Tutorial / Cram Notes
The Microsoft Security Operations Analyst SC-200 certification exam assesses the candidates’ ability in several key areas, including the ability to query, analyze, and interpret data from different sources. One essential skillset involves utilizing the Advanced SIEM Information Model (ASIM) parsers within Microsoft Sentinel to extract valuable insights from security data effectively. ASIM play a crucial role in normalizing and enriching data, making it easier to query and analyze consistently across different data sources.
ASIM Parsers in Microsoft Sentinel
ASIM parsers are used to translate disparate log file formats from various sources into a standardized schema. By transforming diverse datasets into a common format, analysts can write more straightforward and consistent queries across their data sources. This also ensures that data from different systems can be compared and correlated, which is vital for identifying and responding to security threats.
ASIM simplifies the creation of analytics rules and improves the detection capabilities within Microsoft Sentinel. By using a standard schema, ASIM enables security analysts to write generic detections that work across various data sources, such as logs from different operating systems, applications, network appliances, and cloud services.
Querying with ASIM Parsers
To query data using ASIM parsers, you must first ensure that the corresponding data connectors and parsers are activated for the data types you want to analyze. Once the parsers are set, you can use Kusto Query Language (KQL), which is the querying language of Microsoft Sentinel, to write your queries.
Here’s an example of using KQL with ASIM parsers to query data:
Syslog
| where SyslogMessage contains “failed login attempt”
| parse SyslogMessage with * “user” UserName
| project TimeGenerated, Computer, UserName
In this query:
- We start by querying the Syslog table for entries containing the string “failed login attempt.”
- Next, we use the
parseoperator to extract the UserName from the SyslogMessage field. - Finally, we project the relevant fields like TimeGenerated, Computer, and UserName that give us clear insight into the failed login attempts.
Normalization with ASIM
Without normalization, working with data from various sources can be challenging due to the discrepancies in field names, types, and formats. ASIM parsers come into play by normalizing the data into a consistent schema, known as the ASIM schema.
Here’s a comparison showing data before and after applying ASIM normalization:
| Data Source | Original Field | Normalized Field (ASIM) |
|---|---|---|
| Windows Events | EventID | EventID |
| Syslog | MessageID | EventID |
| Firewall logs | Action | Activity |
This table shows how different fields from various sources are normalized into a standardized schema, allowing for easier comparison and analysis.
Extending ASIM Parsers
While ASIM provides a wide range of parsers, there are scenarios where you might want to extend or create custom parsers to handle unique log formats or to extract additional information.
To extend an ASIM parser, you could copy the original parser, modify the new parser according to your needs, and apply it to the corresponding data source. This process ensures that any custom data continues to align with the ASIM schema, keeping your security data normalized and consistent.
Benefits of Using ASIM in Microsoft Sentinel
By adopting ASIM parsers, analysts can reap several benefits, such as:
- Streamlined Analysis: Provides a unified view of the environment, making it easier to derive insights and detect anomalies.
- Enhanced Correlation: Simplifies the process of correlating events across different sources, crucial for identifying complex threats.
- Time Efficiency: Reduces the time needed to create and optimize queries, leading to quicker incident response and resolution times.
In conclusion, using ASIM parsers is an essential skill for candidates preparing for the SC-200 exam. It empowers analysts to efficiently query and analyze data within Microsoft Sentinel, leveraging normalized schemas to enhance security event detection, investigation, and response. Understanding and utilizing ASIM parsers can vastly improve the efficiency and effectiveness of an organization’s security operations center.
Practice Test with Explanation
True or False: ASIM parsers in Microsoft Sentinel are used to normalize data across different data sources before querying.
- 1) True
- 2) False
True
ASIM parsers normalize data from various sources into a common schema, making it easier to query and analyze data consistently in Microsoft Sentinel.
True or False: You must write custom parsers for each new data source you want to integrate with Microsoft Sentinel.
- 1) True
- 2) False
False
Microsoft Sentinel provides ASIM parsers for common data sources, and users can leverage these rather than writing custom parsers for many standard data types.
Which of the following statements is true regarding ASIM parsers?
- A) They are only compatible with Windows-based systems.
- B) They support a variety of log file types, including Syslog and CEF.
- C) They can only parse data in real-time and not from historical data.
B
ASIM parsers are designed to support various log file types and can be used for different operating systems, not just Windows. They can also parse both real-time and historical data.
True or False: ASIM parsers cannot be modified to fit specific use cases.
- 1) True
- 2) False
False
ASIM parsers can be customized to better fit organization-specific use cases or accommodate unique data sources.
What is the primary purpose of ASIM parsers in Microsoft Sentinel?
- A) To delete old logs automatically
- B) To normalize and unify data for easier querying and analysis
- C) To encrypt data for secure transmission
B
The primary purpose of ASIM parsers is to normalize and unify data from various sources, making it simpler to query and analyze within Microsoft Sentinel.
True or False: ASIM parsers can only be used with data connectors provided by Microsoft.
- 1) True
- 2) False
False
While ASIM parsers work seamlessly with Microsoft-provided data connectors, they can also be used with custom or third-party connectors as long as the data is brought into Sentinel in a compatible format.
How does ASIM help with cross-platform data analysis in Microsoft Sentinel?
- A) ASIM converts all data into a proprietary Microsoft format.
- B) ASIM does not support cross-platform data analysis.
- C) ASIM provides a common schema to represent data from different platforms.
C
ASIM provides a common schema that facilitates the analysis of data from multiple platforms within Microsoft Sentinel.
What is required to start using ASIM parsers with Microsoft Sentinel?
- A) Special hardware that supports ASIM parsing
- B) Knowledge of all source data formats to create mappings
- C) Data Connectors that bring relevant data into Sentinel
C
To use ASIM parsers with Microsoft Sentinel, you need data connectors that funnel relevant data into Sentinel. ASIM parsers will then normalize this data.
True or False: ASIM parsers in Microsoft Sentinel are optional and not necessary for querying data.
- 1) True
- 2) False
True
While ASIM parsers provide significant benefits in normalizing and querying data, they are optional, and users could technically perform queries without them.
What is one of the benefits of using ASIM parsers over traditional data normalization methods?
- A) ASIM parsers require manual data type definitions for each log source.
- B) ASIM parsers increase the amount of storage needed for logs.
- C) ASIM parsers facilitate faster and more efficient data analysis.
C
ASIM parsers streamline the data normalization process, resulting in the faster and more efficient analysis of logs.
True or False: ASIM parsers are automatically updated by Microsoft to support new log formats.
- 1) True
- 2) False
True
Microsoft regularly updates ASIM parsers to support new log formats and to ensure they stay current with evolving data source types.
Which feature of ASIM parsers greatly assists in threat detection and response efforts in Microsoft Sentinel?
- A) ASIM parsers can automatically respond to threats without human intervention.
- B) ASIM parsers normalize data, enhancing the effectiveness of analytics rules and machine learning models for threat detection.
- C) ASIM parsers prevent any unauthorized data from entering the Sentinel workspace.
B
By normalizing data, ASIM parsers enhance the functionality of analytics rules and machine learning models, which are critical for effective threat detection and response in Microsoft Sentinel.
Interview Questions
What is an Advanced SIEM Information Model (ASIM) parser?
An ASIM parser is a data normalization technique used in Microsoft Sentinel to transform incoming data into a common format.
What is the purpose of ASIM parsers?
The purpose of ASIM parsers is to normalize data from different sources and reduce the complexity of searching and analyzing data.
How do ASIM parsers work?
ASIM parsers work by identifying key data fields in incoming data, and then mapping those fields to a common set of field names, data types, and values.
What are the benefits of using ASIM parsers?
ASIM parsers can improve search performance, reduce false positives, and help detect and investigate security incidents more quickly.
How can ASIM parsers be customized?
ASIM parsers can be customized by creating or modifying parser configurations using Kusto Query Language (KQL) scripts.
What is a parser configuration?
A parser configuration is a KQL script that defines the mapping between the data fields in incoming data and the fields in the ASIM.
How are parser configurations created?
Parser configurations are created using Kusto Query Language (KQL) scripts that define the mapping between data fields and ASIM fields.
What is the ASIM schema?
The ASIM schema is a set of fields and data types that define the common format for data in Microsoft Sentinel.
How is the ASIM schema used?
The ASIM schema is used to map data fields from different sources to a common set of fields and data types in order to normalize the data for analysis.
What are some best practices for using ASIM parsers?
Best practices for using ASIM parsers include defining clear naming conventions for fields and values, testing parser configurations thoroughly, and regularly reviewing and updating parser configurations to ensure they remain effective.
Can anyone please explain how ASIM parsers can be used to improve threat detection in Microsoft Sentinel?
Thanks for this informative post!
Can somebody explain the difference between ASIM parsers and traditional KQL queries?
I appreciate the clarity of this blog post.
Is there any impact on performance when using ASIM parsers in Microsoft Sentinel?
This post could use some more real-world use cases.
Can ASIM parsers be used with custom log formats?
Very helpful, thank you!