Potential beaconing activity (ASIM Network Session schema)
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 pattern 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 | 1.1.2 |
Arm template | fcb9d75c-c3c1-4910-8697-f136bfef2363.json |
let querystarttime = 2d;
let queryendtime = 1d;
let TimeDeltaThreshold = 10;
let TotalEventsThreshold = 15;
let PercentBeaconThreshold = 80;
_Im_NetworkSession(starttime=ago(querystarttime), endtime=ago(queryendtime))
| where not(ipv4_is_private(DstIpAddr))
| 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
severity: Low
triggerThreshold: 0
query: |
let querystarttime = 2d;
let queryendtime = 1d;
let TimeDeltaThreshold = 10;
let TotalEventsThreshold = 15;
let PercentBeaconThreshold = 80;
_Im_NetworkSession(starttime=ago(querystarttime), endtime=ago(queryendtime))
| where not(ipv4_is_private(DstIpAddr))
| 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
customDetails:
TotalDstBytes: TotalDstBytes
DstPortNumber: DstPortNumber
FrequencyTime: MostFrequentTimeDeltaCount
FrequencyCount: TotalSrcBytes
queryFrequency: 1d
requiredDataConnectors:
- connectorId: AWSS3
dataTypes:
- AWSVPCFlow
- connectorId: MicrosoftThreatProtection
dataTypes:
- DeviceNetworkEvents
- connectorId: SecurityEvents
dataTypes:
- SecurityEvent
- connectorId: WindowsForwardedEvents
dataTypes:
- WindowsEvent
- connectorId: Zscaler
dataTypes:
- CommonSecurityLog
- connectorId: MicrosoftSysmonForLinux
dataTypes:
- Syslog
- connectorId: PaloAltoNetworks
dataTypes:
- CommonSecurityLog
- connectorId: AzureMonitor(VMInsights)
dataTypes:
- VMConnection
- connectorId: AzureFirewall
dataTypes:
- AzureDiagnostics
- connectorId: AzureNSG
dataTypes:
- AzureDiagnostics
- connectorId: CiscoASA
dataTypes:
- CommonSecurityLog
- connectorId: Corelight
dataTypes:
- Corelight_CL
- connectorId: AIVectraStream
dataTypes:
- VectraStream
- connectorId: CheckPoint
dataTypes:
- CommonSecurityLog
- connectorId: Fortinet
dataTypes:
- CommonSecurityLog
- connectorId: CiscoMeraki
dataTypes:
- Syslog
- CiscoMerakiNativePoller
id: fcb9d75c-c3c1-4910-8697-f136bfef2363
version: 1.1.2
name: Potential beaconing activity (ASIM Network Session schema)
kind: Scheduled
status: Available
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Network Session Essentials/Analytic Rules/PossibleBeaconingActivity.yaml
queryPeriod: 2d
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}}
relevantTechniques:
- T1071
- T1571
triggerOperator: gt
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
description: |
This rule identifies beaconing patterns from Network traffic logs based on recurrent frequency patterns. 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/).\<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'
entityMappings:
- entityType: IP
fieldMappings:
- identifier: Address
columnName: SrcIpAddr
- entityType: IP
fieldMappings:
- identifier: Address
columnName: DstIpAddr
{
"$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
"contentVersion": "1.0.0.0",
"parameters": {
"workspace": {
"type": "String"
}
},
"resources": [
{
"id": "[concat(resourceId('Microsoft.OperationalInsights/workspaces/providers', parameters('workspace'), 'Microsoft.SecurityInsights'),'/alertRules/fcb9d75c-c3c1-4910-8697-f136bfef2363')]",
"name": "[concat(parameters('workspace'),'/Microsoft.SecurityInsights/fcb9d75c-c3c1-4910-8697-f136bfef2363')]",
"type": "Microsoft.OperationalInsights/workspaces/providers/alertRules",
"kind": "Scheduled",
"apiVersion": "2022-11-01",
"properties": {
"displayName": "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 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/).\\<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",
"severity": "Low",
"enabled": true,
"query": "let querystarttime = 2d;\nlet queryendtime = 1d;\nlet TimeDeltaThreshold = 10;\nlet TotalEventsThreshold = 15;\nlet PercentBeaconThreshold = 80;\n_Im_NetworkSession(starttime=ago(querystarttime), endtime=ago(queryendtime))\n| where not(ipv4_is_private(DstIpAddr))\n| project TimeGenerated, SrcIpAddr, SrcPortNumber, DstIpAddr, DstPortNumber, DstBytes, SrcBytes\n| sort by SrcIpAddr asc,TimeGenerated asc, DstIpAddr asc, DstPortNumber asc\n| serialize\n| extend nextTimeGenerated = next(TimeGenerated, 1), nextSrcIpAddr = next(SrcIpAddr, 1)\n| extend TimeDeltainSeconds = datetime_diff('second',nextTimeGenerated,TimeGenerated)\n| where SrcIpAddr == nextSrcIpAddr\n//Whitelisting criteria/ threshold criteria\n| where TimeDeltainSeconds > TimeDeltaThreshold \n| project TimeGenerated, TimeDeltainSeconds, SrcIpAddr, SrcPortNumber, DstIpAddr, DstPortNumber, DstBytes, SrcBytes\n| summarize count(), sum(DstBytes), sum(SrcBytes), make_list(TimeDeltainSeconds) \nby TimeDeltainSeconds, bin(TimeGenerated, 1h), SrcIpAddr, DstIpAddr, DstPortNumber\n| summarize (MostFrequentTimeDeltaCount, MostFrequentTimeDeltainSeconds) = arg_max(count_, TimeDeltainSeconds), TotalEvents=sum(count_), TotalSrcBytes = sum(sum_SrcBytes), TotalDstBytes = sum(sum_DstBytes) \nby bin(TimeGenerated, 1h), SrcIpAddr, DstIpAddr, DstPortNumber\n| where TotalEvents > TotalEventsThreshold \n| extend BeaconPercent = MostFrequentTimeDeltaCount/toreal(TotalEvents) * 100\n| where BeaconPercent > PercentBeaconThreshold\n",
"queryFrequency": "P1D",
"queryPeriod": "P2D",
"triggerOperator": "GreaterThan",
"triggerThreshold": 0,
"suppressionDuration": "PT1H",
"suppressionEnabled": false,
"tactics": [
"CommandAndControl"
],
"techniques": [
"T1071",
"T1571"
],
"alertRuleTemplateName": "fcb9d75c-c3c1-4910-8697-f136bfef2363",
"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}}"
},
"customDetails": {
"FrequencyCount": "TotalSrcBytes",
"DstPortNumber": "DstPortNumber",
"FrequencyTime": "MostFrequentTimeDeltaCount",
"TotalDstBytes": "TotalDstBytes"
},
"entityMappings": [
{
"fieldMappings": [
{
"columnName": "SrcIpAddr",
"identifier": "Address"
}
],
"entityType": "IP"
},
{
"fieldMappings": [
{
"columnName": "DstIpAddr",
"identifier": "Address"
}
],
"entityType": "IP"
}
],
"tags": [
{
"ParentVersion": "1.0.0",
"ParentAlert": "https://github.com/Azure/Azure-Sentinel/blob/master/Detections/CommonSecurityLog/PaloAlto-NetworkBeaconing.yaml"
},
{
"Schema": "ASIMNetworkSession",
"SchemaVersion": "0.2.4"
}
],
"OriginalUri": "https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Network Session Essentials/Analytic Rules/PossibleBeaconingActivity.yaml",
"templateVersion": "1.1.2",
"status": "Available"
}
}
]
}