Azure AD Identity Protection (part 2 of 3)

By Ashwin Venugopal -

 




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




Detect Vulnerabilities & Risk Events

Vulnerability is defined as a weakness which can be exploited by a threat actor i.e. an attacker to perform unauthorized actions within a computer system. The vulnerabilities reported by the Azure Identity Protection are as follows:
  • Multi-factor Authentication Registration Not Configured- As the name suggests, this vulnerability affects the deployment of Azure Multi-factor Authentication in your organization which can readily provide strong authentication throughout the range of easy verification options like phone call, text message, mobile app notification, verification code, and third-party OATH tokens. It is recommended for user sign-ins and plays a key-role in risk-based conditional access policies available through Azure Identity Protection.

  • Unmanaged Cloud Apps- It allows you to easily identify unmanaged cloud apps in your organization as nowadays IT departments cannot keep track of all the cloud applications that users are using to complete their work which may lead to unauthorized access to corporate data, possible data leakage, and other security risks. It is recommended to deploy Cloud App Discovery to discover unmanaged cloud applications and to manage them with the help of Azure AD.

  • Security Alerts from Privileged Identity Management- Here you can discover as well as resolve alerts about privileged identities in your organization as privilege users may lead to increase in the attack surface of the organization. It is recommended to use Azure AD Privileged Identity Management to manage, control, and monitor privileged identities as well as their access to resources in Azure AD and the other Microsoft online services like Office 365 or Microsoft Intune.  

Azure AD Risk Events

Azure AD can easily detect suspicious actions related to an organization's user accounts with the help of its adaptive machine learning algorithms and heuristics. It can detect following types of risk events:
  • Users with Leaked Credentials- The Microsoft's Leaked Credentials Service can acquire username/password pairs by monitoring public as well as dark web sites and working with- Researchers, Law enforcement, Security teams at Microsoft, and the other trusted sources; and check them against AAD users' current valid credential. If a match is found, that means a users' password has been compromised and a leaked credentials risk event is created.

  • Sign-ins from Anonymous IP Address- This risk event can identify the users who have signed in from an IP address known as an anonymous proxy IP address that are generally used by those who want to hide their device's IP address and may be used for malicious intent.

  • Impossible Travel to Atypical Locations- This one can identify two sign-ins originating from geographically distant locations in which at least one of these is an atypical for the user according to his/her past behavior. It can also compare the time difference between the two sign ins and the time would have take for the user to travel from first location to the second one indicating that a different user is using the same credentials. However, the system have an initial learning period of 14 days during which it can learn a new user's sign-in behavior. 

  • Sign-in from Unfamiliar Locations- As the name suggests it can keep track of the past sign-in locations to determine new or unfamiliar locations and triggers a risk event if the location is not on the list of familiar locations. This system have an initial learning period of 30 days during which it does not mark any new locations as unfamiliar location. 

  • Sign-ins from Infected Devices- This one can identify sign-ins from the devices infected with malware that can actively communicate with a bot server. You can easily identify this by correlating IP addresses of the user's device against the IP addresses that were in contact with a bot server. 

  • Sign-ins from the IP Addresses with Suspicious Activity- It can identify the IP addresses with a high number of failed sign-in attempts across multiple user accounts over a short period of time. This is a machine learning algorithm that can ignore the obvious "false positives" like the IP addresses used by the other users in the organization. It has an initial learning period of 14 days to learn the sign-in pattern of a new user as well as a new tenant.  









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






































Comments

Post a Comment

Popular posts from this blog

Deployment (Part 3)

By Ashwin Venugopal -
Image
  To read part 1, please click  here To read part 2, please click  here Microsoft Monitoring Agent (MMA) MMA is used across multiple Microsoft solutions and has undergone a few name changes as its features and functionality have evolved. If it is being considered to be used, then following areas should be covered during a Microsoft Sentinel deployment project: Consider the timelines and the strategy for a migration to AMA (Azure Monitor Agent) before the MMA end-of-life.  Consider the central deployment and management methodology for MMA. Determine which endpoints are in scope for deployment as these affect the log ingestion volume significantly.  Azure Monitor Agent (AMA) Organizations with MMA as the main Microsoft Sentinel agent should start planning the migration to AMA as soon as possible to avoid a rushed migration. One of the main advantages of AMA is the ability to control the log collection policy centrally and apply different policies against different...
Read more

Deployment (Part 1)

By Ashwin Venugopal -
Image
  To read part 2, please click  here To read part 3, please click  here Azure Resources Microsoft Sentinel needs following resources to be created: Subscription (if a dedicated subscription(s) will be used) Resource group(s) Log Analytics workspace(s) Automation rules/playbook Alert rules Workbooks Microsoft Sentinel offers hundreds of alert rules, workbooks, and automation playbook templates along with hunting scripts. The templates can be used to activate/deploy schedule alerts, create customized dashboards, create automation playbooks and perform threat-hunting activities. Generally, once deployed, the resources created have to be adjusted to match the existing environment, configure local credentials, etc. Methods of deployment: Manual- Administrator can manually configures the Microsoft Sentinel resources with the help of Azure portal. Any manual process has the inherent risks of human operator error, lack of compliance with potential change control procedures, and u...
Read more

Project Resourcing (Part 2)

By Ashwin Venugopal -
Image
  To read part 1, please click  here Engineering - SIEM The SIEM engineers configures Microsoft Sentinel, including Log Analytics, Logic Apps, workbooks, and playbooks. They are also responsible for the following high-level tasks: Initial configuration of Azure tenant, including provisioning required resources, assigning access roles, and configuring workspace parameters like log retention, resource tagging, and blueprints.  Deployment and configuration of syslog/CEF log collection agents in appropriate locations to collect logs from on-premises devices. Generally, it will be joint effort of both system engineer and SIEM engineer, involving configuration and potential troubleshooting.  Working with system owners to enable log forwarding and configuring any required parsing of log data in Log Analytics.  Working with security operations to create and deploy KQL analytic rules to offer detections for SOC/Computer Security Incident Response Team (CSRIT) use. Tuning...
Read more