Microsoft Sentinel Analytic Rules
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Suspicious AWS EC2 Compute Resource Deployments

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Id9e457dc4-81f0-4d25-bc37-a5fa4a17946a
RulenameSuspicious AWS EC2 Compute Resource Deployments
DescriptionThis detection focused on Suspicious deployment of AWS EC2 resource (virtual machine) scale sets was detected. This behavior might indicate that the threat actor is deploying computing resources for cryptocurrency mining activities.This detection centers around identifying suspicious instances of AWS EC2 resource deployment, particularly scale sets. Such behavior raises concerns of potential threat actor involvement, potentially indicative of efforts to deploy computing resources for the purpose of cryptocurrency mining activities.
SeverityMedium
TacticsImpact
TechniquesT1496
Required data connectorsAWS
KindScheduled
Query frequency1d
Query period1d
Trigger threshold0
Trigger operatorgt
Source Urihttps://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Amazon Web Services/Analytic Rules/SuspiciousAWSEC2ComputeResourceDeployments.yaml
Version1.0.1
Arm template9e457dc4-81f0-4d25-bc37-a5fa4a17946a.json
Deploy To Azure
// Retrieve AWS CloudTrail events generated within the last day
AWSCloudTrail
// Filter events related to instance creation
| where EventName =~ "RunInstances"
// Exclude events with error messages
| where isempty(ErrorMessage)
// Extract the event source type
| extend EventSourceSplit = split(EventSource, ".")
| extend Type = tostring(EventSourceSplit[0])
// Extract instance-related details from the event data
| extend instance = tostring(parse_json(RequestParameters).instanceType),platform = tostring(parse_json(ResponseElements).instancesSet.items[0].platform)
// Determine the operating system platform
| extend OSplatform = iff(isempty(platform), tostring("Linux"), platform),CPU = tostring(parse_json(ResponseElements).instancesSet.items[0].cpuOptions),core = toint(parse_json(ResponseElements).instancesSet.items[0].cpuOptions.coreCount),corThread = toint(parse_json(ResponseElements).instancesSet.items[0].cpuOptions.threadsPerCore),InstanceId = tostring(parse_json(ResponseElements).instancesSet.items[0].instanceId)
// Filter out instances with empty core values
| where isnotempty(core)
// Calculate the total compute based on core and thread counts
| extend totalCorecompute = core * corThread
| extend UserIdentityArn = iif(isempty(UserIdentityArn), tostring(parse_json(Resources)[0].ARN), UserIdentityArn)
| extend UserName = tostring(split(UserIdentityArn, '/')[-1])
| extend AccountName = case( UserIdentityPrincipalid == "Anonymous", "Anonymous", isempty(UserIdentityUserName), UserName, UserIdentityUserName)
| extend AccountName = iif(AccountName contains "@", tostring(split(AccountName, '@', 0)[0]), AccountName),
  AccountUPNSuffix = iif(AccountName contains "@", tostring(split(AccountName, '@', 1)[0]), "")
// Summarize relevant information for analysis
| summarize Start= min(TimeGenerated),
  end=   max(TimeGenerated),
  totalgpu= sum(totalCorecompute)
  by SourceIpAddress, RecipientAccountId, AccountName, AccountUPNSuffix, UserIdentityArn, UserAgent
// Filter results based on total GPU compute and time duration
| where totalgpu > 800
| where datetime_diff('hour', end, Start) < 8
customDetails:
  SourceIpAddress: SourceIpAddress
  UserAgent: UserAgent
  AWSUser: UserIdentityArn
kind: Scheduled
triggerThreshold: 0
relevantTechniques:
- T1496
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Amazon Web Services/Analytic Rules/SuspiciousAWSEC2ComputeResourceDeployments.yaml
requiredDataConnectors:
- dataTypes:
  - AWSCloudTrail
  connectorId: AWS
queryPeriod: 1d
tactics:
- Impact
severity: Medium
triggerOperator: gt
description: |
    'This detection focused on Suspicious deployment of AWS EC2 resource (virtual machine) scale sets was detected. This behavior might indicate that the threat actor is deploying computing resources for cryptocurrency mining activities.This detection centers around identifying suspicious instances of AWS EC2 resource deployment, particularly scale sets. Such behavior raises concerns of potential threat actor involvement, potentially indicative of efforts to deploy computing resources for the purpose of cryptocurrency mining activities.
query: |
  // Retrieve AWS CloudTrail events generated within the last day
  AWSCloudTrail
  // Filter events related to instance creation
  | where EventName =~ "RunInstances"
  // Exclude events with error messages
  | where isempty(ErrorMessage)
  // Extract the event source type
  | extend EventSourceSplit = split(EventSource, ".")
  | extend Type = tostring(EventSourceSplit[0])
  // Extract instance-related details from the event data
  | extend instance = tostring(parse_json(RequestParameters).instanceType),platform = tostring(parse_json(ResponseElements).instancesSet.items[0].platform)
  // Determine the operating system platform
  | extend OSplatform = iff(isempty(platform), tostring("Linux"), platform),CPU = tostring(parse_json(ResponseElements).instancesSet.items[0].cpuOptions),core = toint(parse_json(ResponseElements).instancesSet.items[0].cpuOptions.coreCount),corThread = toint(parse_json(ResponseElements).instancesSet.items[0].cpuOptions.threadsPerCore),InstanceId = tostring(parse_json(ResponseElements).instancesSet.items[0].instanceId)
  // Filter out instances with empty core values
  | where isnotempty(core)
  // Calculate the total compute based on core and thread counts
  | extend totalCorecompute = core * corThread
  | extend UserIdentityArn = iif(isempty(UserIdentityArn), tostring(parse_json(Resources)[0].ARN), UserIdentityArn)
  | extend UserName = tostring(split(UserIdentityArn, '/')[-1])
  | extend AccountName = case( UserIdentityPrincipalid == "Anonymous", "Anonymous", isempty(UserIdentityUserName), UserName, UserIdentityUserName)
  | extend AccountName = iif(AccountName contains "@", tostring(split(AccountName, '@', 0)[0]), AccountName),
    AccountUPNSuffix = iif(AccountName contains "@", tostring(split(AccountName, '@', 1)[0]), "")
  // Summarize relevant information for analysis
  | summarize Start= min(TimeGenerated),
    end=   max(TimeGenerated),
    totalgpu= sum(totalCorecompute)
    by SourceIpAddress, RecipientAccountId, AccountName, AccountUPNSuffix, UserIdentityArn, UserAgent
  // Filter results based on total GPU compute and time duration
  | where totalgpu > 800
  | where datetime_diff('hour', end, Start) < 8
name: Suspicious AWS EC2 Compute Resource Deployments
version: 1.0.1
id: 9e457dc4-81f0-4d25-bc37-a5fa4a17946a
queryFrequency: 1d
entityMappings:
- entityType: Account
  fieldMappings:
  - columnName: AccountName
    identifier: Name
  - columnName: AccountUPNSuffix
    identifier: UPNSuffix
  - columnName: RecipientAccountId
    identifier: CloudAppAccountId
- entityType: IP
  fieldMappings:
  - columnName: SourceIpAddress
    identifier: Address
{
  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
  "contentVersion": "1.0.0.0",
  "parameters": {
    "workspace": {
      "type": "String"
    }
  },
  "resources": [
    {
      "apiVersion": "2023-02-01-preview",
      "id": "[concat(resourceId('Microsoft.OperationalInsights/workspaces/providers', parameters('workspace'), 'Microsoft.SecurityInsights'),'/alertRules/9e457dc4-81f0-4d25-bc37-a5fa4a17946a')]",
      "kind": "Scheduled",
      "name": "[concat(parameters('workspace'),'/Microsoft.SecurityInsights/9e457dc4-81f0-4d25-bc37-a5fa4a17946a')]",
      "properties": {
        "alertRuleTemplateName": "9e457dc4-81f0-4d25-bc37-a5fa4a17946a",
        "customDetails": {
          "AWSUser": "UserIdentityArn",
          "SourceIpAddress": "SourceIpAddress",
          "UserAgent": "UserAgent"
        },
        "description": "'This detection focused on Suspicious deployment of AWS EC2 resource (virtual machine) scale sets was detected. This behavior might indicate that the threat actor is deploying computing resources for cryptocurrency mining activities.This detection centers around identifying suspicious instances of AWS EC2 resource deployment, particularly scale sets. Such behavior raises concerns of potential threat actor involvement, potentially indicative of efforts to deploy computing resources for the purpose of cryptocurrency mining activities.\n",
        "displayName": "Suspicious AWS EC2 Compute Resource Deployments",
        "enabled": true,
        "entityMappings": [
          {
            "entityType": "Account",
            "fieldMappings": [
              {
                "columnName": "AccountName",
                "identifier": "Name"
              },
              {
                "columnName": "AccountUPNSuffix",
                "identifier": "UPNSuffix"
              },
              {
                "columnName": "RecipientAccountId",
                "identifier": "CloudAppAccountId"
              }
            ]
          },
          {
            "entityType": "IP",
            "fieldMappings": [
              {
                "columnName": "SourceIpAddress",
                "identifier": "Address"
              }
            ]
          }
        ],
        "OriginalUri": "https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Amazon Web Services/Analytic Rules/SuspiciousAWSEC2ComputeResourceDeployments.yaml",
        "query": "// Retrieve AWS CloudTrail events generated within the last day\nAWSCloudTrail\n// Filter events related to instance creation\n| where EventName =~ \"RunInstances\"\n// Exclude events with error messages\n| where isempty(ErrorMessage)\n// Extract the event source type\n| extend EventSourceSplit = split(EventSource, \".\")\n| extend Type = tostring(EventSourceSplit[0])\n// Extract instance-related details from the event data\n| extend instance = tostring(parse_json(RequestParameters).instanceType),platform = tostring(parse_json(ResponseElements).instancesSet.items[0].platform)\n// Determine the operating system platform\n| extend OSplatform = iff(isempty(platform), tostring(\"Linux\"), platform),CPU = tostring(parse_json(ResponseElements).instancesSet.items[0].cpuOptions),core = toint(parse_json(ResponseElements).instancesSet.items[0].cpuOptions.coreCount),corThread = toint(parse_json(ResponseElements).instancesSet.items[0].cpuOptions.threadsPerCore),InstanceId = tostring(parse_json(ResponseElements).instancesSet.items[0].instanceId)\n// Filter out instances with empty core values\n| where isnotempty(core)\n// Calculate the total compute based on core and thread counts\n| extend totalCorecompute = core * corThread\n| extend UserIdentityArn = iif(isempty(UserIdentityArn), tostring(parse_json(Resources)[0].ARN), UserIdentityArn)\n| extend UserName = tostring(split(UserIdentityArn, '/')[-1])\n| extend AccountName = case( UserIdentityPrincipalid == \"Anonymous\", \"Anonymous\", isempty(UserIdentityUserName), UserName, UserIdentityUserName)\n| extend AccountName = iif(AccountName contains \"@\", tostring(split(AccountName, '@', 0)[0]), AccountName),\n  AccountUPNSuffix = iif(AccountName contains \"@\", tostring(split(AccountName, '@', 1)[0]), \"\")\n// Summarize relevant information for analysis\n| summarize Start= min(TimeGenerated),\n  end=   max(TimeGenerated),\n  totalgpu= sum(totalCorecompute)\n  by SourceIpAddress, RecipientAccountId, AccountName, AccountUPNSuffix, UserIdentityArn, UserAgent\n// Filter results based on total GPU compute and time duration\n| where totalgpu > 800\n| where datetime_diff('hour', end, Start) < 8\n",
        "queryFrequency": "P1D",
        "queryPeriod": "P1D",
        "severity": "Medium",
        "suppressionDuration": "PT1H",
        "suppressionEnabled": false,
        "tactics": [
          "Impact"
        ],
        "techniques": [
          "T1496"
        ],
        "templateVersion": "1.0.1",
        "triggerOperator": "GreaterThan",
        "triggerThreshold": 0
      },
      "type": "Microsoft.OperationalInsights/workspaces/providers/alertRules"
    }
  ]
}