Implementing A New Microsoft Sentinel Solution (part 4)

By Ashwin Venugopal -

z 






To read part 1, please click here
To read part 2, please click here
To read part 3, please click here






Deploying MMAs

Generally, MMA accumulates Windows Security, application, and system event logs along with the web server logs from Microsoft IIS and by deploying MMA on Linux will help in the collection of any syslog message or local logs that follows a consistent naming convention. In fact, any Linux agent installed with MMA can itself act as a syslog collector for the remote syslog log resources. 

Deploying Workbooks

Microsoft Sentinel workbooks offers various functions/applications like several visualization control, conditional formatting, several features of the analytical platform, etc. while it's also capable in retrieving data from multiple sources that might help in the complex integration of various Microsoft services, such as- Azure Log Analytics Workspace, Microsoft Graph, Azure Data Explorer, Azure Resource Manager, and whatnot. 

Deploying User & Entity Behavior Analytics (UEBA)

UEBA depicts the latest technologies of offered by SIEM solutions and generally rely on its machine learning abilities to keep track of the users and entities like hosts, IP addresses, etc., in order to detect as well as investigate any type deviations from the known pattern. Hence, UEBA proves helpful in collecting the various low fidelity signals to build a timeline of an event that can be further used in the better understanding as well as investigation of the entity behavior. 

Deploying Notebooks

Microsoft Sentinel Notebooks have proven very much helpful due to their advanced threat hunting abilities via the collected data as well as the processing capabilities available in many programming languages including but not limited to Python and C#/, .Net. 

Deploying Cyber Threat Intelligence (CTI) Functionality

CTI can be made available via various sources such as open-source data feeds, threat intelligence sharing communities, premium curated feeds, and your own security investigations. CTI when combined with your own data can offer valuable contextual information, that can majorly help in speeding-up the time used in detecting, identifying, and triaging malicious or anomalous activities. 

Deploying Alert Rules

The configuration of detection rules can be considered as the most important component of any Microsoft Sentinel deployments containing many built-in alert rules templates that can easily cover the whole array of a typical log source with continuous addition of new alert rules (that can be easily obtained via Microsoft Sentinel Community in which both the Microsoft as well as the third-party can publish new content). However, the proposed rules always go though community's review permitting only the valuable ones to be published in Microsoft Sentinel. 








To read part 1, please click here
To read part 2, please click here
To read part 3, please click here














































Comments

Post a Comment

Popular posts from this blog

Query, Visualize, & Monitor Data in Azure Sentinel

By Ashwin Venugopal -
Image
  Azure Sentinel Workbooks Several ready for use templates are provided by the Azure Sentinel that can be used to create your own workbook and then modify them as needed for Contoso. Most of the data connectors it uses to ingest data come with their own workbooks, but better insight can be obtained by simply looking into the data that is being ingested by using tables and visualizations, including bar and pie charts. You can also make your own workbook easily by using this data from the beginning instead of using the predefined templates. Workbook Page You can easily access the workbook page from the Azure Sentinel from the navigation pane which consists of the: Workbook header- You can add a new workbook and review the saved workbooks as well as templates that are available on the workbook page. Templates section- You can access existing workbook templates on the Templates tab. You can save some of the workbooks for quick access and they will appear on the My Workbooks tab.  From the
Read more

Planning for Implementing SAP Solutions on Azure (Part 2 of 5)

By Ashwin Venugopal -
Image
  To read part 1 please click  here To read part 3 please click  here To read part 4 please click  here To read part 5 please click  here Load Balancing The load balancer uses probe ports to determine as well as route the traffic to an active DBMS node, but of there's any failover then the most common SAP application architecture can automatically reconnect against the private virtual IP address without the need for the SAP application to reconfigure it, while the load balancer redirect the traffic against the private virtual IP address without any need for the SAP application to reconfigure. The loaf balancer also offers an option of DirectServerReturn which if configured, can help in directing the traffic from the DBMS VM to the SAP application layer directly to the application layer without routing through the load balancer. But, if it isn't configured, then the return traffic to the SAP application layer is routed through the load balancer. You can also use Azure Load Balan
Read more

Work with String Data Using KQL Statements

By Ashwin Venugopal -
Image
  Extract Data from Unstructured String Fields Unstructured string fields often contains the Security log data and requires parsing to extract data. There are multiple ways of pulling information from string fields in KQL and the two primary operators used are extract and parse.  Extract It gets a match for a regular expression from a text string. You can convert the extracted substring to the indicated type.  Arguments regex- A regular expression. captureGroup- A positive int constant indicating the capture group to extract. 0 stands for the entire match, 1 for the value matched by the first '('parenthesis')' in the regular expression, 2 or more for subsequent parenthesis.  text- A string to search. typeLiteral- An optional type literal. If provided, the extracted substring is converted to this type.  Returns If regex finds a match in text- the substring matched against the indicated capture group captureGroup, optionally converted to typeLiteral. If there's no mat
Read more