filters. Applying macros to device groups does not fulfill the requirement of saving specific log view search parameters.

Conclusion: Incorrect.

Conclusion:

Correct Answer: B. Configure a custom view.

Custom views allow you to save specific search filters, enabling quick access to frequently used parameters in Log View.

In FortiAnalyzer, archive logs refer 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 and stored in an SQL database for quick access and searchability, these are not classified as archive 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 because FortiView primarily 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.

When an incident in FortiAnalyzer is identified as a false positive and its status is updated to "Closed: False Positive," certain records and logs are updated to reflect this change.

Option A - The Audit History Log Will Be Updated:

FortiAnalyzer maintains an audit history log that records changes to incidents, including updates to their status. When an incident status is marked as "Closed: False Positive," this action is logged in the audit history to ensure traceability of changes. This log provides accountability and a record of how incidents have been handled over time.

Conclusion: Correct.

Option B - The Corresponding Event Will Be Marked as Mitigated:

Changing an incident to "Closed: False Positive" does not affect the status of the original event itself. Marking an incident as a false positive signifies that it does not represent a real threat, but it does not imply that the event has been mitigated.

Conclusion: Incorrect.

Option C - The Incident Will Be Deleted:

Marking an incident as "Closed: False Positive" does not delete the incident from FortiAnalyzer. Instead, it updates the status to reflect that it is not a real threat, allowing for historical analysis and preventing similar false positives in the future. Deletion would typically only occur manually or by a different administrative action.

Conclusion: Incorrect.

Option D - The Incident Number Will Be Changed:

The incident number is a unique identifier and does not change when the status of the incident is updated. This identifier remains constant throughout the incident's lifecycle for tracking and reference purposes.

Conclusion: Incorrect.

Conclusion:

Correct Answer: A. The audit history log will be updated.

This is the most accurate answer, as the update to "Closed: False Positive" is recorded in FortiAnalyzer’s audit history log for accountability and tracking purposes.