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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.

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​​.

Parsing Failure: A JSON parser error implies QRadar couldn't correctly extract structured data from the raw log messages created by the custom extension.

Fallback - CRE: QRadar defaults to storing unparseable events as CRE, preserving the raw log message but losing structured fields.

Troubleshooting: CRE events indicate the need to fix the log source extension's JSON parsing.

Understanding Offense Parameters in QRadar: In IBM QRadar, offenses are evaluated and prioritized based on several parameters that determine the significance and potential impact of the security incident.

Key Parameters:

Relevance: Indicates how relevant the event is to the organization's environment.

Severity: Represents the potential damage or impact the event could have on the system.

Credibility: Reflects the likelihood that the event represents a true security incident.

Magnitude Rating Calculation: The magnitude rating is a composite score that is calculated using the relevance, severity, and credibility of an offense. This rating helps security analysts prioritize incidents based on their potential threat level.

Reference Confirmation: According to IBM QRadar documentation, the magnitude rating is the parameter that is derived from the relevance, severity, and credibility of an offense.

References:

IBM QRadar documentation on offense management and parameters confirms the calculation of the magnitude rating based on relevance, severity, and credibility .

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.

Here's why this is the most effective approach:

False Positive Reduction: The goal is to stop legitimate traffic from triggering offenses. This requires fine-tuning the rules generating those offenses.

Building Blocks: Rules are housed within building blocks in QRadar's hierarchical rule structure. The Custom Rules Editor is the tool to modify them.

Event-Based Tuning: The optimal approach is to target the specific event that's causing the false positives, making the solution more precise.

Understanding Reference Data Collections in QRadar: In IBM QRadar, reference data collections are used to store data that can be reused across various rules, searches, and reports. Each type of reference data collection has a specific use case and structure.

Types of Reference Data Collections:

Reference Map: Stores key-value pairs where each key is unique and maps to a specific value.

Reference List: Stores a list of values without any keys.

Reference Table: Stores multiple key-value pairs where each key can have multiple values.

Reference Set: Stores a set of unique values without any keys.

Use Case for Reference Map: When you need to correlate a unique key to a specific value, a reference map is the appropriate data structure. It allows for efficient lookups and associations between keys and their corresponding values.

Reference Confirmation: According to IBM QRadar documentation, a reference map is explicitly designed to correlate unique keys to values, making it the correct choice for such requirements.

References:

IBM QRadar documentation on reference data collections confirms the use of a reference map for correlating unique keys to values.

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

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"​​.