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Understanding the Issue:

The custom event handler for detecting SMTP reconnaissance activities is generating a large number of events.

This high volume of events is overwhelming the notification system, leading to potential alert fatigue and inefficiency in incident response.

Event Handler Configuration:

Event handlers are configured to trigger alerts based on specific criteria.

The frequency and volume of these alerts can be controlled by adjusting the trigger conditions.

Possible Solutions:

A. Increase the trigger count so that it identifies and reduces the count triggered by a particular group:

By increasing the trigger count, you ensure that the event handler only generates alerts after a higher threshold of activity is detected.

This reduces the number of events generated and helps prevent overwhelming the notification system.

Selected as it effectively manages the volume of generated events.

B. Disable the custom event handler because it is not working as expected:

Disabling the event handler is not a practical solution as it would completely stop monitoring for SMTP reconnaissance activities.

Not selected as it does not address the issue of fine-tuning the event generation.

C. Decrease the time range that the custom event handler covers during the attack:

Reducing the time range might help in some cases, but it could also lead to missing important activities if the attack spans a longer period.

Not selected as it could lead to underreporting of significant events.

D. Increase the log field value so that it looks for more unique field values when it creates the event:

Adjusting the log field value might refine the event criteria, but it does not directly control the volume of alerts.

Not selected as it is not the most effective way to manage event volume.

Implementation Steps:

Step 1: Access the event handler configuration in FortiAnalyzer.

Step 2: Locate the trigger count setting within the custom event handler for SMTP reconnaissance.

Step 3: Increase the trigger count to a higher value that balances alert sensitivity and volume.

Step 4: Save the configuration and monitor the event generation to ensure it aligns with expected levels.

Conclusion:

By increasing the trigger count, you can effectively reduce the number of events generated by the custom event handler, preventing the notification system from being overwhelmed.

Fortinet Documentation on Event Handlers and Configuration FortiAnalyzer Administration Guide

Best Practices for Event Management Fortinet Knowledge Base

By increasing the trigger count in the custom event handler, you can manage the volume of generated events and prevent the notification system from being overwhelmed.

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

According to theFortiAnalyzer 7.4 SOC Analystofficial training material (Lesson 5: Automation) and supporting documentation forFortiSOAR 7.6andFortiSIEM 7.3integration, the following best practices are recommended for playbook portability:

Disable playbooks before exporting (A):When a playbook is exported, its current status (Enabled or Disabled) is preserved in the export file. If anEnabledplaybook is imported into a destination ADOM where its trigger conditions are immediately met, it will start executing automatically. Disabling the playbook before export is a critical best practice to prevent unintended automated actions from occurring in the new environment before the analyst has had a chance to verify local configurations.

Include the associated connector settings (B):FortiAnalyzer allows you to include required connector configurations during the export process. By selecting this option, the exported file includes the necessary metadata and configurations for the connectors that the playbook relies on to execute its tasks. This ensures the playbook remains functional and portable across different FortiAnalyzer units or ADOMs without requiring the manual recreation of every connector.

Why other options are incorrect:

Move playbooks between ADOMs (C):There is no native "Move" function for automation playbooks between ADOMs in the same sense as moving a device. The standard supported workflow for transferring automation logic is theExport and Importprocess.

Ensure names do not exist in target (D):While maintaining unique names is good practice, it is not a required "best practice" for the export process itself because FortiAnalyzer automatically handles name conflicts. If an imported playbook shares a name with an existing one, the system automatically appends atimestampto the new playbook's name to avoid a conflict.

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.

Understanding the Event Handler Configuration:

The event handler is set up to detect specific security incidents, such as spearphishing, based on logs forwarded from other Fortinet products like FortiSandbox.

An event handler includes rules that define the conditions under which an event should be triggered.

Analyzing the Current Configuration:

The current event handler is named "Spearphishing handler" with a rule titled "Spearphishing Rule 1".

The log viewer shows that logs are being forwarded by FortiSandbox but no events are generated by FortiAnalyzer.

Key Components of Event Handling:

Log Type: Determines which type of logs will trigger the event handler.

Data Selector: Specifies the criteria that logs must meet to trigger an event.

Automation Stitch: Optional actions that can be triggered when an event occurs.

Notifications: Defines how alerts are communicated when an event is detected.

Issue Identification:

Since FortiSandbox logs are correctly forwarded but no event is generated, the issue likely lies in the data selector configuration or log type matching.

The data selector must be configured to include logs forwarded by FortiSandbox.

Solution:

B. Configure a FortiSandbox data selector and add it to the event handler:

By configuring a data selector specifically for FortiSandbox logs and adding it to the event handler, FortiAnalyzer can accurately identify and trigger events based on the forwarded logs.

Steps to Implement the Solution:

Step 1: Go to the Event Handler settings in FortiAnalyzer.

Step 2: Add a new data selector that includes criteria matching the logs forwarded by FortiSandbox (e.g., log subtype, malware detection details).

Step 3: Link this data selector to the existing spearphishing event handler.

Step 4: Save the configuration and test to ensure events are now being generated.

Conclusion:

The correct configuration of a FortiSandbox data selector within the event handler ensures that FortiAnalyzer can generate events based on relevant logs.

Fortinet Documentation on Event Handlers and Data Selectors FortiAnalyzer Event Handlers

Fortinet Knowledge Base for Configuring Data Selectors FortiAnalyzer Data Selectors

By configuring a FortiSandbox data selector and adding it to the event handler, FortiAnalyzer will be able to accurately generate events based on the appropriate logs.

Understanding the Playbook and its Components:

The exhibit shows a playbook in which an event trigger starts actions upon detecting a malicious file.

The initial tasks in the playbook include CREATE_INCIDENT and GET_EVENTS.

Analysis of Current Tasks:

EVENT_TRIGGER STARTER: This initiates the playbook when a specified event (malicious file detection) occurs.

CREATE_INCIDENT: This task likely creates a new incident in the incident management system for tracking and response.

GET_EVENTS: This task retrieves the event details related to the detected malicious file.

Objective of the Next Task:

The next logical step after creating an incident and retrieving event details is to update the incident with the event data, ensuring all relevant information is attached to the incident record.

This helps SOC analysts by consolidating all pertinent details within the incident record, facilitating efficient tracking and response.

Evaluating the Options:

Option A:Update Asset and Identity is not directly relevant to attaching event data to the incident.

Option B:Attach Data to Incident sounds plausible but typically, updating an incident involves more comprehensive changes including status updates, adding comments, and other data modifications.

Option C:Run Report is irrelevant in this context as the goal is to update the incident with event data.

Option D:Update Incident is the most suitable action for incorporating event data into the existing incident record.

Conclusion:

The next task in the playbook should be to update the incident with the event data to ensure the incident reflects all necessary information for further investigation and response.

Understanding the Threat Hunting Data:

The Threat Hunting Monitor in the provided exhibits shows various application services, their usage counts, and data metrics such as sent bytes, average sent bytes, and maximum sent bytes.

The second part of the exhibit lists connection attempts from a specific source IP (10.0.1.10) to a destination IP (8.8.8.8), with repeated "Connection Failed" messages.

Analyzing the Application Services:

DNS is the top application service with a significantly high count (251,400) and notable sent bytes (9.1 MB).

This large volume of DNS traffic is unusual for regular DNS queries and can indicate the presence of DNS tunneling.

DNS Tunneling:

DNS tunneling is a technique used by attackers to bypass security controls by encoding data within DNS queries and responses. This allows them to extract data from the local network without detection.

The high volume of DNS traffic, combined with the detailed metrics, suggests that DNS tunneling might be in use.

Connection Failures to 8.8.8.8:

The repeated connection attempts from the source IP (10.0.1.10) to the destination IP (8.8.8.8) with connection failures can indicate an attempt to communicate with an external server.

Google DNS (8.8.8.8) is often used for DNS tunneling due to its reliability and global reach.

Conclusion:

Given the significant DNS traffic and the nature of the connection attempts, it is reasonable to conclude that DNS tunneling is being used to extract confidential data from the local network.

Why Other Options are Less Likely:

Spearphishing (A): There is no evidence from the provided data that points to spearphishing attempts, such as email logs or phishing indicators.

Reconnaissance (C): The data does not indicate typical reconnaissance activities, such as scanning or probing mail servers.

FTP C&C (D): There is no evidence of FTP traffic or command-and-control communications using FTP in the provided data.

SANS Institute: "DNS Tunneling: How to Detect Data Exfiltration and Tunneling Through DNS Queries" SANS DNS Tunneling

OWASP: "DNS Tunneling" OWASP DNS Tunneling

By analyzing the provided threat hunting data, it is evident that DNS tunneling is being used to exfiltrate data, indicating a sophisticated method of extracting confidential information from the network.

1. Create a parameter in the child playbook.

2. Apply the parameter to the Disable User Account connector action.

3. Map data to the parameter in the Reference a playbook step in the parent playbook.

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

InFortiSOAR 7.6, the methodology for passing data between playbooks—specifically from a parent to a "Referenced" (child) playbook—follows a strict data flow hierarchy:

Step 1: Create a parameter in the child playbook.Before a parent can send data, the child playbook must be configured to receive it. This is done by adding "Input Parameters" in theStartstep of the child playbook (configured as a "Referenced" trigger). These parameters act as the "inbox" for external data.

Step 2: Apply the parameter to the connector action.Once the child playbook has the parameter defined (e.g., user_id), you must use a Jinja expression like {{vars.input.params.user_id}} within the child's action steps (such as theActive Directory: Disable User Accountconnector) so that the child playbook actually utilizes the data it receives.

Step 3: Map data to the parameter in the parent playbook.Finally, in the parent playbook, when you add theReference a Playbookstep and select the child playbook, FortiSOAR automatically displays the parameters created in Step 1. You then map existing variables from the parent's environment (e.g., from a previous "Search by SamAccountName" step) into these fields to complete the hand-off.

Why other options are excluded:

Create a manual trigger and assign the user to a new variable:While manual triggers capture data, they are not the mechanism forpassingdata between nested playbooks; they are for user-to-system interaction.

Create a parameter in the parent playbook:Parameters in a parent playbook are used to receive data fromoutside(like an external API or manual input), not to send datadownto a child. The child defines what it needs; the parent simply provides it in the Reference step.

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.

Understanding FortiAnalyzer Data Policy and Disk Utilization:

FortiAnalyzer uses data policies to manage log storage, retention, and disk utilization.

The Data Policy section indicates how long logs are kept for analytics and archive purposes.

The Disk Utilization section specifies the allocated disk space and the proportions used for analytics and archive, as well as when alerts should be triggered based on disk usage.

Analyzing the Provided Exhibit:

Keep Logs for Analytics:60 Days

Keep Logs for Archive:120 Days

Disk Allocation:300 GB (with a maximum of 441 GB available)

Analytics: Archive Ratio:30% : 70%

Alert and Delete When Usage Reaches:90%

Potential Problems Identification:

Disk Space Allocation:The allocated disk space is 300 GB out of a possible 441 GB, which might not be insufficient if the log volume is high, but it is not the primary concern based on the given data.

Analytics-to-Archive Ratio:The ratio of 30% for analytics and 70% for archive is unconventional. Typically, a higher percentage is allocated for analytics since real-time or recent data analysis is often prioritized. A common configuration might be a 70% analytics and 30% archive ratio. The misconfigured ratio can lead to insufficient space for analytics, causing issues with real-time monitoring and analysis.

Retention Periods:While the retention periods could be seen as lengthy, they are not necessarily indicative of a problem without knowing the specific log volume and compliance requirements. The length of these periods can vary based on organizational needs and legal requirements.

Conclusion:

Based on the analysis, the primary issue observed is theanalytics-to-archive ratiobeing misconfigured. This misconfiguration can significantly impact the effectiveness of the FortiAnalyzer in real-time log analysis, potentially leading to delayed threat detection and response.

Understanding Playbook Triggers:

Playbook triggers are the starting points for automated workflows within FortiAnalyzer or FortiSOAR.

These triggers determine how and when a playbook is executed and can pass relevant information (trigger variables) to subsequent tasks within the playbook.

Types of Playbook Triggers:

EVENT Trigger:

Initiates the playbook when a specific event occurs.

The event details can be used as variables in later tasks to customize the response.

Selected as it allows using event details as trigger variables.

INCIDENT Trigger:

Activates the playbook when an incident is created or updated.

The incident details are available as variables in subsequent tasks.

Selected as it enables the use of incident details as trigger variables.

ON SCHEDULE Trigger:

Executes the playbook at specified times or intervals.

Does not inherently use trigger events to pass variables to later tasks.

Not selected as it does not involve passing trigger event details.

ON DEMAND Trigger:

Runs the playbook manually or as required.

Does not automatically include trigger event details for use in later tasks.

Not selected as it does not use trigger events for variables.

Implementation Steps:

Step 1: Define the conditions for the EVENT or INCIDENT trigger in the playbook configuration.

Step 2: Use the details from the trigger event or incident in subsequent tasks to customize actions and responses.

Step 3: Test the playbook to ensure that the trigger variables are correctly passed and utilized.

Conclusion:

EVENT and INCIDENT triggers are specifically designed to initiate playbooks based on specific occurrences, allowing the use of trigger details in subsequent tasks.

Fortinet Documentation on Playbook Configuration FortiSOAR Playbook Guide

By using the EVENT and INCIDENT triggers, you can leverage trigger events in later tasks as variables, enabling more dynamic and responsive playbook actions.