Free Azure Virtual Desktop Handbook: Security Fundamentals

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Mon, 04 Oct 2021 19:33:00 +0000

NIST: Securing the IIoT—Cybersecurity for Distributed Energy Resources: Draft SP 1800-32 Available for Comment


Securing the IIoT—Cybersecurity for Distributed Energy Resources: Draft SP 1800-32 Available for Comment

NIST’s National Cybersecurity Center of Excellence (NCCoE) has released a draft of NIST Special Publication (SP) 1800-32, Securing the Industrial Internet of Things: Cybersecurity for Distributed Energy Resources.

The use of small-scale distributed energy resources (DERs) is growing rapidly and transforming the power grid. In fact, a distribution utility may need to remotely communicate with thousands of DERs and other grid-edge devices—many of which are not owned by them.  Any attack that can deny, disrupt, or tamper with DER communications could prevent a utility from performing necessary control actions and could diminish grid resiliency.

In this draft cybersecurity practice guide, the NCCoE applies standards, best practices, and commercially available technology to protect the digital communication, data, and control of cyber-physical grid-edge devices. The guide demonstrates an example solution for monitoring and detecting unusual behavior of connected industrial internet of things (IIoT) devices and building a comprehensive audit trail of trusted IIoT data flows.

The public comment period is open through October 20, 2021. See the publication details for a copy of the document and instructions for submitting comments.

NOTE: A call for patent claims is included on page iv of this draft (Volume B). For additional information, see the Information Technology Laboratory (ITL) Patent Policy--Inclusion of Patents in ITL Publications.

Tue, 21 Sep 2021 19:34:00 +0000

NIST Pre-Draft Call for Comments | Incorporating Privacy in Awareness & Training

 Pre-Draft Call for Comments | Incorporating Privacy in Awareness & Training

To help organizations incorporate privacy into their security awareness and training regimes, NIST plans to revise SP 800-50, Building an Information Technology Security Awareness and Training Program. In the nearly two decades since SP 800-50 was published in 2003, cybersecurity awareness and training resources, methodologies, and requirements have evolved considerably—and new guidance to inform this work has come from Congress and the Office of Management and Budget.  

Prior to drafting the update, NIST is seeking public comment on several topics, including the potential consolidation of companion document SP 800-16, Information Technology Security Training Requirements: A Role- and Performance-Based Model, into the revised SP 800-50. The proposed title for SP 800-50 Revision 1 is Building a Cybersecurity and Privacy Awareness and Training Program. Comments are due by November 5, 2021

Your public comments will be used to influence future drafts, including an Initial Public Draft of the update which is scheduled to be released in early 2022 as SP 800-50 Revision 1.

Learn More

Tue, 21 Sep 2021 17:58:00 +0000

Attacking Active Directory as a Red Teamer or as an Attacker

Blog From Microsoft

Hi, my name is Raymond Roethof, and I am a Microsoft Security enthusiast with over fifteen years of experience within the Microsoft landscape. My focus has been Microsoft Security, and specifically with the last three years out of six as a Red Teamer. In this blog post, I will go through an attacker or Red Teamer's challenges when Microsoft Defender for Identity is in place

Many organizations go through a digital transformation by the increasing use of cloud services. Understanding the current state of the cloud service is essential as maintaining the state is a shared responsibility between the company and its cloud provider.

Many Red Teamers and attackers use the on-premises environment as a stepping stone to the cloud. So, a company must understand the comprehensive set of security controls and capabilities available in Microsoft Azure, Microsoft 365, and on-premises. Active Directory can be a source for lateral movement and an excellent initial attack vector due to the high-value information it holds.

Microsoft Defender for Identity is a cloud-based security solution that leverages your on-premises Active Directory signals to identify, detect, and investigate advanced threats, compromised identities, and malicious insider actions directed at your organization. Defender for Identity also protects Active Directory Federation Services (AD FS) in your environment by detecting advanced threats and providing visibility into authentication events generated by AD FS.

The default Active Directory authentication protocol is Kerberos, an authentication protocol based on tickets, and is known for being the target method of many attacks. Kerberos is an authentication protocol developed by MIT and adopted by Microsoft since Windows 2000. Kerberos can also be complicated and as a result, hard to secure.

This blog post will go through attacking Active Directory as a Red Teamer and having Defender for Identity in place to protect this high-value information. What do I have to consider before I make my next move? Let's find out how Defender for Identity makes my job so difficult.

Attack Kill Chain

As a Red Teamer or an attacker, you want to reach your goal as quickly as possible, preferably without noticing. The purpose and time it takes to perform the attack differs in every scenario. Attackers are mainly financially driven as Red Teamers have a specific pre-defined objective to reach.

Most of the attacks require multiple steps to reach their goal. Red Teamers or attackers use some form of an attack kill chain as a process.


(Figure 1 - an example of an attack kill chain process)


Note: With the digital transformation to the cloud and the complexity of most attacks, a one-size-fits-all kill chain is not feasible anymore, but the Cyber Attack Kill Chain is a good indication of how a Red Teamer or attacker performs an attack. The graphic shown above is more focused on compromising an endpoint, for example. 

 Reconnaissance of Active Directory

 Reconnaissance is a critical and consistent step in any kill chain. Most information found is likely used during an attack at a later stage. Information like server names, IP addresses, operating systems, forest architecture, trusts, service principal names (SPNs), groups and memberships, access control lists, and well-known security misconfigurations is probably part of every reconnaissance phase within Active Directory.

 The challenge as a Red Teamer (or an attacker - assume I'm referring to both throughout this blog) starts with Defender for Identity being enabled at the reconnaissance phase.

 A Red Teamer needs to have a valid set of credentials, a hash, or any form of authentication to communicate with Active Directory. Attacks like phishing e-mails can contain a malicious payload that runs under the user context. This way, a Red Teamer or attacker can perform an attack as an authenticated user. Without any authentication, a Red Teamer uses an attack like AS-Rep roasting and password sprays. If you are a Red Teamer or an attacker, Defender for Identity detects this kind of attack and alerts in almost real time.

 Lateral Movement Active Directory

 The ultimate objective for a Red Teamer is data. For most organizations, data is one of the most valuable assets. Getting access to all data at the initial entry is rare for a Red Teamer or attacker, so it is common to see lateral movement during an attack.

Let us say a Red Teamer gets a foothold, either remotely or on the network, within the environment without being noticed as an authenticated user. The next step would be to seek identities with higher privileges or an identity to access high-value assets, like data.

Attacks like Kerberoasting are also common since service accounts mainly have high privileges to services that contain high-value assets. Kerberoasting is also an attack that Defender for Identity detects. Defender for Identity also detects newer attacks like PetitPotam as well since version 2.158.14362.

Extended Detection and Response

With Extended Detection and Response (XDR), Microsoft delivers a new approach to provide intelligent, automated, and integrated security across domains to help defenders connect seemingly disparate alerts and get ahead of attackers. Due to signal sharing between Microsoft Defender for Endpoint and Defender for Identity, an indicator shows if the endpoint contains an alert within Defender for Endpoint. An analyst can isolate the endpoint within seconds, and as a Red Teamer, you will need to find another entry point to continue your journey. The analyst is also probably more alert and now monitoring the environment even closer as a result.



(Figure 2 - an illustration of an attacker navigating a minefield)


Every step we take next as a Red Teamer or an attacker is like walking in a minefield.


From on-premises to the cloud


Although many organizations go through digital transformation by the increasing their use of cloud services, attackers can use the on-premises environment as a stepping stone to the cloud. One of my blog posts describes creating a forged security token to authenticate to Azure AD using a private key from the AD FS server. Unfortunately for me, Defender for Identity now detects this method of attack as well:



(Figure 3 - A screenshot showing the alert status of an AD FS DKM key read with supporting evidence)

Fri, 17 Sep 2021 14:11:00 +0000

NIST: Machine Learning for Access Control Policy Verification: NISTIR 8360 Published


Machine Learning for Access Control Policy Verification: NISTIR 8360 Published

Access control policy verification ensures that there are no faults within the policy that leak or block access privileges. As a software test, access control policy verification relies on methods such as model proof, data structure, system simulation, and test oracle to verify that the policy logic functions as expected. However, these methods have capability and performance issues related to inaccuracy and complexity limited by applied technologies. For instance, model proof, test oracle, and data structure methods initially assume that the policy under verification is faultless unless the policy model cannot hold for test cases. Thus, the challenge of the method is to compose test cases that can comprehensively discover all faults. Alternatively, a system simulation method requires translating the policy to a simulated system. The translation between systems may be difficult or impractical to implement if the policy logic is complicated or the number of policy rules is large.

NISTIR 8360, Machine Learning for Access Control Policy Verification, proposes an efficient and straightforward method for access control policy verification by applying a classification algorithm of machine learning, which does not require comprehensive test cases, oracle, or system translation but rather checks the logic of policy rules directly, making it more efficient and feasible compared to traditional methods. Ultimately, three general applications are provided: enhancement of existing verification methods, verification of access control policies with numerical attributes, and policy enforcement that can be supported by the proposed machine learning policy verification method.

Read More

Fri, 17 Sep 2021 14:04:00 +0000

Become an Azure Sentinel Ninja: The complete level 400 training



thumbnail image 1 of blog post titled  	 	 	  	 	 	 				 		 			 				 						 							Become an Azure Sentinel Ninja: The complete level 400 training


This training program includes 16 modules. The post includes a presentation for each module, preferably recorded (when still not, we are working on the recording) and supporting information: relevant product documentation, blog posts, and other resources.

The modules listed below are split into five groups following the life cycle of a SOC:


Part 1: Overview

- Module 0: Other learning and support options

- Module 1: Get started with Azure Sentinel

- Module 2: How is Azure Sentinel used?


Part 2: Architecting & Deploying

- Module 3: Workspace and tenant architecture

- Module 4: Data collection

- Module 5: Log Management

- Module 6: Enrichment: TI, Watchlists, and more

- Module X: Migration

- Module Z: ASIM and Normalization


Part 3: Creating Content

- Module 7: The Kusto Query Language (KQL)

- Module 8: Analytics

- Module 9: SOAR

- Module 10: Workbooks, reporting, and visualization

- Module Y: Notebooks

- Module 11: Use cases and solutions


Part 4: Operating

- Module 12: A day in a SOC analyst's life, incident management, and investigation

- Module 13: Hunting

- Module 14: User and Entity Behavior Analytics (UEBA) 

- Module 15: Monitoring Azure Sentinel's health


Part 5: Advanced Topics

- Module 16: Extending and Integrating using Azure Sentinel APIs

- Module 17: Bring your own ML


Part 1: Overview


Module 0: Other learning and support options


The Ninja training is a level 400 training. If you don't want to go as deep or have a specific issue, other resources might be more suitable:


Think you're a true Sentinel Ninja? Take the knowledge check and find out. If you pass the 
knowledge check with a score of over 80% you can request a certificate to prove your ninja

1. Take the knowledge check here. 
2. If you score 80% or more in the knowledge check, request your participation certificate 
here. If you achieved less than 80%, please review the questions that you got it wrong, study
more and take the assessment again.


Module 1: Get started with Azure Sentinel


Short on time? Watch the Fall Ignite presentation
Already know? The Spring Ignite session focuses on what's new and an how to use demo
Get deeper? Watch the Webinar: MP4YouTube,Presentation


Microsoft Azure Sentinel is a scalable, cloud-native, security information event management (SIEM) and security orchestration automated response (SOAR) solution. Azure Sentinel delivers intelligent security analytics and threat intelligence across the enterprise, providing a single solution for alert detection, threat visibility, proactive hunting, and threat response (read more).


If you want to get an initial overview of Azure Sentinel's technical capabilities, the latest Ignite presentation is a good starting point. You might also find the Quick Start Guide to Azure Sentinel useful (requires registration). A more detailed overview, however somewhat dated, can be found in this webinar: MP4YouTube, Presentation.


Lastly, want to try it yourself? The Azure Sentinel All-In-One Accelerator  (blogYoutubeMP4deck) presents an easy way to get you started. To learn how to start yourself, review the onboarding documentation, or watch Insight's Sentinel setup and configuration video.


Learn from users

Thousands of organizations and service providers are using Azure Sentinel. As usual with security products, most do not go public about that. Still, there are some.


Learn from Analysts


Module 2: How is Azure Sentinel used?


Short on time? Read this presentation.


Many users use Azure Sentinel as their primary SIEM. Most of the modules in this course cover this use case. In this module, we present a few additional ways to use Azure Sentinel.


As part of the Microsoft Security stack

Use Sentinel, Azure Defender, Microsoft 365 Defender  in tandem to protect your Microsoft workloads, including Windows, Azure, and Office:


To monitor your multi-cloud workloads

The cloud is (still) new and often not monitored as extensively as on-prem workloads. Read this presentation to learn how Azure Sentinel can help you close the cloud monitoring gap across your clouds.


Side by side with your existing SIEM

Either for a transition period or a longer term, if you are using Azure Sentinel for your cloud workloads, you may be using Azure Sentinel alongside your existing SIEM. You might also be using both with a ticketing system such as Service Now. 


For more information on migrating from another SIEM to Azure Sentinel, watch the migration webinar: MP4YouTubeDeck.


There are three common scenarios for side by side deployment:

You can also send the alerts from Azure Sentinel to your 3rd party SIEM or ticketing system using the Graph Security API, which is simpler but would not enable sending additional data. 



Since it eliminates the setup cost and is location agnostics, Azure Sentinel is a popular choice for providing SIEM as a service. You can find a list of MISA (Microsoft Intelligent Security Association) member MSSPs using Azure Sentinel. Many other MSSPs, especially regional and smaller ones, use Azure Sentinel but are not MISA members.


To start your journey as an MSSP, you should read the Azure Sentinel Technical Playbooks for MSSPs. More information about MSSP support is included in the next module, cloud architecture and multi-tenant support.  


Part 2: Architecting & Deploying


While the previous section offers options to start using Azure Sentinel in a matter of minutes, before you start a production deployment, you need to plan. This section walks you through the areas that you need to consider when architecting your solution, as well as provides guidelines on how to implement your design:


Module 3: Workspace and tenant architecture


Short on time? Watch the Nic DiCola's Ignite presentation (first 11 Minutes)
Get Deeper? Watch the Webinar: MP4YouTubePresentation


An Azure Sentinel instance is called a workspace. The workspace is the same as a Log Analytics workspace and supports any Log Analytics capability. You can think of Sentinel as a solution that adds SIEM features on top of a Log Analytics workspace.


Multiple workspaces are often necessary and can act together as a single Azure Sentinel system. A special use case is providing service using Azure Sentinel, for example, by an MSSP (Managed Security Service Provider) or by a Global SOC in a large organization. 


To learn more about why use multiple workspaces and use them as one Azure Sentinel system, read Extend Azure Sentinel across workspaces and tenants or, if you prefer, the Webinar version: MP4YouTubePresentation.


There are a few specific areas that require your consideration when using multiple workspaces:



The Azure Sentinel Technical Playbook for MSSPs provides detailed guidelines for many of those topics, and is useful also for large organizations, not just to MSSPs.


Module 4: Data collection


Sept 2021 update: our latest webinar on data collection scenarios by Edi Lahav and Yaniv 
Shasha. YouTube, MP4, Deck

Short on time? Watch the Nic DiCola's Ignite presentation (Mid 11 Minutes)
Get Deeper? Watch the Webinar: YouTube, MP4Deck.


The foundation of a SIEM is collecting telemetry: events, alerts, and contextual enrichment information such as Threat Intelligence, vulnerability data, and asset information. You can find a list of sources you can connect here:


How you connect each source falls into several categories or source types. Each source type has a distinct setup effort but once deployed,  it serves all sources of that type. The Grand List specifies for each source what its type is. To learn more about those categories, watch the Webinar (includes Module 3): YouTubeMP4Deck.


The types are:









If your source is not available, you can create a custom connector. Custom connectors use the ingestion API and therefore are similar to direct sources. Custom connectors are most often implemented using Logic Apps, offering a codeless option, or Azure Functions.


Module 5: Log Management


While how many and which workspaces to use is the first architecture question to ask, there are additional log management architectural decisions:




Logs Security


Dedicated cluster


Module 6: Enrichment: TI, Watchlists, and more


One of the important functions of a SIEM is to apply contextual information to the event steam, enabling detection, alert prioritization, and incident investigation. Contextual information includes, for example, threat intelligence, IP intelligence, host and user information, and watchlists.


Azure Sentinel provides comprehensive tools to import, manage, and use threat intelligence. For other types of contextual information, Azure Sentinel provides Watchlists, as well as alternative solutions.

Threat Intelligence


Sept 2021 update: Sign up for the Explore the Power of Threat Intelligence in Azure Sentinel
webinar on Oct 25 here.

Short on time? watch the Ignite session (28 Minutes)
Get Deeper? Watch the Webinar: YouTubeMP4Presentation


Threat Intelligence is an important building block of a SIEM.


In Azure Sentinel, you can integrate threat intelligence (TI) using the built-in connectors from TAXII servers or through the Microsoft Graph Security API. Read more on how to in the documentation. Refer to the data collection modules for more information about importing Threat Intelligence. 


Once imported, Threat Intelligence is used extensively throughout Azure Sentinel and is weaved into the different modules. The following features focus on using Threat Intelligence:


Watchlists and other lookup mechanisms

To import and manage any type of contextual information, Azure Sentinel provides Watchlists, which enable you to upload data tables in CSV format and use them in your KQL queries. Read more about Watchlists in the documentation
In addition to Watchlists, you can also use the KQL externaldata operator, custom logs, and KQL functions to manage and query context information. Each one of the four methods has its pros and cons, and you can read more about the comparison between those options in the blog post "Implementing Lookups in Azure Sentinel." While each method is different, using the resulting information in your queries is similar enabling easy switching between them.
Read utilize Watchlists to Drive Efficiency During Azure Sentinel Investigations for ideas on using Watchlist outside of analytic rules.

Module X: Migration


Watch the Webinar: YouTubeMP4Presentation


In many (if not most) cases, you already have a SIEM and need to migrate to Azure Sentinel. While it may be a good time to start over and rethink your SIEM implementation, it makes sense to utilize some of the assets you already built in your current implementation. To start watch our webinar describing best practices for converting detection rules from Splunk, QRadar, and ArcSight to Azure Sentinel Rules: YouTubeMP4Presentationblog.


You might also be interested in some of the resources presented in the blog:


Module Z: ASIM and Normalization


Watch the Understanding Normalization in Azure Sentinel webinar: YouTubePresentation
Watch the Deep Dive into Azure Sentinel Normalizing Parsers and Normalized
Content webinar:
YouTube, MP3, Presentation

Sign up for the Turbocharging ASIM: Making Sure Normalization Helps Performance Rather Than
Impacting It webinar on Oct 6 here.


Working with various data types and tables together presents a challenge. You must become familiar with many different data types and schemas, write and use a unique set of analytics rules, workbooks, and hunting queries for each, even for those that share commonalities (for example, DNS servers). Correlation between the different data types necessary for investigation and hunting is also tricky.


The Azure Sentinel Information Model (ASIM) provides a seamless experience for handling various sources in uniform, normalized views. ASIM aligns with the Open-Source Security Events Metadata (OSSEM) common information model, promoting vendor agnostic, industry-wide normalization.


The current implementation is based on query time normalization using KQL functions. And includes the following:

  • Normalized schemas cover standard sets of predictable event types that are easy to work with and build unified capabilities. The schema defines which fields should represent an event, a normalized column naming convention, and a standard format for the field values.
  • Parsers map existing data to the normalized schemas. Parsers are implemented using KQL functions.
  • Content for each normalized schema includes analytics rules, workbooks, hunting queries, and additional content. This content works on any normalized data without the need to create source-specific content.


Using ASIM provides the following benefits:

  • Cross source detection: Normalized analytic rules work across sources, on-prem and cloud, now detecting attacks such as brute force or impossible travel across systems including Okta, AWS, and Azure.
  • Allows source agnostic content: the coverage of built-in as well as custom content using ASIM automatically expands to any source that supports ASIM, even if the source was added after the content was created. For example, process event analytics support any source that a customer may use to bring in the data, including Defender for Endpoint, Windows Events, and Sysmon. We are ready to add Sysmon for Linux and WEF once released!
  • Support for your custom sources in built-in analytics
  • Ease of use: once an analyst learns ASIM, writing queries is much simpler as the field names are always the same.


To learn more about ASIM:

  • Watch the overview webinar: YouTubeslides.
  • Watch the Deep Dive into Azure Sentinel Normalizing Parsers and Normalized Content webinar: YouTubeMP3Presentation.
  • Sign up for the Turbocharging ASIM: Making Sure Normalization Helps Performance Rather Than Impacting It webinar on Oct 6 here.
  • Read the documentation.


To Deploy ASIM:

  • Deploy the parsers from the folders starting with “ASim*” in the parsers folder on GitHub.
  • Activate analytic rules that use ASIM. Search for “normal” in the template gallery to find some of them. To get the full list use this GitHub search.


To Use ASIM:


Part 3: Creating Content


What is Azure Sentinel's content?


Azure Sentinel security value is a combination of its built-in capabilities such as UEBA, Machine Learning, or out-of-the-box analytics rules and your capability to create custom capabilities and customize built-in ones. Customized SIEM capabilities are often referred to as "content" and include analytic rules, hunting queries, workbooks, playbooks, and more.


In this section, we grouped the modules that help you learn how to create such content or modify built-in-content to your needs.  We start with KQL, the Lingua Franca of Azure Sentinel. The following modules discuss one of the content building blocks such as rules, playbooks, and workbooks. We wrap up by discussing use cases, which encompass elements of different types to address specific security goals such as threat detection, hunting, or governance. 


Module 7: KQL


Short on time? Start at the beginning and go as far as time allows.


Most Azure Sentinel capabilities use KQL or Kusto Query Language. When you search in your logs, write rules, create hunting queries, or design workbooks, you use KQL.  Note that the next section on writing rules explains how to use KQL in the specific context of SIEM rules.


We suggest you follow this Sentinel KQL journey:

  1. Pluralsight KQL course - the basics
  2. The Azure Sentinel KQL Lab: An interactive lab teaching KQL focusing on what you need for Azure Sentinel:
    1. Learning module (SC-200 part 4)
    2. DeckLab URL 
    3. Jupyter Notebooks version contributed by jjsantanna, which let you test the queries within the notebook.
    4. Learning webinar: YoutubeMP4;
    5. Reviewing lab solutions webinar: YouTubeMP4
  3. Pluralsight Advanced KQL course
  4. Optimizing Azure Sentinel KQL queries performance: YouTubeMP4Deck.
  5. Using ASIM in your KQL queries: YouTubeDeck


You might also find the following reference information useful as you learn KQL:


Module 8: Analytics


Writing Scheduled Analytics Rules


Short on time? watch the Webinar: MP4YouTubePresentation


Azure Sentinel enables you to use built-in rule templates, customize the templates for your environment, or create custom rules. The core of the rules is a KQL query; however, there is much more than that to configure in a rule.


To learn the procedure for creating rules, read the documentation. To learn how to write rules, i.e., what should go into a rule, focusing on KQL for rules, watch the webinar: MP4, YouTube, Presentation.


SIEM rules have specific patterns. Learn how to implement rules and write KQL for those patterns:  


To blog post "Blob and File Storage Investigations" provides a step by step example of writing a useful analytic rule.


Using built-in analytics


Short on time? watch the Machine Learning Webinar: MP4YouTubePresentation


Before embarking on your own rule writing, you should take advantage of the built-in analytics capabilities. Those do not require much from you, but it is worthwhile learning about them:


Module 9: Implementing SOAR


Sept 2021 update: sign up for the What’s New in Azure Sentinel Automation webinar on Oct 28 

Short on time? watch the Webinar:
YouTubeMP4, Deck


In modern SIEMs such as Azure Sentinel, SOAR (Security Orchestration, Automation, and Response) comprises the entire process from the moment an incident is triggered and until it is resolved. This process starts with an incident investigation and continues with an automated response. The blog post "How to use Azure Sentinel for Incident Response, Orchestration and Automation" provides an overview of common use cases for SOAR.


Automation rules are the starting point for Azure Sentinel automation. They provide a lightweight method for central automated handling of incidents, including suppression, false-positive handling, and automatic assignment.


To provide robust workflow based automation capabilities, automation rules use Logic App playbooks:

You can find dozens of useful Playbooks in the Playbooks folder on the Azure Sentinel GitHub, or read "A playbook using a watchlist to Inform a subscription owner about an alert" for a Playbook walkthrough.


While Azure Sentinel is a cloud-native SIEM, its automation capabilities do extend to on-prem environments, either using the Logic Apps on-prem gateway or using Azure Automation as described in "Automatically disable On-prem AD User using a Playbook triggered in Azure"


Module 10: Workbooks, reporting, and visualization


Short on time? Watch the Webinar: YouTubeMP4Deck




As the nerve center of your SOC, you need Azure Sentinel to visualize the information it collects and produces. Use workbooks to visualize data in Azure Sentinel.


Workbooks can be interactive and enable much more than just charting. With Workbooks, you can create apps or extension modules for Azure Sentinel to complement built-in functionality. We also use workbooks to extend the features of Azure Sentinel. Few examples of such apps you can both use and learn from are:

You can find dozens of workbooks in the Workbooks folder in the Azure Sentinel GitHub. Some of those are available in the Azure Sentinel workbooks gallery and some are not. 


Reporting and other visualization options


Workbooks can serve for reporting. For more advanced reporting capabilities such as reports scheduling and distribution or pivot tables, you might want to use:


Module Y: Notebooks


Short on time? Watch the short introduction video 
Get Deeper? Watch the Webinar: YouTubeMP4Presentation


Jupyter notebooks are fully integrated with Azure Sentinel. While usually considered an important tool in the hunter's tool chest and discussed the webinars in the hunting section below, their value is much broader. Notebooks can serve for advanced visualization, an investigation guide, and for sophisticated automation.


To understand them better, watch the Introduction to notebooks video. Get started using the Notebooks webinar (YouTubeMP4Presentation) or by reading the documentation.


An important part of the integration is implemented by MSTICPY, a Python library developed by our research team for use with Jupyter notebooks that adds Azure Sentinel interfaces and sophisticated security capabilities to your notebooks.


Module 11: Use cases and solutions


Sept 21 update: sign up for the Create Your Own Azure Sentinel Solutions webinar on Nov 16 

Short on time? watch the "Tackling Identity" Webinar: YouTubeMP4Deck


Using connectors, rules, playbooks, and workbooks enables you to implement use cases: the SIEM term for a content pack intended to detect and respond to a threat. You can deploy Sentinel built-in use cases by activating the suggested rules when connecting each Connector. A solution is a group of use cases addressing a specific threat domain.


The Webinar "Tackling Identity" (YouTubeMP4Presentation) explains what a use case is, how to approach its design, and presents several use cases that collectively address identity threats.


Another very relevant solution area is protecting remote work. Watch our ignite session on protection remote work, and read more on the specific use cases:


And lastly, focusing on recent attacks, learn how to monitor the software supply chain with Azure Sentinel.


Azure Sentinel solutions provide in-product discoverability, single-step deployment, and enablement of end-to-end product, domain, and/or vertical scenarios in Azure Sentinel. Read more about them here, and sign up for the upcoming webinar on Nov 16 on how to create solutions here.



Part 4: Operating


Module 12: Handling incidents


Sept 21 update: sign up for the Decrease Your SOC’s MTTR (Mean Time to Respond) by Integrating 
Azure Sentinel with Microsoft Teams webinar on Nov 10 here.

Short on time? Watch the "day in a life" Webinar: YouTubeMP4Deck


After building your SOC, you need to start using it. The "day in a SOC analyst life" webinar (YouTubeMP4Presentation) walks you through using Azure Sentinel in the SOC to triage, investigate and respond to incidents.


Integrating with Microsoft Teams directly from Azure Sentinel enables your teams to collaborate seamlessly across the organization, and with external stakeholders. Sign up for the Decrease Your SOC’s MTTR (Mean Time to Respond) by Integrating Azure Sentinel with Microsoft Teams webinar on Nov 10 here.


You might also want to read the documentation article on incident investigation. As part of the investigation, you will also use the entity pages to get more information about entities related to your incident or identified as part of your investigation.


Incident investigation in Azure Sentinel extends beyond the core incident investigation functionality. We can build additional investigation tools using Workbooks and Notebooks (the latter are discussed later, under hunting). You can also build additional investigation tools or modify ours to your specific needs. Examples include: 


Module 13: Hunting


Short on time? watch the Webinar: YouTubeMP4Deck
(Note that the Webinar starts with an update on new features, to learn about hunting, start at slide 12. The YouTube 
link is already set to start there)


While most of the discussion so far focused on detection and incident management, hunting is another important use case for Azure Sentinel. Hunting is a proactive search for threats rather than a reactive response to alerts. 


The hunting dashboard was recently refreshed in July 2021 and shows all the queries written by Microsoft's team of security analysts and any extra queries that you have created or modified. Each query provides a description of what it hunts for, and what kind of data it runs on. These templates are grouped by their various tactics - the icons on the right categorize the type of threat, such as initial access, persistence, and exfiltration. Read more about it here.


To understand more about what hunting is and how Azure Sentinel supports it, Watch the hunting intro Webinar (YouTubeMP4Deck). Note that the Webinar starts with an update on new features. To learn about hunting, start at slide 12. The YouTube link is already set to start there.


While the intro webinar focuses on tools, hunting is all about security. Our security research team webinar on hunting (MP4YouTubePresentation) focuses on how to actually hunt. The follow-up AWS Threat Hunting using Sentinel Webinar (MP4YouTubePresentation) really drives the point by showing an end-to-end hunting scenario on a high-value target environment. Lastly, you can learn how to do SolarWinds Post-Compromise Hunting with Azure Sentinel and WebShell hunting motivated by the latest recent vulnerabilities in on-premises Microsoft Exchange servers.


Module 14: User and Entity Behavior Analytics (UEBA)


Short on time? Watch the Webinar: MP4YouTubeDeck


Azure Sentinel newly introduced User and Entity Behavior Analytics (UEBA) module enables you to identify and investigate threats inside your organization and their potential impact - whether a compromised entity or a malicious insider.


Learn more about UEBA in the UEBA Webinar (MP4YouTubeDeck) and read about using UEBA for investigations in your SOC. 


Module 15: Monitoring Azure Sentinel's health


Short on time? watch the videos on monitoring connectors, 
security operations health or workspace audit.


Part of operating a SIEM is making sure it works smoothly and an evolving area in Azure Sentinel. Use the following to monitor Azure Sentinel's health:



Part 5: Advanced Topics


Module 16: Extending and Integrating using Azure Sentinel APIs


Short on time? watch the video (5 minutes)
Get deeper? Watch the Webinar: MP4YouTubePresentation


As a cloud-native SIEM, Azure Sentinel is an API first system. Every feature can be configured and used through an API, enabling easy integration with other systems and extending Sentinel with your own code. If API sounds intimidating to you, don't worry; whatever is available using the API is also available using PowerShell.


To learn more about Azure Sentinel APIs, watch the short introductory video and blog post. To get the details, watch the deep dive Webinar (MP4YouTubePresentation) and read the blog post  Extending Azure Sentinel: APIs, Integration, and management automation.


Module 17: Bring your own ML


Short on time? watch the video


Azure Sentinel provides a great platform for implementing your own Machine Learning algorithms. We call it Bring Your Own ML or BYOML for short. Obviously, this is intended for advanced users. If you are looking for built-in behavioral analytics, use our ML Analytic rules, UEBA module, or write your own behavioral analytics KQL based analytics rules.


To start with bringing your own ML to Azure Sentinel, watch the video, and read the blog post. You might also want to refer to the BYOML documentation

Wed, 08 Sep 2021 19:42:00 +0000

NOW Open for Comment | NIST’s Draft Ransomware Risk Management Profile

 In an ongoing effort to provide practical and actionable guidance to help organizations manage growing cybersecurity risks, NIST has released a draft ransomware risk management profile. The Cybersecurity Framework Profile for Ransomware Risk Management, Draft NISTIR 8374, is now open for comment through October 8, 2021.

The draft profile, prepared by the National Cybersecurity Center of Excellence (NCCoE), identifies security objectives from the NIST Cybersecurity Framework that can help prevent, respond to, and recover from ransomware events. It can be used as a guide to managing risk—including helping gauge an organization’s readiness to mitigate ransomware threats and react to potential impacts. The profile addresses issues that were raised in public comments on a preliminary draft released in June.

Read More

Wed, 08 Sep 2021 19:40:00 +0000

New York Metro Joint Cyber Security Conference & Workshop

 Registration is OPEN for the 8th annual New York Metro Joint Cyber Security Conference & Workshop (Oct. 14/15). Find out more at

DAY 1 OCT 14, 2021 Conference Agenda 

DAY 2 OCT 14, 2021 Workshop

Wed, 08 Sep 2021 19:37:00 +0000

New Microsoft Security and Compliance blog: How to Gain More from your Connection to an OT Network

How to Gain More from your Connection to an OT Network

One of the most productive and non-intrusive tools in the Cyber Security Engineer’s bag is passive Network Traffic Analysis (NTA).  Providing network maps, inventory, and firmware information among other benefits provides insights that are not generally known any other way.  Manual inventory collection methods are error-prone and expose this information to interception over corporate email networks, shared file folders, etc.  But how do we implement this kind of system without causing any bumps in the road for real-time processes?  What are the risks?  Which methods are best?  The best sensor does no good unconnected and is of little value connected in the wrong part of the network. 

 To discuss this, I will use a diagram that was developed for my last blog post Designing a Robust Defense for Operational Technology Using Azure Defender for IoT (  This diagram (below) shows an example OT network monitored by Azure Defender for IoT. Defender for IoT is an agentless passive Network Traffic Analysis tool with strong roots in Operational Technology, now expanding to IoT. Defender for IoT discovers OT/IoT devices, identifies vulnerabilities, and provides continuous OT/IoT-aware monitoring of network traffic.  The recommended locations for Azure Defender for IoT  (AD4IoT) are shown in red color.  Why have these locations been chosen?  To explain this, we will break this network into pieces and address these issues for each type of traffic.




 Starting with the lower portion of this sketch, let’s look at traffic flows around the PLCs. 



  1. The first arrow shows traffic between a PLC and its ethernet-connected Input/Output (I/O) modules.  This traffic utilizes simplistic protocols and is very structured and periodic.  It can be leveraged as a threat to the overall OT system and is more vulnerable when I/O is remote from the PLCs in unsecured areas.  Malicious applications could perform inappropriate control actions and/or falsify data.  Firmware problems in I/O modules often go unpatched unless some form of undesirable behavior is experienced. In certain families of PLCs or controllers, the Defender for IoT can provide data on firmware levels and types of I/O modules if this data is requested by an HMI or historian. 

 The mechanism to monitor this traffic is to span switches used in the I/O subsystem as shown here.  If they are unmanaged switches, taps may be located at the connection to the PLC or controller.

 2. The second arrow identifies traffic from Variable Frequency Drives or similar equipment often interfaced with the PLCs or Controllers.  This communication may be Modbus, Rockwell Protocols, or CIP.  Equipment could be damaged or destroyed by inappropriate commands sent to such devices.  Good engineering practice would put bounds of reasonability around all potential setpoints, but this may not be the case.  These protocols are well understood and in the public domain.  A man-in-the-middle attack could affect this type of equipment.  Monitoring these communications can identify inappropriate function calls, program or firmware changes, and parameter updates. As above, switch span or taps are the mechanisms to monitor this traffic.

 3. Custom engineered systems may utilize well-known, open OT protocols such as Modbus, OPC, or others.  This traffic should be monitored even if it is not fully understood as the behavior patterns should be very predictable.  It is common for these systems to utilize unusual functions and atypical ranges for data.  This is the result of a developer reading a protocol spec with no actual field experience with the protocol.  Custom alerts can be configured and tuned based on the nature of the data.  Since such systems are engineered to order for a specific purpose, the damage could have long-term implications on plant production.

 4. Traffic crossing OT Access-level switches should always be monitored.  This is the primary point at which PLCs or controllers communicate with HMIs, engineering stations, and sometimes historians.  The problem here is that these switches carry the actual OT control traffic.  Any action that could compromise this traffic affects the reliability of the OT system.  Many switches at the I/O and access layers may be unmanaged devices.  By unmanaged, I mean that they are not configurable and therefore cannot support a SPAN (or mirror) session. 

 Unmanaged switches is not an insurmountable hurdle.  Two possible paths may be followed from this point.  The least intrusive is to install network taps.  The security engineer should consult with the OT engineer on the most valuable locations for taps.  Since a stand-alone tap monitors only one data stream, the most valuable assets (compromise targets) should be monitored. These would normally be at least the engineering station, historian and/or alarms server (if appropriate), and HMIs, particularly those with engineering tools installed.  If it is necessary to monitor all traffic, a tap aggregator may be used.

Another approach would be to replace the unmanaged switches with managed switches.  This may sound daunting but usually is not.  Most managed switches are configured to “wake up” in a basic mode which approximates an unmanaged switch.  So replacement, while requiring a system shutdown, can be accomplished rather quickly and have the system up and functioning again.  Once this is done, the configuration can be added to provide basic security and copy traffic to a SPAN or mirror port.  Make sure these configurations are saved as most switches make changes to operating memory which is not stored on power reset.  It is generally recommended to discuss this change with your OT support personnel and/or OEM service engineers.  They probably have some standard switch configurations that they apply when a customer requests managed switches.  Additionally, they should be able to provide you with approximate bus speeds needed to support OT traffic with mirroring.

What are the risks? In the case of switch SPAN (SwitchPort ANalyzer), or mirror sessions, the only concern of serious significance is the current traffic level on the switch.  If a SPAN session is added to a heavily loaded switch, the SPAN may drop packets because the SPAN session is a lower priority than actual switching traffic. This could mean that some packets might slip through unmonitored.  However, it does not affect the normal functioning of the switch for ICS traffic.  Some switches, if they are greatly overloaded can revert to ‘flood mode’ in which they act as a network hub.  This situation is extremely rare.  If switch SPANning is chosen as a method, it is wise to monitor network traffic on the switch prior to adding the session.  Assume that a full switch span will double the switch backbone traffic. 

 If network taps are installed, the risks are insignificant.  Passive taps should of course be chosen.  Passive means that the tap continues to pass control traffic even if it loses power.  Passive taps are simply inserted in-line with the existing traffic, see sketch below.  Installation needs to be coordinated with OT engineers to limit the impact on operating processes. 

 Network Tap.jpg

 Next, we will discuss special equipment including analysis devices and robotics.  This portion of the overall diagram is shown below.  



Network traffic to analyzers typically looks like normal PC traffic using common IT protocols.  Most analyzers have some form of controller that is designed for a specific function.  Sometimes the PC is the controller, utilizing specialized I/O boards included in the machine. Some analyzers or groups of analyzers may be managed by mini computers.   In any case, from a network security perspective, these devices appear on the network as computers, not analyzers per se.  Patching of these customized machines often lags behind the upgrade strategies used for standard IT equipment.  Upgrades to analysis systems must be approved by, and often be implemented by the OEMs which may be expensive and involve downtime. Because of infrequent patching and/or OS upgrades, this equipment can become a security liability on a lab network. Ideally, lab equipment should be separated either physically onto separate networks or via VLANs, but such changes may require extensive planning and testing and still can be disruptive to ongoing lab processes.

Most major medical laboratories utilize either a LIMS (Laboratory Information Management System) or a middleware server to collect analytics data from these devices and forward that data to a patient information database managed either locally or in the cloud (see sketch below).  Hence, the traffic to/from the analyzer will be most easily recognized by the ultimate destination at the middleware or LIMS.  Since these potentially vulnerable machines may process interactions with users on the lab network for input data or maintenance functions, they should be monitored more closely than fully patched IT machines.  This presents a challenge to lab IT managers who may want to gain a handle on this type of OT equipment in their network but may not have good inventory information. 

Since medical testing facilities utilize normal switched networks, monitoring should be installed at an appropriate location to ‘see’ all the traffic from analyzers to the middleware or LIMS server.  This could be either core or distribution level switches depending on the network design.  Standard SPAN or mirror traffic can be used.

Dual-homed machines present special security challenges since they could be converted to active routers by malware.  It is common for expensive lab or analysis equipment to be leased.  OEM terms and conditions specify how this equipment may be used and what service it requires to achieve contracted performance.  This is often monitored via a ‘secure’ datalink to the manufacturer’s support site.  These may or may not be bi-directional.  These links are generally firewalled, either by the OEM, by the customer or by both.  Bi-directional links are inherently a threat.  Remote access to a computer on the lab network can put much more than that computer in jeopardy. 




In robotic applications, the primary issue is the speed of response.  The control systems are complex, utilizing high-level programming toolsets.  The low-level communication may not utilize standard ethernet framing.  Robot protocols vary widely and include Ethernet/IP, DeviceNet, Profibus-DP, Profinet, CC-Link, and EtherCat protocols.  Physical media may be Cat5/6, but RG-6 coaxial, twisted pair, RS-485, and fiber are also used.  Monitoring the low-level communication between controllers and robots requires careful coordination with the equipment designer and should not be attempted casually.  Network monitoring should utilize taps. Switch SPAN, or mirroring is not recommended. 

 As described above, most industrial robots are programmed using a computer workstation.  Downloading and selection of programs may be manual or automated using standard network protocols. So, monitoring should focus on the programming workstations and the source of robot program selections.  Robot program file downloads may be transferred from a central server.  These could occur over SFTP, FTP, SMB, or other methods. 

 Finally, we would like to address the OT interface to the business (Enterprise) network.  This can be a gateway for potential threats to OT systems.  Some vulnerabilities that may be unsuccessful in the IT network space may cause severe problems in the OT space because the machines may not be patched.  Out of date and unsupported operating systems may be in use.  As a result, traffic that enters from the Enterprise network and ultimately reaches the OT network should be monitored. 

 Generally, good practice prevents any direct traversal of the DMZ.  For instance, remote desktop sessions should be hosted by a RAS server in the DMZ which is then used to open a remote desktop session into an OT machine with different credentials. Elaborate credential systems with short password lives attempt to increase the challenge for attackers attempting to gain control.  Well designed implementations keep all machines in the DMZ patched up-to-date which should limit the effect of known vulnerabilities. 

 Zero day vulnerabilities will always be a threat prior to discovery.  So, monitoring sessions entering the DMZ from the Enterprise and those leaving the DMZ for the OT network are an important part of a security design.  Similarly, monitoring traffic from the OT network to a Historian server and Enterprise connections to that same server could uncover issues.  Since these sessions are often encrypted, efforts should focus on the legitimacy of the Enterprise hosts, times of access, data rates, and other indicators to validate these externally generated sessions.

 The DMZ is also used as a connection point for a variety of other facility systems such as IP phones; perimeter security systems; weather stations; contracted supply systems like water purification, compressed air supply and the like; wireless devices; etc.  In most cases, these various systems are assigned separate VLANs and subnets.  By monitoring all the VLANS in this zone, suspicious traffic can be identified and managed.  Traffic originating from any of these devices to the ICS network should not normally exist. 

Subnet-to-subnet traffic could be cause for concern.  This is another area where Defender for IoT can help.  By mapping the assets, assigning them to VLANs, subnets, and user assigned subsystems, communication between the various device groups can be easily seen greatly aiding efforts to perform or monitor network segregation.  

 The visual network map produced by Defender for IoT in conjunction with the filtering capabilities on the map make it easy to identify interconnections between various plant control systems. Having a powerful visual of group-to-group communication makes the effort of segmentation much easier.  This process is a long and tedious one using arp tables on switches.  Also, if this effort is underway, the map will show areas that may have been overlooked.

TRITON asset map 1.png


 Well-engineered connections to ICS networks can yield valuable results, including accurate inventories, network maps, and improved security with no risk to the reliability of the underlying OT systems.  This information can be combined, in Azure Sentinel or other SIEM/SOAR solutions, with agent-based Defender for endpoint data to produce a complete picture of OT networks.  Custom-designed playbooks can assist your analysts in responding to OT or IoT issues.  

Teamwork between OT engineers and IT security personnel can yield benefits for both groups while presenting a more challenging landscape to potential intruders.


Wed, 18 Aug 2021 23:01:00 +0000

New Azure Sentinel blog: What's new: Watchlists templates are now in public preview!

As we know, each organization is unique and have different use cases and scenarios in mind when it come to security operations. Nevertheless we've identified several use cases that are common across many SOC teams.

Azure Sentinel now provides built-in watchlist templates, which you can customize for your environment and use during investigations.

After those watchlists are populated with data, you can correlate that data with analytics rules, view it in the entity pages and investigation graphs as insights, create custom uses such as to track VIP or sensitive users, and more.

Watchlist templates currently include:


Watchlists templates insights in entity pages

Watchlists templates insights in entity pages


We've created the watchlists templates schemas to be super easy and extensible, in order for you to populate it with the relevant data. more information about using the watchlists templates can be found here.


What’s next?


Beside surfacing the watchlists templates data inside the entity pages, we're working on embedding this information in the UEBA anomalies, and the entity risk score which is planned next. Understanding if a user is a VIP/Terminated or an asset is an HVA is important to provide both context and security value for the analyst while investigating.


Wed, 18 Aug 2021 22:55:00 +0000