Use Watchlists in Azure Sentinel

By Ashwin Venugopal -

 



Plan for Azure Sentinel Watchlists

Azure Sentinel watchlists are famous for collecting data from external data sources to promote the correlation with the events in your Azure Sentinel environment. Common scenarios for using watchlists includes:
  • Investigating threats and responding to incidents quickly with the rapid import of IP addresses, file hashes, and other data from CSV files. Once imported, you can use watchlist name- value pairs for joins and filters in alert rules, threat hunting, workbooks, notebooks, and general queries.

  • Importing business data as a watchlist. For example, import user lists with privileged system access, or terminated employees, and then use the watchlist to create allow as well as deny lists used to detect or prevent those users from logging in to the network.

  • Reducing alert fatigue. Create allow lists to suppress alerts from a group of users, such as users from authorized IP addresses that perform tasks that would normally trigger the alert, and prevent benign events from becoming alerts. 

  • Enriching event data. You can use watchlists to enrich your event data with name-value combinations derived from external sources. 

Creation and deletion of the  Watchlists can be done easily, but you can't update it. If you are working with more dynamic lists, you can use the KQL external data operators to create temporary virtual tables. 

Utilize Threat Intelligence in Azure Sentinel

Define threat intelligence

The information describing known existing or potential threats to systems and users are called as Cyber Threat Intelligence (CTI). Organizations always use CTI to provide essential context to unusual activity so that security personnel can quickly take action to protect their people and assets. Azure Sentinel allows you to use threat indicators to help in detecting malicious activities observed in your environment as well as offer context to security investigators to help inform response decisions. Threat Intelligence (TI) can be integrated into Azure Sentinel through the following activities:
  • Use data connectors to various TI platforms to import threat intelligence into Azure Sentinel.
  • View and manage the imported threat intelligence in Logs and the new Threat Intelligence area of Azure Sentinel. 
  • Use the built-in Analytics rule templates to generate security alerts and incidents using your imported threat intelligence.
  • Visualize critical information about your threat intelligence in Azure Sentinel with the Threat Intelligence workbook.
  • Perform threat hunting with your imported threat intelligence.   

Threat indicators are the data that can associate observations such as URLs, file hashes, or IP addresses with known threat activity such as phishing, botnets, or malware. As this form of threat intelligence can be applied to security products as well as automation on a large scale to protect and detect potential threats to an organization, it is often referred to as a tactical threat intelligence.





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