Brute Force Attack against GitHub Account
Id | 97ad74c4-fdd9-4a3f-b6bf-5e28f4f71e06 |
Rulename | Brute Force Attack against GitHub Account |
Description | Attackers who are trying to guess your users’ passwords or use brute-force methods to get in. If your organization is using SSO with Microsoft Entra ID, authentication logs to GitHub.com will be generated. Using the following query can help you identify a sudden increase in failed logon attempt of users. |
Severity | Medium |
Tactics | CredentialAccess |
Techniques | T1110 |
Required data connectors | AzureActiveDirectory |
Kind | Scheduled |
Query frequency | 1h |
Query period | 7d |
Trigger threshold | 0 |
Trigger operator | gt |
Source Uri | https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Microsoft Entra ID/Analytic Rules/Brute Force Attack against GitHub Account.yaml |
Version | 2.0.2 |
Arm template | 97ad74c4-fdd9-4a3f-b6bf-5e28f4f71e06.json |
let LearningPeriod = 7d;
let BinTime = 1h;
let RunTime = 1h;
let StartTime = 1h;
let sensitivity = 2.5;
let EndRunTime = StartTime - RunTime;
let EndLearningTime = StartTime + LearningPeriod;
let aadFunc = (tableName:string){
table(tableName)
| where TimeGenerated between (ago(EndLearningTime) .. ago(EndRunTime))
| where AppDisplayName =~ "GitHub.com"
| where ResultType != 0
| make-series FailedLogins = count() on TimeGenerated from ago(LearningPeriod) to ago(EndRunTime) step BinTime by UserPrincipalName, Type
| extend (Anomalies, Score, Baseline) = series_decompose_anomalies(FailedLogins, sensitivity, -1, 'linefit')
| mv-expand FailedLogins to typeof(double), TimeGenerated to typeof(datetime), Anomalies to typeof(double), Score to typeof(double), Baseline to typeof(long)
| where TimeGenerated >= ago(RunTime)
| where Anomalies > 0 and Baseline > 0
| join kind=inner (
table(tableName)
| where TimeGenerated between (ago(StartTime) .. ago(EndRunTime))
| where AppDisplayName =~ "GitHub.com"
| where ResultType != 0
| summarize StartTime = min(TimeGenerated), EndTime = max(TimeGenerated), IPAddresses = make_set(IPAddress,100), Locations = make_set(LocationDetails,20), Devices = make_set(DeviceDetail,20) by UserPrincipalName, UserId, AppDisplayName
) on UserPrincipalName
| project-away UserPrincipalName1
| extend Name = tostring(split(UserPrincipalName,'@',0)[0]), UPNSuffix = tostring(split(UserPrincipalName,'@',1)[0])
| extend IPAddressFirst = tostring(IPAddresses[0])
};
let aadSignin = aadFunc("SigninLogs");
let aadNonInt = aadFunc("AADNonInteractiveUserSignInLogs");
union isfuzzy=true aadSignin, aadNonInt
id: 97ad74c4-fdd9-4a3f-b6bf-5e28f4f71e06
triggerOperator: gt
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Microsoft Entra ID/Analytic Rules/Brute Force Attack against GitHub Account.yaml
requiredDataConnectors:
- dataTypes:
- SigninLogs
connectorId: AzureActiveDirectory
- dataTypes:
- AADNonInteractiveUserSignInLogs
connectorId: AzureActiveDirectory
description: |
'Attackers who are trying to guess your users' passwords or use brute-force methods to get in. If your organization is using SSO with Microsoft Entra ID, authentication logs to GitHub.com will be generated. Using the following query can help you identify a sudden increase in failed logon attempt of users.'
severity: Medium
queryPeriod: 7d
kind: Scheduled
tactics:
- CredentialAccess
queryFrequency: 1h
query: |
let LearningPeriod = 7d;
let BinTime = 1h;
let RunTime = 1h;
let StartTime = 1h;
let sensitivity = 2.5;
let EndRunTime = StartTime - RunTime;
let EndLearningTime = StartTime + LearningPeriod;
let aadFunc = (tableName:string){
table(tableName)
| where TimeGenerated between (ago(EndLearningTime) .. ago(EndRunTime))
| where AppDisplayName =~ "GitHub.com"
| where ResultType != 0
| make-series FailedLogins = count() on TimeGenerated from ago(LearningPeriod) to ago(EndRunTime) step BinTime by UserPrincipalName, Type
| extend (Anomalies, Score, Baseline) = series_decompose_anomalies(FailedLogins, sensitivity, -1, 'linefit')
| mv-expand FailedLogins to typeof(double), TimeGenerated to typeof(datetime), Anomalies to typeof(double), Score to typeof(double), Baseline to typeof(long)
| where TimeGenerated >= ago(RunTime)
| where Anomalies > 0 and Baseline > 0
| join kind=inner (
table(tableName)
| where TimeGenerated between (ago(StartTime) .. ago(EndRunTime))
| where AppDisplayName =~ "GitHub.com"
| where ResultType != 0
| summarize StartTime = min(TimeGenerated), EndTime = max(TimeGenerated), IPAddresses = make_set(IPAddress,100), Locations = make_set(LocationDetails,20), Devices = make_set(DeviceDetail,20) by UserPrincipalName, UserId, AppDisplayName
) on UserPrincipalName
| project-away UserPrincipalName1
| extend Name = tostring(split(UserPrincipalName,'@',0)[0]), UPNSuffix = tostring(split(UserPrincipalName,'@',1)[0])
| extend IPAddressFirst = tostring(IPAddresses[0])
};
let aadSignin = aadFunc("SigninLogs");
let aadNonInt = aadFunc("AADNonInteractiveUserSignInLogs");
union isfuzzy=true aadSignin, aadNonInt
version: 2.0.2
triggerThreshold: 0
name: Brute Force Attack against GitHub Account
entityMappings:
- entityType: Account
fieldMappings:
- columnName: UserPrincipalName
identifier: FullName
- columnName: Name
identifier: Name
- columnName: UPNSuffix
identifier: UPNSuffix
- entityType: Account
fieldMappings:
- columnName: UserId
identifier: AadUserId
- entityType: IP
fieldMappings:
- columnName: IPAddressFirst
identifier: Address
status: Available
relevantTechniques:
- T1110
{
"$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
"contentVersion": "1.0.0.0",
"parameters": {
"workspace": {
"type": "String"
}
},
"resources": [
{
"apiVersion": "2024-01-01-preview",
"id": "[concat(resourceId('Microsoft.OperationalInsights/workspaces/providers', parameters('workspace'), 'Microsoft.SecurityInsights'),'/alertRules/97ad74c4-fdd9-4a3f-b6bf-5e28f4f71e06')]",
"kind": "Scheduled",
"name": "[concat(parameters('workspace'),'/Microsoft.SecurityInsights/97ad74c4-fdd9-4a3f-b6bf-5e28f4f71e06')]",
"properties": {
"alertRuleTemplateName": "97ad74c4-fdd9-4a3f-b6bf-5e28f4f71e06",
"customDetails": null,
"description": "'Attackers who are trying to guess your users' passwords or use brute-force methods to get in. If your organization is using SSO with Microsoft Entra ID, authentication logs to GitHub.com will be generated. Using the following query can help you identify a sudden increase in failed logon attempt of users.'\n",
"displayName": "Brute Force Attack against GitHub Account",
"enabled": true,
"entityMappings": [
{
"entityType": "Account",
"fieldMappings": [
{
"columnName": "UserPrincipalName",
"identifier": "FullName"
},
{
"columnName": "Name",
"identifier": "Name"
},
{
"columnName": "UPNSuffix",
"identifier": "UPNSuffix"
}
]
},
{
"entityType": "Account",
"fieldMappings": [
{
"columnName": "UserId",
"identifier": "AadUserId"
}
]
},
{
"entityType": "IP",
"fieldMappings": [
{
"columnName": "IPAddressFirst",
"identifier": "Address"
}
]
}
],
"OriginalUri": "https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Microsoft Entra ID/Analytic Rules/Brute Force Attack against GitHub Account.yaml",
"query": "let LearningPeriod = 7d;\nlet BinTime = 1h;\nlet RunTime = 1h;\nlet StartTime = 1h; \nlet sensitivity = 2.5;\nlet EndRunTime = StartTime - RunTime;\nlet EndLearningTime = StartTime + LearningPeriod;\nlet aadFunc = (tableName:string){\ntable(tableName) \n| where TimeGenerated between (ago(EndLearningTime) .. ago(EndRunTime))\n| where AppDisplayName =~ \"GitHub.com\"\n| where ResultType != 0\n| make-series FailedLogins = count() on TimeGenerated from ago(LearningPeriod) to ago(EndRunTime) step BinTime by UserPrincipalName, Type\n| extend (Anomalies, Score, Baseline) = series_decompose_anomalies(FailedLogins, sensitivity, -1, 'linefit')\n| mv-expand FailedLogins to typeof(double), TimeGenerated to typeof(datetime), Anomalies to typeof(double), Score to typeof(double), Baseline to typeof(long) \n| where TimeGenerated >= ago(RunTime)\n| where Anomalies > 0 and Baseline > 0\n| join kind=inner (\n table(tableName) \n | where TimeGenerated between (ago(StartTime) .. ago(EndRunTime))\n | where AppDisplayName =~ \"GitHub.com\"\n | where ResultType != 0\n | summarize StartTime = min(TimeGenerated), EndTime = max(TimeGenerated), IPAddresses = make_set(IPAddress,100), Locations = make_set(LocationDetails,20), Devices = make_set(DeviceDetail,20) by UserPrincipalName, UserId, AppDisplayName\n ) on UserPrincipalName\n| project-away UserPrincipalName1\n| extend Name = tostring(split(UserPrincipalName,'@',0)[0]), UPNSuffix = tostring(split(UserPrincipalName,'@',1)[0])\n| extend IPAddressFirst = tostring(IPAddresses[0])\n};\nlet aadSignin = aadFunc(\"SigninLogs\");\nlet aadNonInt = aadFunc(\"AADNonInteractiveUserSignInLogs\");\nunion isfuzzy=true aadSignin, aadNonInt\n",
"queryFrequency": "PT1H",
"queryPeriod": "P7D",
"severity": "Medium",
"status": "Available",
"subTechniques": [],
"suppressionDuration": "PT1H",
"suppressionEnabled": false,
"tactics": [
"CredentialAccess"
],
"techniques": [
"T1110"
],
"templateVersion": "2.0.2",
"triggerOperator": "GreaterThan",
"triggerThreshold": 0
},
"type": "Microsoft.OperationalInsights/workspaces/providers/alertRules"
}
]
}