Skip to content

Latest commit

 

History

History
205 lines (154 loc) · 10.9 KB

alert-classification-password-spray-attack.md

File metadata and controls

205 lines (154 loc) · 10.9 KB
title description ms.service f1.keywords ms.author author ms.localizationpriority manager audience ms.collection ms.custom ms.topic search.appverid ms.date
Alert classification for password spray attacks
Alert classification guide for password spray attacks coming to review the alerts and take recommended actions to remediate the attack and protect your network.
defender-xdr
NOCSH
diannegali
diannegali
medium
dansimp
ITPro
m365-security
tier2
admindeeplinkDEFENDER
conceptual
MOE150
met150
02/11/2024

Alert classification for password spray attacks

[!INCLUDE Microsoft Defender XDR rebranding]

Applies to:

  • Microsoft Defender XDR

Threat actors use innovative ways to compromise their target environments. One type of attack gaining traction is the password spray attack, where attackers aim to access many accounts within a network with minimal effort. Unlike traditional brute force attacks, where threat actors try many passwords on a single account, password spray attacks focus on guessing the correct password for many accounts with a limited set of commonly used passwords. It makes the attack particularly effective against organizations with weak or easily guessable passwords, leading to severe data breaches and financial losses for organizations.

Attackers use automated tools to repeatedly attempt to gain access to a specific account or system using a list of commonly used passwords. Attackers sometimes abuse legitimate cloud services by creating many virtual machines (VMs) or containers to launch a password spray attack.

This playbook helps investigate cases where suspicious behavior is observed as indicative of a password spray attack. This guide is for security teams like the security operations center (SOC) and IT administrators who review, handle/manage, and classify the alerts. This guide helps in quickly classifying the alerts as either true positive (TP) or false positive (FP) and, in the case of TP, take recommended actions to remediate the attack and mitigate the security risks.

The intended results of using this guide are:

  • You've identified the alerts associated with password spray attempts as malicious (TP) or false positive (FP) activities.

  • You've taken the necessary actions to remediate the attack.

Investigation steps

This section contains step-by-step guidance to respond to the alert and take the recommended actions to protect your organization from further attacks.

1. Investigate the security alerts

  • Are the alerted sign-in attempts coming from a suspicious location? Check sign-in attempts from locations other than those typical for impacted user accounts. Multiple sign-in attempts from one or many users are helpful indicators.

2. Investigate suspicious user activity

  • Are there unusual events with uncommon properties? Unique properties for an impacted user, like unusual ISP, country/region, or city, might indicate suspicious sign-in patterns.

  • Is there a marked increase in email or file-related activities? Suspicious events like increased attempts in mail access or send activity or an increase in uploading of files to SharePoint or OneDrive for an impacted user are some signs to look for.

  • Are there multiple failed sign-in attempts? A high number of failed sign-in attempts from various IPs and geographic locations by an impacted user might indicate a password spray attack.

  • Identify the ISP from the sign-in activity of an impacted user. Check for sign-in activities by other user accounts from the same ISP.

  • Inspect any recent modifications in your environment:

    • Changes in Office 365 applications like Exchange Online permission, mail auto-forwarding, mail redirection
    • Modifications in PowerApps, like automated data transmission configuration through PowerAutomate
    • Modifications in Azure environments, like Azure portal subscription changes
    • Changes to SharePoint Online, like the impacted user account gaining access to multiple sites or files with sensitive/confidential/company-only content
  • Inspect the impacted account's activities that occur within a short time span on multiple platforms and apps. Audit events to check the timeline of activities, like contrasting the user's time spent reading or sending email followed by allocating resources to the user's account or other accounts.

3. Investigate possible follow-on attacks

Inspect your environment for other attacks involving impacted user accounts as attackers often perform malicious activities after a successful password spray attack. Consider investigating the following possibly suspicious activities:

  • Multi-factor authentication (MFA)-related attacks

    • Attackers use MFA fatigue to bypass this security measure that organizations adopt to protect their systems. Check for multiple MFA requests raised by an impacted user account.
    • Attackers might perform MFA tampering using an impacted user account with elevated privileges by disabling MFA protection for other accounts within the tenant. Check for suspicious admin activities performed by an impacted user.
  • Internal phishing attacks

Advanced hunting queries

Advanced hunting is a query-based threat hunting tool that lets you inspect events in your network and locate threat indicators.

Use these queries to gather more information related to the alert and determine whether the activity is suspicious.

Ensure you have access to the following tables:

Use this query to identify password spray activity.

IdentityLogonEvents
| where Timestamp > ago(7d)
| where ActionType == "LogonFailed"
| where isnotempty(RiskLevelDuringSignIn)
| where AccountObjectId == <Impacted User Account Object ID>
| summarize TargetCount = dcount(AccountObjectId), TargetCountry = dcount(Location), TargetIPAddress = dcount(IPAddress) by ISP
| where TargetCount >= 100
| where TargetCountry >= 5
| where TargetIPAddress >= 25

Use this query to identify other activities from the alerted ISP.

CloudAppEvents
| where Timestamp > ago(7d)
| where AccountObjectId == <Impacted User Account Object ID>
| where ISP == <Alerted ISP>
| summarize count() by Application, ActionType, bin(Timestamp, 1h)

Use this query to identify sign-in patterns for the impacted user.

IdentityLogonEvents
| where Timestamp > ago(7d)
| where AccountObjectId == <Impacted User Account Object ID>
| where ISP == <Alerted ISP>
| where Application != "Active Directory"
| summarize SuccessCount = countif(ActionType == "LogonSuccess"), FailureCount = countif(ActionType == "LogonFailed") by ISP

Use this query to identify MFA fatigue attacks.

AADSignInEventsBeta
| where Timestamp > ago(1h)
//Error Code : 50088 : Limit on telecom MFA calls reached
//Error Code : 50074 : Strong Authentication is required.
| where ErrorCode in  ("50074","50088")
| where isnotempty(AccountObjectId)
| where isnotempty(IPAddress)
| where isnotempty(Country)
| summarize (Timestamp, ReportId) = arg_max(Timestamp, ReportId), FailureCount = count() by AccountObjectId, Country, IPAddress
| where FailureCount >= 10

Use this query to identify MFA reset activities.

let relevantActionTypes = pack_array("Disable Strong Authentication.","system.mfa.factor.deactivate", "user.mfa.factor.update", "user.mfa.factor.reset_all", "core.user_auth.mfa_bypass_attempted");
CloudAppEvents
AlertInfo
| where Timestamp > ago(1d)
| where isnotempty(AccountObjectId)
| where Application in ("Office 365","Okta")
| where ActionType in (relevantActionTypes)
| where RawEventData contains "success"
| project Timestamp, ReportId, AccountObjectId, IPAddress, ActionType



CloudAppEvents
| where Timestamp > ago(1d)
| where ApplicationId == 11161 
| where ActionType == "Update user." 
| where isnotempty(AccountObjectId)
| where RawEventData has_all("StrongAuthenticationRequirement","[]")
| mv-expand ModifiedProperties = RawEventData.ModifiedProperties
| where ModifiedProperties.Name == "StrongAuthenticationRequirement" and ModifiedProperties.OldValue != "[]" and ModifiedProperties.NewValue == "[]"
| mv-expand ActivityObject = ActivityObjects
| where ActivityObject.Role == "Target object"
| extend TargetObjectId = tostring(ActivityObject.Id)
| project Timestamp, ReportId, AccountObjectId, ActivityObjects, TargetObjectId

Use this query to find new email inbox rules created by the impacted user.

CloudAppEvents
| where AccountObjectId == <ImpactedUser>
| where Timestamp > ago(21d)
| where ActionType == "New-InboxRule"
| where RawEventData.SessionId in (suspiciousSessionIds)

Recommended actions

Once you determine that the activities associated with this alert are malicious, classify those alerts as TP and take these actions for remediation:

  1. Reset the user's account credentials.
  2. Revoke access tokens of the compromised account.
  3. Use number matching in Microsoft Authenticator to mitigate MFA fatigue attacks.
  4. Apply the principle of least privilege. Create accounts with minimum privilege required to complete tasks.
  5. Configure blocking based on the sender's IP address and domains if the artifacts are related to email.
  6. Block URLs or IP addresses (on the network protection platforms) that were identified as malicious during the investigation.

See also