C1000-162 Practice Exam Questions with Answers IBM Security QRadar SIEM V7.5 Analysis Certification

Understanding Scatter Charts in QRadar Pulse: QRadar Pulse is a visualization application used to create and view different types of charts for better data analysis and interpretation.

Types of Y-Axis:

Linear Axis: This type of axis displays data points at equal intervals. It's suitable for evenly distributed data and shows trends in a straightforward manner.

Logarithmic (Log) Axis: This axis type displays data on a logarithmic scale, which is useful for data that covers several orders of magnitude or for data that grows exponentially.

Selection for Scatter Charts: When creating scatter charts in QRadar Pulse, the application allows users to choose between linear and logarithmic (log) Y-axis types to best represent their data.

Reference Confirmation: According to IBM QRadar documentation, both linear and logarithmic Y-axis types are supported for scatter charts in the Pulse app, making them the correct answers.

References:

IBM QRadar documentation on Pulse app charting options confirms the availability of linear and logarithmic Y-axis types.

In IBM Security QRadar SIEM V7.5, to search for all events containing a specific keyword such as "access", an analyst should navigate to the "Log Activity" tab. This section of the QRadar interface is dedicated to viewing and analyzing log data collected from various sources. By running a quick search with the "access" keyword in the Log Activity tab, the analyst can filter out events that contain this term in any part of the log data. This functionality is crucial for identifying specific activities or incidents within the vast amounts of log data QRadar processes, allowing analysts to quickly hone in on relevant information for further investigation or action.

When defining the network hierarchy in QRadar, it is recommended to organize systems and networks by role or similar traffic patterns to differentiate network behavior effectively. Additionally, it is advised not to configure a network group with more than 15 objects to avoid difficulties in viewing detailed information for each object and to ensure efficient management of network groups??.

Events can be exported from the QRadar Log Activity tab in XML (Extensible Markup Language) or CSV (Comma-Separated Values) formats, providing flexibility in how data is extracted and used for further analysis outside of QRadar??.

Key-Value Mapping: You need to associate each patent ID (key) with multiple usernames (values).

Sets: The ability to store multiple values per key is a core feature of reference maps of sets.

Unique Keys: QRadar requires unique keys within reference sets collections.

The information displayed when pressing “Ctrl + Space” in the search field in the Log Activity tab in QRadar is not explicitly mentioned in the search results. However, in general, this shortcut is often used in various software and platforms to display a list of available commands, functions, or properties. In the context of QRadar, it’s likely that pressing “Ctrl + Space” in the search field would display a list of available AQL (Ariel Query Language) databases, functions, and fields (properties).

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??.

Adding indexed properties to QRadar can significantly improve the efficiency of searches by reducing the size of the data set required to locate matches for non-indexed search values. Indexing creates references to unique terms in the data and their locations, which means that the search engine can filter the data set by indexed properties first, eliminating irrelevant portions of the data set and thereby reducing the overall volume of data that needs to be searched??.

A "Flow Bias" Quick Search can be performed from the Network Activity tab in QRadar, providing insights into network flows and potential anomalies or biases in the traffic patterns??.

In the Dynamic Search window on the Admin tab of QRadar, the available data sources include "Assets" and "Offenses." These options allow administrators and analysts to construct queries based on asset information or offense data, enabling targeted searches and analyses tailored to specific security concerns within the organization??.

Here's why this is the correct statement:

Purpose of the Assets Tab: The Assets tab is QRadar's central repository for information about discovered assets on your network.expand_more Assets include network devices, servers, applications, and more.

Discovery Process: QRadar discovers assets by passively analyzing log and flow data, as well as through active scans if configured.

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.

The MITRE heat map in the Use Case Manager app within QRadar uses several factors to determine the colors displayed, among which the number of rules mapped to MITRE ATT&CK tactics and techniques and the level of mapping confidence are crucial. These factors help visualize the coverage and reliability of rule mappings against the comprehensive MITRE ATT&CK framework, aiding in the identification of potential gaps or areas for improvement in threat detection capabilities??.

Before configuring the QRadar Use Case Manager app, it is essential to ensure that the app has the necessary permissions to function correctly. This typically involves creating an authorized service token which provides the app with the permissions to access and manage the QRadar environment??.

Pulse Dashboards and JSON: The QRadar Pulse app uses JSON (JavaScript Object Notation) to represent dashboard configurations. Here's why:

Structured Data: JSON is ideal for representing hierarchical data like the layout, widgets, and queries contained within a Pulse dashboard.

Import/Export Mechanism: QRadar Pulse supports importing and exporting dashboards in JSON format to enable sharing.

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??.

QRadar supports different types of content extensions that can be downloaded from the IBM X-Force Exchange portal. Among the supported content extensions are "Custom Functions" and "Offenses." These extensions allow for enhanced functionality and customization within QRadar, providing users with the ability to tailor the system to specific security needs and requirements??.

In QRadar, when performing a search in the My Offenses or All Offenses tabs, valid values for the Offense Type field include "Any" and "Source IP". "Any" searches all offense sources, while "Source IP" allows for searching offenses with a specific source IP address??.

The magnitude rating of an offense in IBM Security QRadar SIEM is a measure of the relative importance of a particular offense. It is a weighted value calculated from several factors, including severity, relevance, and credibility . These parameters are used to assess the potential impact of an offense, taking into account its seriousness (severity), its applicability or significance to the protected environment (relevance), and the reliability of the source or the confidence in the accuracy of the data (credibility). This multifaceted approach ensures that offenses are prioritized in a manner that reflects both their potential impact and the confidence in the underlying data, enabling security analysts to focus on the most critical issues first.

Widget chart types - IBM Documentation

QRadar supports generating reports in various file formats, including PDF, HTML, XML, and XLS. These formats provide flexibility in how reports are viewed and shared, catering to different needs and preferences for report presentation and analysis??.

Here's why MaxMind updates are essential:

IP to Location Mapping: QRadar relies on a GeoIP database to translate IP addresses into geographical locations (countries, regions, cities, etc.).

MaxMind: A widely used provider of GeoIP databases. QRadar integrates with MaxMind to obtain this data.

Fresh Updates: GeoIP mapping can change over time. Regular updates ensure the accuracy of location-based rules.

Why Other Options Are Less Relevant

X-Force Exchange: Provides threat intelligence feeds, primarily focused on IOCs, not geographic mappings.

X-Force Exchange ATP Updates: Likely refers to threat intelligence updates but not specifically for geolocation data.

Watson: IBM's AI platform. While potentially related to analytics, it's not the primary mechanism for geolocation in QRadar.

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.

Identify a value from the event payload that will be used as the basis for this threat detection. You must first determine the specific piece of information within the log payload that signals the malware outbreak activity you want to detect.

Create a custom property to extract the value from the logs. QRadar needs a custom property to isolate this specific value from the raw log data in a structured way.

Ensure the custom property is optimized and enabled. Optimize the custom property's extraction method for accuracy and efficiency. Ensure it's enabled, so QRadar actively parses this data element.

Create and Configure a rule to create an offense that uses the custom property as the offense index field. Now that the custom property is ready, create a rule that references this property. Designate the custom property as the rule's offense index field to ensure offenses are correctly grouped based on the extracted malware indicator.

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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??.

On the Offenses tab within QRadar, the "Offense Type" column explains the cause of the offense. The offense type is determined by the rule that triggered the offense, and it dictates the kind of information displayed in the Offense Source Summary pane. This helps analysts understand the nature and origin of the offense, facilitating more effective investigation and response actions??.

In IBM Security QRadar SIEM, building blocks are utilized to categorize assets and server types into CIDR/IP ranges to either exclude or include entire asset categories in rule tests. The most suitable type of building block for this purpose is the "Host definition". This type of building block allows administrators to define groups of IP addresses, often in CIDR notation, to represent different parts of the network, such as specific servers, subnets, or entire network segments. By doing so, rules can be crafted to apply only to traffic involving these defined hosts, thereby including or excluding specific asset categories from rule tests based on their network location or role within the organization??.

Use Case Manager: This app is specifically designed for investigation and analysis of offenses within QRadar. It offers more focused tools for this task than general Reports.

Active Rules: This view within the Use Case Manager provides insights into rules that directly triggered offenses. This is essential for filtering down to our target rules.

Filtering:

Start Date: Allows you to limit the analysis timeframe to the "previous week" as specified in the question.

Closure Reason: Crucially, this lets you isolate offenses marked as "False Positive" or "Tuned" – the core of the question.

The magnitude rating of an offense in IBM Security QRadar SIEM V7.5 is calculated based on three key parameters: severity, relevance, and credibility. Severity indicates the level of threat, relevance determines the offense's impact on the network, and credibility reflects the integrity of the offense as determined by the credibility rating configured in the log source. This combination of factors helps prioritize offenses and guide analysts on which ones to investigate first??.

Event rules in QRadar test against incoming log source data processed in real time by the QRadar Event Processor. This real-time processing enables QRadar to analyze and respond to security events as they occur, enhancing the system's ability to detect and mitigate threats promptly??.

Event Details Page in QRadar: The event details page in QRadar provides comprehensive information about each event, including metadata, payload, and correlation details.

Checking Fully Matched Rules:

The event details page includes a section that lists all the rules that were fully matched for that specific event.

This information is crucial for analysts to understand why an event was flagged and how it contributes to the overall offense.

Navigating to Event Details:

To view the event details page, an analyst can click on the event from the offense details or directly from the event list.

Within the event details, the matched rules are typically listed under the "Rules" or "Correlation" section.

Reference Confirmation: According to IBM QRadar documentation, the event details page is the location where analysts can see which rules were fully matched for a specific event.

References:

IBM QRadar documentation on event investigation and details page layout confirms that fully matched rules are displayed on the event details page .

The logical operator != in an AQL (Ariel Query Language) query is used to compare two values and returns true if the values are unequal. This operator is a common element in various programming and query languages, and its purpose is consistent across these environments, including in IBM Security QRadar SIEM V7.5.

For instance, in an AQL query, if you are analyzing event or flow data and want to filter out records where a specific field, say username, does not equal a certain value, you could use the != operator in your query like so: SELECT * FROM events WHERE username != 'admin'. This query would return all records where the username field does not equal 'admin'.

The use of the != operator is crucial in data analysis and threat hunting within QRadar, as it allows security analysts to exclude certain data points and focus on the relevant data that might indicate security incidents or breaches.