Free Practice Questions for IBM C1000-162 Exam

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​​.

Understanding Flow Payload in QRadar: QRadar captures and analyzes network flow data, which includes payload information. However, due to storage and performance considerations, payload data may be truncated if it exceeds a certain size.

Default Payload Size: The default value size for flow payloads in QRadar is 256 bytes. When the payload exceeds this size, the remaining data is truncated, and only the first 256 bytes are stored and displayed for analysis.

Impact of Truncation: Truncated payloads may omit critical information, which can impact the depth of analysis. Analysts need to be aware of this limitation and may need to adjust settings or use additional tools for a complete payload view if necessary.

Reference Confirmation: According to IBM QRadar documentation, the default payload size that, when exceeded, leads to truncation is 256 bytes.

References:

IBM QRadar documentation on flow data analysis and payload size limitations confirms the default truncation threshold of 256 bytes .

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.

Custom Properties: QRadar allows you to extract custom properties from raw log and flow data, enriching your analysis capabilities.

Supported Expression Types:

Regex (Regular Expressions): Powerful patterns for extracting specific strings or values from textual data.

JSON (JavaScript Object Notation): Extracts values from structured JSON data within events and flows.

Unsupported Types:

XLS: Excel spreadsheet format. QRadar isn't designed to parse spreadsheets directly.

YAML: A data serialization language. QRadar's extraction is more focused on data within events and flows rather than standalone configuration files.

HTML: Markup language used for web pages. Event data is unlikely to be solely in HTML format.

References:

IBM QRadar Documentation - Custom Property Expression Types: https://www.ibm.com/docs/en/qradar-on-cloud?topic=expressions-configuring-custom-property-expression

Vulnerability Scans and Offenses: VA scanners frequently trigger alerts as their activity can resemble malicious behavior.

Host Definitions: This QRadar building block group helps define known hosts, including their attributes and roles on the network.

Adding to Definitions: Including the VA scanner's IP in the host definitions allows QRadar to recognize it and properly categorize its activity.

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​​.

Behavioral rule test parameters in QRadar SIEM are crucial for configuring how anomaly detection functions within rules. Here's a breakdown of each parameter:

Season: This is the most important parameter. It defines the historical time period used to establish a baseline of "normal" behavior. Consider the nature of the traffic you're monitoring when choosing a season:

Network traffic with human interaction: A season of 1 week might be appropriate.

Daily patterns: A season of 24 hours would be more suitable.

Current traffic level: Represents the current value of the property being monitored by the rule (e.g., number of login failures, bandwidth usage, etc.).

Predicted value: This is an estimation of what the traffic level "should" be, based on the established season and historical trends.

How the Parameters Work Together

Behavioral rules primarily identify deviations between the Current traffic level and the Predicted value within the context of the defined Season. Significant discrepancies can trigger alerts.

References

IBM Security QRadar Documentation - Anomaly Detection Rules: (https://www.ibm.com/docs/en/qradar-on-cloud?topic=rules-anomaly-detection ). Search for "behavioral rule test parameter options" within the relevant documentation for QRadar SIEM V7.5.

The Domain attribute governs who can view the value of a reference set data element, ensuring that only users with appropriate domain access or tenant assignments can view the data. This is essential for maintaining data visibility and access control within a multi-tenant QRadar environment​​.

Searchable Columns: In QRadar's "My Offenses" and "All Offenses" tabs, you can search by:

Source IPs: Filter offenses based on the originating IP address. Id: Search using the unique offense ID number.

Incorrect Options:

Impact, Relevance, Weight: These are offense attributes, but you often filter by them rather than directly searching within the column data.

References:

IBM QRadar Documentation - Searching for Offenses https://www.ibm.com/docs/en/qradar-on-cloud?topic=searches-searching-offenses-my-offenses-all-offenses-pages