What is Microsoft Sentinel?
Microsoft Sentinel is a cloud-native SIEM solution provided by Microsoft. It is designed to provide advanced security analytics and continuous threat detection in the environment. We have a separate blog to help you get a basic understanding of Sentinel here.

Why Microsoft Sentinel?
We surely have a lot of technical perks of using Sentinel. But, we will discuss the non-technical benefits of Microsoft Sentinel instead of the technical ones.

• Ease of use: Sentinel offers many templates that the engineer can use as a starting point and build upon them for the best results. There is very little tool-specific training required to fully use this tool. The limitation is the security knowledge of the engineer using the tool.
• Pricing: Sentinel uses the Pay-as-you-Go model, where you will pay only for the volume of data ingested and the volume of data used for analytics. The price varies from region to region. Detailed pricing can be found here.
• Compatibility: Sentinel is compatible with almost all the market leaders in any service you can imagine. You can find the updated list here. Suppose you have your proprietary kind of logs you want to onboard to Sentinel. You can use the HTTP Data collection API to onboard them into Sentinel.
• Future Scope: SIEM is an enormous investment for any organization. It should serve us for the years to come. Microsoft is continuously improving and expanding its features for the exponentially growing cyber attacks in this digital world.
• Reliability: Microsoft’s ownership and frequent updates ensure that Sentinel’s templates remain reliable in the face of advancing threats. Microsoft uses its wide user base to enhance its Machine learning models for precise detections and alerts.
• No infrastructure requirement: Sentinel was one of the first tools to be a completely cloud-native SIEM solution. Being completely hosted on the cloud, there is very minimal effort required to have the SIEM up and running. Meeting all the prerequisites allows you to spin up Sentinel in less than 10 minutes.

Why not Microsoft Sentinel?
As we are well aware, nothing is perfect, even Microsoft Sentinel has its drawbacks. We have listed the major drawbacks below:

• No completely On-prem version: Sentinel is completely cloud-native, it doesn’t have any on-prem version. This may be required for some organizations who wish to keep all their data with them. Even though there are ways to connect local security monitoring tools like SCOM to Sentinel, it is not built into Sentinel.
• Analytical rules limitation: The number of active analytical rules you can have is limited to 512. Yes, this number is a big number, but for an organization with widespread infrastructure and choosing to have the best security, this is not sufficient. Again, organizations use cross-workspace queries to get around this limitation. Having a higher ceiling would be great.
• Historical logs: Don’t get confused by the term ‘historical logs’. This only applies if you are migrating from an existing SIEM to Sentinel. There is no way to copy your logs in your current SIEM to Sentinel. Even Microsoft recommends storing all the old logs in a storage account or a database and having Azure Data Explorer (ADX) query those logs. Although you can query data in ADX using KQL, it still requires monitoring a different portal.

As discussed above, Microsoft Sentinel has its own strengths and weaknesses, but we still think Sentinel is one of the most potent SIEM in the market. Garner has identified Sentinel as one of the market leaders in SIEM for the year 2023.

Step-1.1 From Service Provider / Managed Service Provider

1.2-Go to https://portal.azure.com, Select “My Customers“

1.3-Select “Create ARM Template”

1.4-Provide a Name & Description. Select the Delegated Scope – I am choosing “Subscription”.

1.5-The click on “Add Authorization”.

1.6-Select the User/Group, here am selecting a group having all the SOC Analysts. Then press ADD.

1.7-Then press on “View Template”

1.8-Download the template (filename.json).

Step-2.1 From Customer

2.2-Go to https://portal.azure.com, Select “Service Providers“.

2.3-Select “Service Provider Offers” select “Add Offer” > “Add via Template”

2.4-Upload the downloaded template (.json file).

2.5-On-boarding process is now completed. To see the subscription of the customer enable it from the directory.

3.1-For that go to “Directories & Subscription”

3.2-Select the Customer Directory.

3.2-Go to subscriptions and make sure the Customers’ subscription is showing there, if yes you can see the customers Sentinel workspace.

Below are some of the KQL queries for AD Security Events.

——————————————————————————————————————

AAD Password Protection-AllEvents

//If you add “Microsoft-AzureADPasswordProtection-DCAgent/Admin” as a log source to Sentinel/Log Analytics you can query Azure AD Password Protection events
Event
| where Source == “Microsoft-AzureADPasswordProtection-DCAgent”
| where EventID in (“10014”, “10015”, “10016”, “30002”, “30004”, “30026”, “10024”, “30008”, “30010”, “30028”, “30024”, “30003”, “30005”, “30027”, “30022”, “30007”, “10025”, “30009”, “30029”, “30023”)

——————————————————————————————————————

Table = SecurityEvent | Account Pre Auth Changes

//Detect when Kerberos preauthentication is enabled or disabled for a user
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| where EventID == 4738
| where AccountType == “User”
| where UserAccountControl has_any (“2064”, “2096”)
| extend Action = case(UserAccountControl has “2096”, strcat(“Kerberos preauthentication disabled”),
UserAccountControl has “2064”, strcat(“Kerberos preauthentication enabled”),
“unknown”)
| project TimeGenerated, Actor=SubjectAccount, User=TargetAccount, Action

——————————————————————————————————————

Table = SecurityEvent | Account Sensitivity Changed

//Detect when the ‘account is sensitive and cannot be delegated’ flag on an account is changed
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| project TimeGenerated, EventID, TargetAccount, SubjectAccount, UserAccountControl
| where EventID == “4738”
| where UserAccountControl has_any(“2094”, “2062”)
| extend Activity = case
(UserAccountControl contains “2094”, strcat(“Account Sensitivity Enabled”),
UserAccountControl contains “2062”, strcat(“Account Sensitivity Disabled”),
“Unknown”)
| project TimeGenerated, Target=TargetAccount, Actor=SubjectAccount, Activity

——————————————————————————————————————

Table = SecurityEvent | Account Set Password Not Required

//Alert when an Active Directory account is set to password not required
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| project TimeGenerated, EventID, TargetAccount, SubjectAccount, UserAccountControl
| where EventID == “4738”
| where UserAccountControl has (“2082”)
| extend Activity = strcat(“Account set to password not required”)
| project TimeGenerated, Target=TargetAccount, Actor=SubjectAccount, Activity

——————————————————————————————————————

Table = SecurityEvent | Anomalous IPC Recon

//Use series_decompose_anomalies to detect potentially anomalous IPC$ recon events. Configure start time as your anomaly learning period and timeframe as your detection period.
// Detection threshold determines the sensitivity, the higher the threshold value the higher the anomaly required to detect.
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent.

let starttime = 7d;
let timeframe = 30m;
let detectionthreshold = 2;
let outliers =
SecurityEvent
| project TimeGenerated, Account, Computer, EventID, ShareName
| where TimeGenerated > ago(starttime)
// Exclude known Accounts that often connect to various machines, such as Defender for ID or vulnerability management software
| where Account !in (“DOMAIN\Account1”)
| where EventID == “5140”
| where ShareName == “\\\IPC$” | order by TimeGenerated | summarize Events=count()by Account, bin(TimeGenerated, timeframe) | summarize EventCount=make_list(Events),TimeGenerated=make_list(TimeGenerated) by Account | extend outliers=series_decompose_anomalies(EventCount, detectionthreshold) | mv-expand TimeGenerated, EventCount, outliers | where outliers == 1 | distinct Account; SecurityEvent | project TimeGenerated, Account, Computer, EventID, ShareName, IpAddress | where TimeGenerated > ago(timeframe) | where EventID == “5140” | where ShareName == “\\\IPC$”
// Exclude computer objects connecting to themselves by parsing DOMAIN\Computer$ objects and Computer.DOMAIN.COM objects and excluding matches
| parse Account with * “\” AccountParse “$”
| parse Computer with ComputerParse “.” *
| where AccountParse != ComputerParse
// Find remaining outliers and make a set
| where Account in (outliers)
| summarize AccountActivity=make_set(Computer) by Account

——————————————————————————————————————

Table = SecurityEvent | Daily Summary of Group Additions

//Create a daily report of users being added to on premise Active Directory groups, summarized by group name
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| where TimeGenerated > ago (7d)
| where AccountType == “User”
| where EventID in (4728, 4732, 4756, 4761, 4746, 4751)
| project TimeGenerated, MemberName, [‘Group Name’]=TargetUserName, EventID
| parse MemberName with * ‘CN=’ UserAdded ‘,’ *
| summarize UsersAdded=make_set(UserAdded) by [‘Group Name’], startofday(TimeGenerated)
| sort by [‘Group Name’] asc, TimeGenerated desc

——————————————————————————————————————

Table = SecurityEvent | Detect Privileged AAD Admin Password Change

//Detects when a user with a privileged Azure AD role has had their on premises Active Directory password changed by someone other than themselves.
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent
//Data connector required for this query – Microsoft Sentinel UEBA

let timeframe=7d;
//First find any users that hold privileged Azure AD roles
IdentityInfo
| where TimeGenerated > ago(21d)
| where isnotempty(AssignedRoles)
| where AssignedRoles != “[]”
| summarize arg_max(TimeGenerated, *) by AccountUPN
| project AccountUPN, AccountName, AccountSID
//Join those users based on AccountSID to on premises Active Directory password reset events
| join kind=inner (
SecurityEvent
| where TimeGenerated > ago(timeframe)
| where EventID == “4724”
| project
TimeGenerated,
Activity,
SubjectAccount,
TargetAccount,
TargetSid,
SubjectUserSid
)
on $left.AccountSID == $right.TargetSid
| where SubjectUserSid != TargetSid
//Summarize event data to make it easy to read
| project [‘Time of Password Reset’]=TimeGenerated, Activity, Actor=SubjectAccount, [‘Target UserPrincipalName’]=AccountUPN,[‘Target AccountName’]=TargetAccount

——————————————————————————————————————

Table = SecurityEvent | GPO Inheritance Changed

//Detect when group policy inheritance is either allowed or blocked
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| project TimeGenerated, EventID, EventData, SubjectAccount
| where EventID == “5136”
| parse EventData with * ‘ObjectDN”>’ OU ” LDAPAttribute ” AttributeValue ‘%%’ OperationType ‘</Data’ *
| project
TimeGenerated,
Actor=SubjectAccount,
OU,
LDAPAttribute,
AttributeValue,
OperationType
| where LDAPAttribute == “gPOptions”
| where AttributeValue == “1”
| extend Activity = case
(OperationType == “14674” and AttributeValue == “1”, strcat(“Group Policy Inheritance Blocked”),
OperationType == “14675” and AttributeValue == “1”, strcat(“Group Policy Inheritance Allowed”),
“Unknown”)
| project TimeGenerated, Actor, OU, Activity

——————————————————————————————————————

Table = SecurityEvent | Logon To Device List Changed

//Alert when the ‘Log on to’ device list is changed for a user
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| where EventID == 4738
| where AccountType == “User”
//Include domain accounts only (excluding local accounts)
| where TargetDomainName == SubjectDomainName
| extend [‘Allowed Devices’] = case(isnotempty(UserWorkstations) and UserWorkstations != “-” and UserWorkstations != “%%1793”, split(UserWorkstations, “,”),
(isnotempty(UserWorkstations) and UserWorkstations == “%%1793”), strcat(“User can log onto all devices”),
“unknown”)
//Exclude other 4738 events where the device list isn’t changed
| where [‘Allowed Devices’] != “unknown”
| project TimeGenerated, Actor=SubjectAccount, User=TargetAccount, [‘Allowed Devices’]

——————————————————————————————————————

Table = SecurityEvent | Summarize Privileges Assigned on Logon

//Create a summary of your computers and the accounts that have logged on with special privileges over the last 30 days
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| where TimeGenerated > ago (30d)
| project TimeGenerated, EventID, Account, AccountType, PrivilegeList, Computer
| where EventID == “4672”
| where Account != “NT AUTHORITY\SYSTEM” and Account !has “Window Manager”
| where AccountType == “User”
//The privilege list is stored in a string of text that we need to split
| extend Privs=extract_all(@”Se(.*?)Privilege”, PrivilegeList)
//Once we retrieve the privileges from the string of text we can recreate the proper naming
| mv-expand Privs
| extend Privilege=strcat(‘Se’, Privs, ‘Privilege’)
| project TimeGenerated, Account, Computer, Privilege
| summarize [‘List of Privileges’]=make_set(Privilege) by Computer, Account
| sort by Computer asc

——————————————————————————————————————

Table = SecurityEvent | Summarize RDP Activity

//Creates a list of computers that your users have connected to via RDP and the total count of distinct computers each user has connected to
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| where TimeGenerated > ago(7d)
| where EventID == “4624”
| where LogonType == 10
//Extend new column that drops Account to lower case so users are correctly summarized, i.e User123 and user123 are combined
| extend AccountName=tolower(Account)
| summarize
[‘Count of Computers’]=dcount(Computer),
[‘List of Computers’]=make_set(Computer)
by AccountName
| sort by [‘Count of Computers’] desc

——————————————————————————————————————

Table = SecurityEvent | UAC Flag Parser

//Creates a parser for all user account control changes changing the code into a readable message
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| where isnotempty(UserAccountControl) and UserAccountControl != “-“
| where AccountType == “User”
| extend x = extract_all(@”([0-9]{4})”, UserAccountControl)
| mv-expand x
| extend [‘User Account Flag Description’] = case
(
x == “2048”, strcat(“Account Enabled”),
x == “2049”, strcat(“Home Directory Required – Disabled”),
x == “2050”, strcat(“Password Not Required – Disabled”),
x == “2051”, strcat(“Temp Duplicate Account – Disabled”),
x == “2052”, strcat(“Normal Account – Disabled”),
x == “2053”, strcat(“MNS Logon Account – Disabled”),
x == “2054”, strcat(“Interdomain Trust Account – Disabled”),
x == “2055”, strcat(“Workstation Trust Account – Disabled”),
x == “2056”, strcat(“Server Trust Account – Disabled”),
x == “2057”, strcat(“Don’t Expire Password – Disabled”),
x == “2058”, strcat(“Account Unlocked”),
x == “2059”, strcat(“Encrypted Text Password Allowed – Disabled”),
x == “2060”, strcat(“Smartcard Required – Disabled”),
x == “2061”, strcat(“Trusted For Delegation – Disabled”),
x == “2062”, strcat(“Not Delegated – Disabled”),
x == “2063”, strcat(“Use DES Key Only – Disabled”),
x == “2064”, strcat(“Don’t Require Preauth – Disabled”),
x == “2065”, strcat(“Password Expired – Disabled”),
x == “2066”, strcat(“Trusted To Authenticate For Delegation – Disabled”),
x == “2067”, strcat(“Exclude Authorization Information – Disabled”),
x == “2068”, strcat(“Undefined UserAccountControl Bit 20 – Disabled”),
x == “2069”, strcat(“Protect Kerberos Service Tickets with AES Keys – Disabled”),
x == “2070”, strcat(“Undefined UserAccountControl Bit 22 – Disabled”),
x == “2071”, strcat(“Undefined UserAccountControl Bit 23 – Disabled”),
x == “2072”, strcat(“Undefined UserAccountControl Bit 24 – Disabled”),
x == “2073”, strcat(“Undefined UserAccountControl Bit 25 – Disabled”),
x == “2074”, strcat(“Undefined UserAccountControl Bit 26 – Disabled”),
x == “2075”, strcat(“Undefined UserAccountControl Bit 27 – Disabled”),
x == “2076”, strcat(“Undefined UserAccountControl Bit 28 – Disabled”),
x == “2077”, strcat(“Undefined UserAccountControl Bit 29 – Disabled”),
x == “2078”, strcat(“Undefined UserAccountControl Bit 30 – Disabled”),
x == “2079”, strcat(“Undefined UserAccountControl Bit 31 – Disabled”),
x == “2080”, strcat(“Account Disabled”),
x == “2081”, strcat(“Home Directory Required – Enabled”),
x == “2082”, strcat(“Password Not Required – Enabled”),
x == “2083”, strcat(“Temp Duplicate Account – Enabled”),
x == “2084”, strcat(“Normal Account – Enabled”),
x == “2085”, strcat(“MNS Logon Account – Enabled”),
x == “2086”, strcat(“Interdomain Trust Account – Enabled”),
x == “2087”, strcat(“Workstation Trust Account – Enabled”),
x == “2088”, strcat(“Server Trust Account – Enabled”),
x == “2089”, strcat(“Don’t Expire Password – Enabled”),
x == “2090”, strcat(“Account Locked”),
x == “2091”, strcat(“Encrypted Text Password Allowed – Enabled”),
x == “2092”, strcat(“Smartcard Required – Enabled”),
x == “2093”, strcat(“Trusted For Delegation – Enabled”),
x == “2094”, strcat(“Not Delegated – Enabled”),
x == “2095”, strcat(“Use DES Key Only – Enabled”),
x == “2096”, strcat(“Don’t Require Preauth – Enabled”),
x == “2097”, strcat(“Password Expired – Enabled”),
x == “2098”, strcat(“Trusted To Authenticate For Delegation – Enabled”),
x == “2099”, strcat(“Exclude Authorization Information – Enabled”),
x == “2100”, strcat(“Undefined UserAccountControl Bit 20 – Enabled”),
x == “2101”, strcat(“Protect Kerberos Service Tickets with AES Keys – Enabled”),
x == “2102”, strcat(“Undefined UserAccountControl Bit 22 – Enabled”),
x == “2103”, strcat(“Undefined UserAccountControl Bit 23 – Enabled”),
x == “2104”, strcat(“Undefined UserAccountControl Bit 24 – Enabled”),
x == “2105”, strcat(“Undefined UserAccountControl Bit 25 – Enabled”),
x == “2106”, strcat(“Undefined UserAccountControl Bit 26 – Enabled”),
x == “2107”, strcat(“Undefined UserAccountControl Bit 27 – Enabled”),
x == “2108”, strcat(“Undefined UserAccountControl Bit 28 – Enabled”),
x == “2109”, strcat(“Undefined UserAccountControl Bit 29 – Enabled”),
x == “2110”, strcat(“Undefined UserAccountControl Bit 30 – Enabled”),
x == “2111”, strcat(“Undefined UserAccountControl Bit 31 – Enabled”),
“Unknown”)
| project
TimeGenerated,
TargetAccount,
Actor=SubjectAccount,
UserAccountControl=x,
[‘User Account Flag Description’]

——————————————————————————————————————

Table = SecurityEvent | Unconstrained Delegation Enabled

//Detects when unconstrained kerberos delegation is enabled on a computer object
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| where EventID == “4742”
| parse EventData with * ‘NewUacValue”>’ NewUacValue ” *
| parse EventData with * ‘TargetUserName”>’ ComputerName ” *
| parse EventData with * ‘SubjectUserName”>’ Actor ” *
| where NewUacValue == “0x2080”
| project TimeGenerated, Activity, ComputerName, Actor

——————————————————————————————————————

Table = SecurityEvent | Unconstrained Delegation to User

//Detects when unconstrained kerberos delegation is enabled on a user object
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| where EventID == “4738”
| parse EventData with * ‘NewUacValue”>’ NewUacValue ” *
| parse EventData with * ‘TargetUserName”>’ UserName ” *
| parse EventData with * ‘SubjectUserName”>’ Actor ” *
| where NewUacValue == “0x2010”
| project TimeGenerated, Activity, UserName, Actor

——————————————————————————————————————

Table = SecurityEvent | Visualize Accounts Created Disabled Deleted

//Visualize Active Directory accounts created, disabled and deleted per day
//Data connector required for this query – Windows Security Events via AMA or Security Events via Legacy Agent

SecurityEvent
| where TimeGenerated > ago(30d)
| where AccountType == “User”
| project TimeGenerated, Account, EventID, TargetAccount
| where EventID in (“4720”, “4725”, “4726”)
| where TargetAccount !endswith “$”
| summarize
[‘Accounts Created’]=countif(EventID == “4720”),
[‘Accounts Deleted’]=countif(EventID == “4726”),
[‘Accounts Disabled’]=countif(EventID == “4725”)
by startofday(TimeGenerated)
| render columnchart
with (
kind=unstacked,
xtitle=”Day”,
ytitle=”Count”,
title=”Active Directory User Accounts Created, Disabled and Deleted per day”)

——————————————————————————————————————

Microsoft Sentinel utilizes various machine learning (ML) techniques to enhance its threat detection, incident response, and overall security capabilities. Microsoft has been investing heavily in AI and ML technologies, and these are integrated into Azure Sentinel to provide intelligent security analytics. Some of the key machine learning aspects of Microsoft Sentinel include:

1. Anomaly Detection: Azure Sentinel employs machine learning algorithms to establish baseline patterns of normal behavior for users, devices, and entities within an organization’s environment. By continuously analyzing data and comparing it to these baselines, Azure Sentinel can detect anomalies that might indicate potential security threats or abnormal behavior.
2. Threat Detection: Machine learning is utilized to identify patterns and indicators of compromise (IOCs) that are indicative of known or emerging threats. By analyzing large volumes of data from various sources, Azure Sentinel can identify malicious activities that may go unnoticed using traditional rule-based approaches.
3. User and Entity Behavior Analytics (UEBA): Azure Sentinel’s UEBA capabilities utilize machine learning algorithms to monitor and analyze user and entity behavior across the organization’s network. By identifying deviations from normal behavior, UEBA can flag potential insider threats or compromised accounts.
4. Automated Incident Response: Machine learning algorithms play a crucial role in Azure Sentinel’s Security Orchestration, Automation, and Response (SOAR) capabilities. These algorithms help in automating response actions based on predefined playbooks, reducing the manual effort required for incident response.
5. Threat Intelligence: Azure Sentinel integrates with threat intelligence feeds, and machine learning is used to process and analyze threat data continuously. This ensures that the platform stays up-to-date with the latest threat information and can enrich security events with relevant threat context.
6. Log Analytics: Azure Sentinel’s log analytics capabilities are enhanced by machine learning algorithms that assist in parsing and categorizing vast amounts of log data from diverse sources. This enables faster and more efficient querying and analysis of security data.

1. Threat Intelligence: Azure Sentinel uses AI-powered threat intelligence to stay up-to-date with the latest threats, attack patterns, and vulnerabilities. It leverages various threat feeds and sources to enrich security data and enhance threat detection.
2. Anomaly Detection: Azure Sentinel employs machine learning algorithms to identify anomalies and abnormal behavior in the environment. By analyzing historical data, it establishes baseline patterns of normal activity and can identify deviations that may indicate potential security incidents.
3. Behavioral Analytics: The platform incorporates behavioral analytics to detect suspicious activities or unauthorized access attempts. By analyzing user and entity behavior, Azure Sentinel can identify potentially risky actions and flag them for investigation.
4. Automated Incident Response: Azure Sentinel’s SOAR capabilities, driven by AI and automation, allow for automated incident response actions. Security teams can create playbooks that define automated responses to specific types of security incidents, streamlining the incident response process.
5. Incident Prioritization: AI-powered analytics help Azure Sentinel prioritize security alerts based on their severity and potential impact. This prioritization allows security analysts to focus on the most critical threats first.
6. Threat Hunting: Azure Sentinel enables security teams to perform advanced threat hunting using AI-driven queries and analytics. Analysts can proactively search for potential threats and indicators of compromise in their environment.
7. User and Entity Behavior Analytics (UEBA): Azure Sentinel includes UEBA capabilities that use AI to detect unusual or risky behavior by users and entities. This helps identify insider threats and other anomalous activities that might not be apparent through traditional rule-based detection.
8. Smart Response Suggestions: During incident investigations, Azure Sentinel provides smart response suggestions based on historical data and previous actions taken for similar incidents. This helps guide analysts in making informed decisions on response actions.

Microsoft Sentinel is designed to provide intelligent security analytics and threat intelligence to help organizations detect, investigate, and respond to cybersecurity threats in real-time. It collects and analyzes data from various sources, including logs, events, and alerts generated by different cloud and on-premises resources, network devices, and applications. By leveraging advanced AI and machine learning capabilities, Azure Sentinel helps security teams uncover and respond to threats more effectively.

Key features of Azure Sentinel include:

1. Data Collection: Azure Sentinel ingests data from various sources, including Microsoft and third-party solutions, making it easier to centralize and correlate security data.
2. Threat Detection: The platform uses advanced analytics and AI-driven detections to identify and prioritize potential threats and security incidents.
3. Incident Investigation: Security analysts can perform in-depth investigations by analyzing historical data and employing interactive workbooks and visualizations.
4. Threat Intelligence: Azure Sentinel integrates with threat intelligence feeds to stay up-to-date with the latest threats and attack patterns.
5. Automated Response: The platform allows users to define and automate responses to certain types of security incidents, streamlining incident response workflows.
6. Integration with Microsoft Services: Azure Sentinel works seamlessly with other Microsoft services such as Microsoft 365 Defender, Azure Security Center, and more.

Microsoft Sentinel is considered one of the leading Security Information and Event Management (SIEM) and SOAR solutions in the industry:

1. Integration with Microsoft Ecosystem: Azure Sentinel seamlessly integrates with other Microsoft services, such as Microsoft 365 Defender, Azure Security Center, and Microsoft Defender ATP. This integration allows for a unified security experience and streamlined workflows for security teams.
2. Cloud-Native Solution: Being a cloud-native SIEM, Azure Sentinel can scale dynamically to handle large volumes of security data from various sources, including on-premises and cloud environments. It takes advantage of cloud capabilities for storage, processing, and analytics, reducing the need for on-premises infrastructure.
3. Advanced Threat Detection: Azure Sentinel leverages Microsoft’s AI and machine learning capabilities to detect and respond to sophisticated cyber threats in real-time. Its advanced analytics can identify anomalous activities and patterns that might be indicative of security incidents.
4. Security Orchestration and Automation: The inclusion of Security Orchestration, Automation, and Response (SOAR) capabilities allows security teams to automate response actions, reducing manual tasks and improving incident response times.
5. Built-in Threat Intelligence: Azure Sentinel integrates with threat intelligence feeds, providing security teams with up-to-date information about known threats and vulnerabilities.
6. Customization and Flexibility: Azure Sentinel allows organizations to customize detection rules, alerts, and playbooks based on their unique security requirements. This flexibility ensures that the platform can adapt to specific use cases.
7. Microsoft’s Commitment to Security: Microsoft is a major player in the technology industry, and it invests heavily in security research and development. Azure Sentinel benefits from Microsoft’s ongoing efforts to enhance security across its products and services.
8. Comprehensive Data Visibility: With its ability to ingest data from various sources, including cloud services, network devices, and security solutions, Azure Sentinel provides a comprehensive view of an organization’s security landscape.

The SOAR capabilities in Azure Sentinel are designed to help security teams:

1. Automate Playbooks: Security analysts can create and customize playbooks that define automated response actions to specific security incidents or events. Playbooks are a series of automated steps that can be executed when certain conditions are met. They can include actions such as quarantining an endpoint, blocking an IP address, or notifying relevant stakeholders.
2. Incident Response Automation: Azure Sentinel can automatically trigger and execute predefined playbooks in response to detected security incidents. This automation helps reduce the time it takes to respond to threats, minimizes manual intervention, and ensures consistent and effective responses.
3. Integration with Security Solutions: Azure Sentinel integrates with a wide range of Microsoft and third-party security solutions, such as Azure Security Center, Microsoft Defender ATP, and more. This integration enables seamless communication and collaboration between different security tools and allows for a coordinated response to security incidents.
4. Interactive Investigation with Automated Response: During incident investigations, security analysts can utilize interactive workbooks and visualizations to gain insights into the incident. If necessary, they can also initiate automated response actions directly from the investigation interface.
5. Alert Enrichment and Contextualization: Azure Sentinel enriches and contextualizes alerts by pulling in relevant data from various sources. This additional information assists analysts in understanding the severity and scope of an incident and helps in making informed decisions about response actions.
6. Continuous Improvement: As incidents are resolved, Azure Sentinel tracks and records the response actions taken. This data can be analyzed to identify patterns and improve the efficiency of future automated responses.