C1000-162 IBM Security QRadar SIEM V7.5 Analysis Questions and Answers

The Application Overview dashboard in QRadar includes various default items1. Two of these items are Top Applications (Total Bytes) and Outbound Traffic by Country (Total Bytes)1.

Default dashboards - IBM Documentation

According to the IBM Security QRadar SIEM V7.5 documentation, the Application Overview dashboard by default includes items such as "Inbound Traffic by Country (Total Bytes)," "Outbound Traffic by Country (Total Bytes)," and "Top Applications (Total Bytes)" among others. This confirms that options C and D are displayed by default on the Application Overview dashboard​​.

In QRadar, to limit the time period for which an AQL (Ariel Query Language) query is evaluated, the functions and clauses that can be used include START, STOP, LAST, NOW, and PARSEDATETIME. Specifically, the LAST function is used to define a relative time range for the query, such as "LAST 2 DAYS"​​.

Understanding Offense Creation in QRadar: QRadar SIEM generates offenses based on the correlation of various types of information to detect potential security threats and incidents.

Analyzed Information for Offense Creation:

Incoming Events and Flows: QRadar collects and analyzes incoming log events and network flows to identify suspicious activities.

Asset Information: Information about the assets within the organization, including their roles and vulnerabilities, is crucial for accurate threat detection.

Known Vulnerabilities: QRadar uses data about known vulnerabilities to correlate events and determine if a potential threat is exploiting these vulnerabilities.

Relevance of the Selected Information: The combination of incoming events, flows, asset information, and known vulnerabilities provides a comprehensive view that helps QRadar accurately identify and correlate potential security incidents, resulting in the creation of offenses.

Reference Confirmation: According to IBM QRadar documentation, the correct combination of analyzed information for creating offenses includes incoming events and flows, asset information, and known vulnerabilities.

References:

IBM QRadar documentation on offense creation and analysis confirms the use of incoming events, flows, asset information, and known vulnerabilities.

Selecting "False Positive" from the right-click menu in the Log Activity tab opens a window that enables users to tune out events that are known to be false positives, preventing them from generating offenses. This feature is crucial for minimizing noise and focusing on genuine threats, thereby enhancing the efficiency of threat detection and response processes within QRadar​​.

X-Force Exchange: The primary repository for contributed QRadar content, including compliance-focused content packs.

HIPAA Packs: Likely contain:

Predefined searches: Relevant to HIPAA monitoring and auditing

Reports: To generate structured documentation for compliance

Custom Rules: To detect potential HIPAA-related violations

Custom properties: To enhance event/flow data for HIPAA context

Other Options (less suitable):

Use Case Manager: Broader purpose, might include HIPAA use cases

Pulse App: Primarily dashboard oriented, not focused on content distribution

IBM Fix Central: Focuses on software fixes, not compliance content

References:

IBM X-Force Exchange: https://exchange.xforce.ibmcloud.com/hub  (Search for HIPAA)

Threshold rules in QRadar are designed to test events or flows for activities that are greater than or less than a specified range. These rules are particularly useful for detecting significant changes such as bandwidth usage variations, failed services, changes in the number of connected users, and large outbound data transfers. By setting acceptable limits within threshold rules, administrators can effectively monitor for and respond to abnormal activities within the network​​.

A Quick filter search in IBM Security QRadar SIEM operates on raw event or flow data. This type of search allows users to rapidly filter through large volumes of data to find specific events or flows of interest without the need for complex query syntax. Quick filter searches are particularly useful for conducting initial analyses or when looking for specific indicators within the raw data streams. The ability to search directly on raw event or flow data enables analysts to work with the most granular level of information available, facilitating detailed investigations and the identification of subtle patterns or anomalies that might indicate security issues .

Quick Filter Behavior: The Quick Filter heavily restricts search results to items matching the keywords you've entered. If your valid AQL doesn't match the Quick Filter, you won't get results.

Disabling to Verify: The easiest way to confirm this is to temporarily disable the Quick Filter and rerun your AQL search.

AQL Focus: AQL is QRadar's search language primarily used for analyzing:

Log Activity: The core area to search events received from various log sources.

Offenses: Offenses are generated based on rule triggering, and you can search them to investigate patterns.

In Rule Response for Offense Naming, QRadar provides options to either contribute to or set/replace the name of the associated offenses. These options allow for dynamic naming of offenses based on event name information, facilitating easier identification and categorization of offenses​​.

Offense Summary Window: The Offense Summary window provides detailed information about a specific offense.

Display Menu: Within this window, the "Display" menu offers options to customize what information is shown.

Rules Option: Selecting "Display > Rules" will reveal a list of rules that contributed to the chained offense sequence.

References

IBM QRadar Documentation - Offense Summary: [invalid URL removed]

IBM QRadar Documentation: Offense Chaining https://www.ibm.com/docs/en/qsip/7.4?topic=management-offense-chaining

The magnitude rating of an offense in QRadar is calculated based on relevance, severity, and credibility. Relevance determines the impact on the network, credibility indicates the integrity of the offense, and severity represents the level of threat. QRadar uses complex algorithms to calculate and periodically re-evaluate the offense magnitude rating​​.

QRadar will mark an Event offense as dormant if no new events or flows occur within 30 minutes. However, if QRadar did not process any events within 4 hours, this also triggers the offense to become dormant. Once dormant, the offense remains in this state for 5 days unless new events or flows are added​​​​.

While the documentation does not explicitly list "Stored" and "Parsed" as categories comprising events, it discusses high-level event categories and the process of categorizing incoming events for easy searching. Without specific mention of the categories "Stored" and "Parsed," the provided documentation does not verify any of the options directly. Further insight into event categories is provided by discussing how events are grouped into high-level categories for organizational purposes​​.

QRadar uses a red star icon to visually identify events that directly contributed to triggering an offense. These events fully matched all the criteria specified in the rule that generated the offense.

Partially matched events may also be associated with the offense (especially for rules using match counts), but they won't have the red star. These events are still valuable for providing context during investigations.

In IBM Security QRadar SIEM V7.5, the integration with MITRE ATT&CK framework is a valuable feature that enhances the understanding of threat tactics and techniques. The Use Case Manager within QRadar provides detailed insights into various MITRE ATT&CK tactics and techniques associated with different offenses or alerts. To get more information about a specific MITRE entry, users can click on the Tactic’s Explore icon associated with the entry. This action opens the corresponding page on the MITRE ATT&CK website, providing detailed information about the tactic or technique, including its description, examples of use, and mitigation strategies. This direct link to the MITRE ATT&CK website enriches the user's knowledge and aids in the analysis of security incidents, making it easier to understand the context and implications of specific attack behaviors observed in the monitored environment.

To check the offenses triggered and mapped to the MITRE ATT&CK framework using the Use Case Manager app, an analyst can navigate through the Offenses tab, click on All Offenses, and then utilize the All Offenses Summary toolbar to display rules contributing to an offense. This process allows for an investigation into how offenses correlate with the MITRE ATT&CK framework. However, the exact option "Detected in timeframe" is not explicitly mentioned in the provided documentation, and the described procedure offers a broader approach to reviewing offenses and their associated rules within the MITRE ATT&CK context​​.

Here's the breakdown of why this approach is the most suitable:

Focused Export: The "Event Export (with AQL)" option allows targeted exporting of events based on specific AQL queries. This ensures you only extract the necessary data.

Usability: The Log Activity tab's interface, including the Test and Export functionality, makes it easy to use even for less technical users familiar with basic QRadar concepts.

CSV Format: CSV offers a readable, widely compatible format for data review outside of QRadar.

App Communication: QRadar apps often communicate with the core QRadar system using APIs or other internal communication channels.

Authorization: Authorized service tokens provide a secure mechanism for apps to authenticate these actions, ensuring proper access and data flow.

Offense chaining in IBM Security QRadar SIEM V7.5 is based on the offense index field specified in the rule. This means that if a rule is configured to use a specific field, such as the source IP address, as the offense index field, there will only be one offense for that specific source IP address while the offense is active. This mechanism is crucial for tracking and managing offenses efficiently within the system​​.

To identify events that were missed by the Custom Rule Engine (CRE) in IBM Security QRadar SIEM, an analyst would primarily look for "Log Only Events sent to a Data Store" and "High Level Category Unknown Events." Log Only Events are those that are stored directly without being processed by the CRE, indicating they might have been overlooked or not matched by any existing rules. High Level Category Unknown Events are those that do not fit into any of the predefined categories in QRadar, suggesting that the CRE might not have rules to handle or categorize these events properly. These types of events are crucial for analysts to review to ensure that no significant incidents are missed and to refine the rule set for better detection in the future.

Network Attacks: In security investigations, the Source IP typically represents the attacking device. It's the origin of the malicious activity.

Offense Data: QRadar offenses gather information about the incident, including the Source IP as a crucial property.

Time Series Charts in QRadar: Time series charts visualize how event or flow data changes over time. They are primarily used to spot trends and anomalies.

Interactivity: QRadar's time series charts allow zooming, panning, and hovering to see specific data points. This helps analysts drill down into patterns.

Search-Based: Time series charts always reflect the results of a search query. Changing the time range or refining the search alters the chart.

Inaccurate Statements

A. Static time series: QRadar's charts are not static; the interactivity is key.

C & D. Export Time: These focus on data export, which isn't directly related to the nature of time series charts themselves.

References

IBM QRadar Documentation - Time Series Charts: https://www.ibm.com/docs/en/qradar-common?topic=pulse-aggregating-data-create-time-series-chart

Event Details Page Overview: The Event Details page in QRadar provides in-depth information about each event that is logged. This includes various parameters that help in the analysis and investigation of security incidents.

Configured Parameters:

Event Processor UUID: Unique identifier for the event processor, generally used for internal tracking.

High Level Category: Represents the general category of the event, useful for quick identification and filtering.

Log Source Time: The timestamp indicating when the log was generated by the source.

Log Source Group: A grouping of log sources for organizational purposes.

Relevance of High Level Category: The High Level Category is a crucial parameter found in the Event Details page, as it provides a broad classification of the event type, aiding in quick understanding and categorization of events.

Reference Confirmation: According to IBM QRadar documentation, the High Level Category is prominently featured on the Event Details page, making it the correct answer.

References:

IBM QRadar documentation on event analysis and Event Details page layout.

Specificity: The question states that the addresses are specifically IPv6-formatted. Using the 'IPv6' type ensures precision in the reference set.

IP Matching by QRadar: QRadar's rule engine will properly match against IPv6 addresses when the reference set type is 'IPv6'.

Magnitude: The Magnitude metric in QRadar represents a calculated severity or importance score assigned to an offense. Here's how it helps:

Prioritization: Higher magnitude offenses often demand more urgent attention and investigation. This helps analysts focus their efforts.

Customization: Magnitude is influenced by factors like asset value, rule severity, and the offense's repetition. It reflects your environment's specific risk concerns.

Here's why "Am I Affected" is the most suitable answer among the given options:

Am I Affected (AIA): The "Am I Affected" feature on the IBM X-Force Exchange is designed specifically to help you determine if your systems have observed Indicators of Compromise (IOCs) related to a specific threat or campaign.

COVID-19 IOCs: If you have a set of IOCs (e.g., IP addresses, domain names, file hashes) associated with COVID-19-themed attacks, you can use the AIA feature to query QRadar and see if any were detected within your network.

Reasons Why Other Options Are Less Ideal:

TAXII Automatic Updates: This focuses on automatically pulling threat intelligence feeds into QRadar, not retrospective searches for past IOC presence.

STIX Bundle: A STIX bundle is a structured way to represent threat intelligence.expand_more It wouldn't directly tell you if those indicators have been seen in your QRadar data.

Threat Intelligence ATP: This likely refers to a broader threat intelligence platform, not a specific X-Force Exchange feature for checking QRadar data.

QRadar offers several chart types for visualizing security data on dashboards. Here's a breakdown of why the options are correct or incorrect:

Supported:

Bar Charts: Great for comparing discrete categories of data (e.g., top source IP addresses, offenses by severity).

Tables (Tabular Display Charts): Ideal for presenting detailed data in a structured, row-and-column format.

Unsupported or Partially Supported:

Line Charts: Line charts are supported in QRadar's Pulse app, which has a dedicated dashboard building interface. They might also be included with some custom content extensions.

Radar Charts: Not natively supported as a core visualization in QRadar dashboards.

Dashboard Data Refresh: Most widgets on QRadar dashboards typically refresh the displayed data every minute by default.

Customization: In some cases, you might be able to configure this refresh interval depending on the widget type.

Indexing: QRadar indexes certain fields to create a structured way to quickly locate matching data.

Search Optimization: Including indexed fields in queries allows QRadar to leverage pre-built indexes rather than scanning all data.

Filtering: A well-constructed search with indexed fields significantly narrows the dataset, speeding up operations.