Potential beaconing activity ASIM Network Session schema

Back


Id	fcb9d75c-c3c1-4910-8697-f136bfef2363
Rulename	Potential beaconing activity (ASIM Network Session schema)
Description	This rule identifies beaconing patterns from Network traffic logs based on recurrent frequency patterns. Such potential outbound beaconing patterns to untrusted public networks should be investigated for any malware callbacks or data exfiltration attempts as discussed in this Blog.\<br><br> This analytic rule uses ASIM and supports any built-in or custom source that supports the ASIM NetworkSession schema
Severity	Low
Tactics	CommandAndControl
Techniques	T1071 T1571
Required data connectors	AIVectraStream AWSS3 AzureFirewall AzureMonitor(VMInsights) AzureNSG CheckPoint CiscoASA CiscoMeraki Corelight Fortinet MicrosoftSysmonForLinux MicrosoftThreatProtection PaloAltoNetworks SecurityEvents WindowsForwardedEvents Zscaler
Kind	Scheduled
Query frequency	1d
Query period	2d
Trigger threshold	0
Trigger operator	gt
Source Uri	https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Network Session Essentials/Analytic Rules/PossibleBeaconingActivity.yaml
Version	1.1.4
Arm template	fcb9d75c-c3c1-4910-8697-f136bfef2363.json

KQL

let querystarttime = 2d;
let queryendtime = 1d;
let TimeDeltaThreshold = 10;
let TotalEventsThreshold = 15;
let PercentBeaconThreshold = 80;
let LocalNetworks=dynamic(["169.254.0.0/16","127.0.0.0/8"]);
_Im_NetworkSession(starttime=ago(querystarttime), endtime=ago(queryendtime))
| where not(ipv4_is_private(DstIpAddr))
| where not (ipv4_is_in_any_range(DstIpAddr, LocalNetworks))
| project 
    TimeGenerated
    , SrcIpAddr
    , SrcPortNumber
    , DstIpAddr
    , DstPortNumber
    , DstBytes
    , SrcBytes
| sort by 
    SrcIpAddr asc
    , TimeGenerated asc
    , DstIpAddr asc
    , DstPortNumber asc
| serialize
| extend 
    nextTimeGenerated = next(TimeGenerated, 1)
    , nextSrcIpAddr = next(SrcIpAddr, 1)
| extend 
    TimeDeltainSeconds = datetime_diff('second', nextTimeGenerated, TimeGenerated)
| where SrcIpAddr == nextSrcIpAddr
//Whitelisting criteria/ threshold criteria
| where TimeDeltainSeconds > TimeDeltaThreshold 
| project
    TimeGenerated
    , TimeDeltainSeconds
    , SrcIpAddr
    , SrcPortNumber
    , DstIpAddr
    , DstPortNumber
    , DstBytes
    , SrcBytes
| summarize
    count()
    , sum(DstBytes)
    , sum(SrcBytes)
    , make_list(TimeDeltainSeconds) 
    by TimeDeltainSeconds
        , bin(TimeGenerated, 1h)
        , SrcIpAddr
        , DstIpAddr
        , DstPortNumber
| summarize
    (MostFrequentTimeDeltaCount, MostFrequentTimeDeltainSeconds) = arg_max(count_, TimeDeltainSeconds)
    , TotalEvents=sum(count_)
    , TotalSrcBytes = sum(sum_SrcBytes)
    , TotalDstBytes = sum(sum_DstBytes)
    by bin(TimeGenerated, 1h)
        , SrcIpAddr
        , DstIpAddr
        , DstPortNumber
| where TotalEvents > TotalEventsThreshold 
| extend BeaconPercent = MostFrequentTimeDeltaCount/toreal(TotalEvents) * 100
| where BeaconPercent > PercentBeaconThreshold

YAML

customDetails:
  DstPortNumber: DstPortNumber
  FrequencyCount: TotalSrcBytes
  TotalDstBytes: TotalDstBytes
  FrequencyTime: MostFrequentTimeDeltaCount
name: Potential beaconing activity (ASIM Network Session schema)
status: Available
triggerThreshold: 0
severity: Low
tactics:
- CommandAndControl
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Network Session Essentials/Analytic Rules/PossibleBeaconingActivity.yaml
entityMappings:
- entityType: IP
  fieldMappings:
  - columnName: SrcIpAddr
    identifier: Address
- entityType: IP
  fieldMappings:
  - columnName: DstIpAddr
    identifier: Address
queryPeriod: 2d
queryFrequency: 1d
version: 1.1.4
triggerOperator: gt
description: |
  This rule identifies beaconing patterns from Network traffic logs based on recurrent frequency patterns. Such potential outbound beaconing patterns to untrusted public networks should be investigated for any malware callbacks or data exfiltration attempts as discussed in this [Blog](https://medium.com/@HuntOperator/detect-beaconing-with-flare-elastic-stack-and-intrusion-detection-systems-110dc74e0c56).\<br><br>
  This analytic rule uses [ASIM](https://aka.ms/AboutASIM) and supports any built-in or custom source that supports the ASIM NetworkSession schema'  
query: |
  let querystarttime = 2d;
  let queryendtime = 1d;
  let TimeDeltaThreshold = 10;
  let TotalEventsThreshold = 15;
  let PercentBeaconThreshold = 80;
  let LocalNetworks=dynamic(["169.254.0.0/16","127.0.0.0/8"]);
  _Im_NetworkSession(starttime=ago(querystarttime), endtime=ago(queryendtime))
  | where not(ipv4_is_private(DstIpAddr))
  | where not (ipv4_is_in_any_range(DstIpAddr, LocalNetworks))
  | project 
      TimeGenerated
      , SrcIpAddr
      , SrcPortNumber
      , DstIpAddr
      , DstPortNumber
      , DstBytes
      , SrcBytes
  | sort by 
      SrcIpAddr asc
      , TimeGenerated asc
      , DstIpAddr asc
      , DstPortNumber asc
  | serialize
  | extend 
      nextTimeGenerated = next(TimeGenerated, 1)
      , nextSrcIpAddr = next(SrcIpAddr, 1)
  | extend 
      TimeDeltainSeconds = datetime_diff('second', nextTimeGenerated, TimeGenerated)
  | where SrcIpAddr == nextSrcIpAddr
  //Whitelisting criteria/ threshold criteria
  | where TimeDeltainSeconds > TimeDeltaThreshold 
  | project
      TimeGenerated
      , TimeDeltainSeconds
      , SrcIpAddr
      , SrcPortNumber
      , DstIpAddr
      , DstPortNumber
      , DstBytes
      , SrcBytes
  | summarize
      count()
      , sum(DstBytes)
      , sum(SrcBytes)
      , make_list(TimeDeltainSeconds) 
      by TimeDeltainSeconds
          , bin(TimeGenerated, 1h)
          , SrcIpAddr
          , DstIpAddr
          , DstPortNumber
  | summarize
      (MostFrequentTimeDeltaCount, MostFrequentTimeDeltainSeconds) = arg_max(count_, TimeDeltainSeconds)
      , TotalEvents=sum(count_)
      , TotalSrcBytes = sum(sum_SrcBytes)
      , TotalDstBytes = sum(sum_DstBytes)
      by bin(TimeGenerated, 1h)
          , SrcIpAddr
          , DstIpAddr
          , DstPortNumber
  | where TotalEvents > TotalEventsThreshold 
  | extend BeaconPercent = MostFrequentTimeDeltaCount/toreal(TotalEvents) * 100
  | where BeaconPercent > PercentBeaconThreshold  
relevantTechniques:
- T1071
- T1571
id: fcb9d75c-c3c1-4910-8697-f136bfef2363
requiredDataConnectors:
- dataTypes:
  - AWSVPCFlow
  connectorId: AWSS3
- dataTypes:
  - DeviceNetworkEvents
  connectorId: MicrosoftThreatProtection
- dataTypes:
  - SecurityEvent
  connectorId: SecurityEvents
- dataTypes:
  - WindowsEvent
  connectorId: WindowsForwardedEvents
- dataTypes:
  - CommonSecurityLog
  connectorId: Zscaler
- dataTypes:
  - Syslog
  connectorId: MicrosoftSysmonForLinux
- dataTypes:
  - CommonSecurityLog
  connectorId: PaloAltoNetworks
- dataTypes:
  - VMConnection
  connectorId: AzureMonitor(VMInsights)
- dataTypes:
  - AzureDiagnostics
  connectorId: AzureFirewall
- dataTypes:
  - AzureDiagnostics
  connectorId: AzureNSG
- dataTypes:
  - CommonSecurityLog
  connectorId: CiscoASA
- dataTypes:
  - Corelight_CL
  connectorId: Corelight
- dataTypes:
  - VectraStream
  connectorId: AIVectraStream
- dataTypes:
  - CommonSecurityLog
  connectorId: CheckPoint
- dataTypes:
  - CommonSecurityLog
  connectorId: Fortinet
- dataTypes:
  - Syslog
  - CiscoMerakiNativePoller
  connectorId: CiscoMeraki
tags:
- ParentAlert: https://github.com/Azure/Azure-Sentinel/blob/master/Detections/CommonSecurityLog/PaloAlto-NetworkBeaconing.yaml
  ParentVersion: 1.0.0
- Schema: ASIMNetworkSession
  SchemaVersion: 0.2.4
alertDetailsOverride:
  alertDisplayNameFormat: Potential beaconing from {{SrcIpAddr}} to {{DstIpAddr}}
  alertDescriptionFormat: Potential beaconing pattern from a client at address {{SrcIpAddr}} to a server at address {{DstIpAddr}} over port {{DstPortNumber}} identified. Such potential outbound beaconing pattern to untrusted public networks should be investigated for any malware callbacks or data exfiltration attempts as discussed in this [Blog](http://www.austintaylor.io/detect/beaconing/intrusion/detection/system/command/control/flare/elastic/stack/2017/06/10/detect-beaconing-with-flare-elasticsearch-and-intrusion-detection-systems/). The recurring frequency, reported as FrequencyTime in the custom details, and the total transferred volume reported as TotalDstBytes in the custom details, can help to determine the significance of this incident.
kind: Scheduled

ARM

{
  "$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/fcb9d75c-c3c1-4910-8697-f136bfef2363')]",
      "kind": "Scheduled",
      "name": "[concat(parameters('workspace'),'/Microsoft.SecurityInsights/fcb9d75c-c3c1-4910-8697-f136bfef2363')]",
      "properties": {
        "alertDetailsOverride": {
          "alertDescriptionFormat": "Potential beaconing pattern from a client at address {{SrcIpAddr}} to a server at address {{DstIpAddr}} over port {{DstPortNumber}} identified. Such potential outbound beaconing pattern to untrusted public networks should be investigated for any malware callbacks or data exfiltration attempts as discussed in this [Blog](http://www.austintaylor.io/detect/beaconing/intrusion/detection/system/command/control/flare/elastic/stack/2017/06/10/detect-beaconing-with-flare-elasticsearch-and-intrusion-detection-systems/). The recurring frequency, reported as FrequencyTime in the custom details, and the total transferred volume reported as TotalDstBytes in the custom details, can help to determine the significance of this incident.",
          "alertDisplayNameFormat": "Potential beaconing from {{SrcIpAddr}} to {{DstIpAddr}}"
        },
        "alertRuleTemplateName": "fcb9d75c-c3c1-4910-8697-f136bfef2363",
        "customDetails": {
          "DstPortNumber": "DstPortNumber",
          "FrequencyCount": "TotalSrcBytes",
          "FrequencyTime": "MostFrequentTimeDeltaCount",
          "TotalDstBytes": "TotalDstBytes"
        },
        "description": "This rule identifies beaconing patterns from Network traffic logs based on recurrent frequency patterns. Such potential outbound beaconing patterns to untrusted public networks should be investigated for any malware callbacks or data exfiltration attempts as discussed in this [Blog](https://medium.com/@HuntOperator/detect-beaconing-with-flare-elastic-stack-and-intrusion-detection-systems-110dc74e0c56).\\<br><br>\nThis analytic rule uses [ASIM](https://aka.ms/AboutASIM) and supports any built-in or custom source that supports the ASIM NetworkSession schema'\n",
        "displayName": "Potential beaconing activity (ASIM Network Session schema)",
        "enabled": true,
        "entityMappings": [
          {
            "entityType": "IP",
            "fieldMappings": [
              {
                "columnName": "SrcIpAddr",
                "identifier": "Address"
              }
            ]
          },
          {
            "entityType": "IP",
            "fieldMappings": [
              {
                "columnName": "DstIpAddr",
                "identifier": "Address"
              }
            ]
          }
        ],
        "OriginalUri": "https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Network Session Essentials/Analytic Rules/PossibleBeaconingActivity.yaml",
        "query": "let querystarttime = 2d;\nlet queryendtime = 1d;\nlet TimeDeltaThreshold = 10;\nlet TotalEventsThreshold = 15;\nlet PercentBeaconThreshold = 80;\nlet LocalNetworks=dynamic([\"169.254.0.0/16\",\"127.0.0.0/8\"]);\n_Im_NetworkSession(starttime=ago(querystarttime), endtime=ago(queryendtime))\n| where not(ipv4_is_private(DstIpAddr))\n| where not (ipv4_is_in_any_range(DstIpAddr, LocalNetworks))\n| project \n    TimeGenerated\n    , SrcIpAddr\n    , SrcPortNumber\n    , DstIpAddr\n    , DstPortNumber\n    , DstBytes\n    , SrcBytes\n| sort by \n    SrcIpAddr asc\n    , TimeGenerated asc\n    , DstIpAddr asc\n    , DstPortNumber asc\n| serialize\n| extend \n    nextTimeGenerated = next(TimeGenerated, 1)\n    , nextSrcIpAddr = next(SrcIpAddr, 1)\n| extend \n    TimeDeltainSeconds = datetime_diff('second', nextTimeGenerated, TimeGenerated)\n| where SrcIpAddr == nextSrcIpAddr\n//Whitelisting criteria/ threshold criteria\n| where TimeDeltainSeconds > TimeDeltaThreshold \n| project\n    TimeGenerated\n    , TimeDeltainSeconds\n    , SrcIpAddr\n    , SrcPortNumber\n    , DstIpAddr\n    , DstPortNumber\n    , DstBytes\n    , SrcBytes\n| summarize\n    count()\n    , sum(DstBytes)\n    , sum(SrcBytes)\n    , make_list(TimeDeltainSeconds) \n    by TimeDeltainSeconds\n        , bin(TimeGenerated, 1h)\n        , SrcIpAddr\n        , DstIpAddr\n        , DstPortNumber\n| summarize\n    (MostFrequentTimeDeltaCount, MostFrequentTimeDeltainSeconds) = arg_max(count_, TimeDeltainSeconds)\n    , TotalEvents=sum(count_)\n    , TotalSrcBytes = sum(sum_SrcBytes)\n    , TotalDstBytes = sum(sum_DstBytes)\n    by bin(TimeGenerated, 1h)\n        , SrcIpAddr\n        , DstIpAddr\n        , DstPortNumber\n| where TotalEvents > TotalEventsThreshold \n| extend BeaconPercent = MostFrequentTimeDeltaCount/toreal(TotalEvents) * 100\n| where BeaconPercent > PercentBeaconThreshold\n",
        "queryFrequency": "P1D",
        "queryPeriod": "P2D",
        "severity": "Low",
        "status": "Available",
        "suppressionDuration": "PT1H",
        "suppressionEnabled": false,
        "tactics": [
          "CommandAndControl"
        ],
        "tags": [
          {
            "ParentAlert": "https://github.com/Azure/Azure-Sentinel/blob/master/Detections/CommonSecurityLog/PaloAlto-NetworkBeaconing.yaml",
            "ParentVersion": "1.0.0"
          },
          {
            "Schema": "ASIMNetworkSession",
            "SchemaVersion": "0.2.4"
          }
        ],
        "techniques": [
          "T1071",
          "T1571"
        ],
        "templateVersion": "1.1.4",
        "triggerOperator": "GreaterThan",
        "triggerThreshold": 0
      },
      "type": "Microsoft.OperationalInsights/workspaces/providers/alertRules"
    }
  ]
}