Potential DGA(Domain Generation Algorithm) detected via Repetitive Failures - Anomaly based (ASIM DNS Solution)

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Id	01191239-274e-43c9-b154-3a042692af06
Rulename	Potential DGA(Domain Generation Algorithm) detected via Repetitive Failures - Anomaly based (ASIM DNS Solution)
Description	This rule makes use of the series decompose anomaly method to detect clients with a high NXDomain response count, which could be indicative of a DGA (cycling through possible C2 domains where most C2s are not live). An alert is generated when new IP address DNS activity is identified as an outlier when compared to the baseline, indicating a recurring pattern. It utilizes ASIM normalization and is applied to any source that supports the ASIM DNS schema.
Severity	Medium
Tactics	CommandAndControl
Techniques	T1568 T1008
Kind	Scheduled
Query frequency	1d
Query period	14d
Trigger threshold	0
Trigger operator	gt
Source Uri	https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/PotentialDGADetectedviaRepetitiveFailuresAnomalyBased.yaml
Version	1.0.2
Arm template	01191239-274e-43c9-b154-3a042692af06.json

KQL

let threshold = 2.5;
let min_t = ago(14d);
let max_t = now();
let timeframe = 1d;
// calculate avg. eps(events per second)
let eps = materialize (_Im_Dns
  | project TimeGenerated
  | where TimeGenerated > ago(5m)
  | count
  | extend Count = Count / 300);
let maxSummarizedTime = toscalar (
  union isfuzzy=true 
      (
      DNS_Summarized_Logs_ip_CL 
      | where EventTime_t >= min_t
      | summarize max_TimeGenerated=max(EventTime_t)
      | extend max_TimeGenerated = datetime_add('hour', 1, max_TimeGenerated)
      ),
      (
      print(min_t)
      | project max_TimeGenerated = print_0
      )
  | summarize maxTimeGenerated = max(max_TimeGenerated) 
  );
let summarizationexist = materialize(
  union isfuzzy=true 
      (
      DNS_Summarized_Logs_ip_CL
      | where EventTime_t > ago(1d) 
      | project v = int(2)
      ),
      (
      print int(1) 
      | project v = print_0
      )
  | summarize maxv = max(v)
  | extend sumexist = (maxv > 1)
  );
let allData = union isfuzzy=true
      (
      (datatable(exists: int, sumexist: bool)[1, false]
      | where toscalar(eps) > 1000
      | join (summarizationexist) on sumexist)
      | join (
          _Im_Dns(responsecodename='NXDOMAIN', starttime=todatetime(ago(2d)), endtime=now())
          | where TimeGenerated > maxSummarizedTime
          | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated, 1h)
          | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)
          )
          on exists
      | project-away exists, maxv, sum*
      ),
      (
      (datatable(exists: int, sumexist: bool)[1, false]
      | where toscalar(eps) between (501 .. 1000)
      | join (summarizationexist) on sumexist)
      | join (
          _Im_Dns(responsecodename='NXDOMAIN', starttime=todatetime(ago(3d)), endtime=now())
          | where TimeGenerated > maxSummarizedTime
          | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated, 1h)
          | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)
          )
          on exists
      | project-away exists, maxv, sum*
      ),
      (
      (datatable(exists: int, sumexist: bool)[1, false]
      | where toscalar(eps) <= 500
      | join (summarizationexist) on sumexist)
      | join (
          _Im_Dns(responsecodename='NXDOMAIN', starttime=todatetime(ago(4d)), endtime=now())
          | where TimeGenerated > maxSummarizedTime
          | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated, 1h)
          | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)
          )
          on exists
      | project-away exists, maxv, sum*
      ),
      (
      DNS_Summarized_Logs_ip_CL
      | where EventTime_t > min_t and EventResultDetails_s == 'NXDOMAIN'
      | project-rename
          SrcIpAddr=SrcIpAddr_s,
          DnsQuery=DnsQuery_s,
          Count=count__d,
          EventTime=EventTime_t
      | extend Count = toint(Count)
      );
allData
| make-series QueryCount=dcount(DnsQuery) on EventTime from min_t to max_t step timeframe by SrcIpAddr
// include calculated Anomalies, Score and Baseline
| extend (anomalies, score, baseline) = series_decompose_anomalies(QueryCount, threshold, -1, 'linefit')
| mv-expand anomalies, score, baseline, EventTime, QueryCount
| extend
  anomalies = toint(anomalies),
  score = toint(score),
  baseline = toint(baseline),
  EventTime = todatetime(EventTime),
  Total = tolong(QueryCount)
| where EventTime >= ago(timeframe)
| where score >= threshold * 2
// Join allData to include DnsQuery details
| join kind=inner(allData
  | where TimeGenerated >= ago(timeframe)
  | summarize DNSQueries = make_set(DnsQuery, 1000) by SrcIpAddr)
  on SrcIpAddr
| project-away SrcIpAddr1

YAML

triggerOperator: gt
version: 1.0.2
query: |
  let threshold = 2.5;
  let min_t = ago(14d);
  let max_t = now();
  let timeframe = 1d;
  // calculate avg. eps(events per second)
  let eps = materialize (_Im_Dns
    | project TimeGenerated
    | where TimeGenerated > ago(5m)
    | count
    | extend Count = Count / 300);
  let maxSummarizedTime = toscalar (
    union isfuzzy=true 
        (
        DNS_Summarized_Logs_ip_CL 
        | where EventTime_t >= min_t
        | summarize max_TimeGenerated=max(EventTime_t)
        | extend max_TimeGenerated = datetime_add('hour', 1, max_TimeGenerated)
        ),
        (
        print(min_t)
        | project max_TimeGenerated = print_0
        )
    | summarize maxTimeGenerated = max(max_TimeGenerated) 
    );
  let summarizationexist = materialize(
    union isfuzzy=true 
        (
        DNS_Summarized_Logs_ip_CL
        | where EventTime_t > ago(1d) 
        | project v = int(2)
        ),
        (
        print int(1) 
        | project v = print_0
        )
    | summarize maxv = max(v)
    | extend sumexist = (maxv > 1)
    );
  let allData = union isfuzzy=true
        (
        (datatable(exists: int, sumexist: bool)[1, false]
        | where toscalar(eps) > 1000
        | join (summarizationexist) on sumexist)
        | join (
            _Im_Dns(responsecodename='NXDOMAIN', starttime=todatetime(ago(2d)), endtime=now())
            | where TimeGenerated > maxSummarizedTime
            | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated, 1h)
            | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)
            )
            on exists
        | project-away exists, maxv, sum*
        ),
        (
        (datatable(exists: int, sumexist: bool)[1, false]
        | where toscalar(eps) between (501 .. 1000)
        | join (summarizationexist) on sumexist)
        | join (
            _Im_Dns(responsecodename='NXDOMAIN', starttime=todatetime(ago(3d)), endtime=now())
            | where TimeGenerated > maxSummarizedTime
            | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated, 1h)
            | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)
            )
            on exists
        | project-away exists, maxv, sum*
        ),
        (
        (datatable(exists: int, sumexist: bool)[1, false]
        | where toscalar(eps) <= 500
        | join (summarizationexist) on sumexist)
        | join (
            _Im_Dns(responsecodename='NXDOMAIN', starttime=todatetime(ago(4d)), endtime=now())
            | where TimeGenerated > maxSummarizedTime
            | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated, 1h)
            | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)
            )
            on exists
        | project-away exists, maxv, sum*
        ),
        (
        DNS_Summarized_Logs_ip_CL
        | where EventTime_t > min_t and EventResultDetails_s == 'NXDOMAIN'
        | project-rename
            SrcIpAddr=SrcIpAddr_s,
            DnsQuery=DnsQuery_s,
            Count=count__d,
            EventTime=EventTime_t
        | extend Count = toint(Count)
        );
  allData
  | make-series QueryCount=dcount(DnsQuery) on EventTime from min_t to max_t step timeframe by SrcIpAddr
  // include calculated Anomalies, Score and Baseline
  | extend (anomalies, score, baseline) = series_decompose_anomalies(QueryCount, threshold, -1, 'linefit')
  | mv-expand anomalies, score, baseline, EventTime, QueryCount
  | extend
    anomalies = toint(anomalies),
    score = toint(score),
    baseline = toint(baseline),
    EventTime = todatetime(EventTime),
    Total = tolong(QueryCount)
  | where EventTime >= ago(timeframe)
  | where score >= threshold * 2
  // Join allData to include DnsQuery details
  | join kind=inner(allData
    | where TimeGenerated >= ago(timeframe)
    | summarize DNSQueries = make_set(DnsQuery, 1000) by SrcIpAddr)
    on SrcIpAddr
  | project-away SrcIpAddr1  
status: Available
entityMappings:
- entityType: IP
  fieldMappings:
  - columnName: SrcIpAddr
    identifier: Address
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/PotentialDGADetectedviaRepetitiveFailuresAnomalyBased.yaml
queryFrequency: 1d
requiredDataConnectors: []
tags:
- Schema: ASimDns
  SchemaVersion: 0.1.6
name: Potential DGA(Domain Generation Algorithm) detected via Repetitive Failures - Anomaly based (ASIM DNS Solution)
queryPeriod: 14d
severity: Medium
eventGroupingSettings:
  aggregationKind: AlertPerResult
kind: Scheduled
tactics:
- CommandAndControl
id: 01191239-274e-43c9-b154-3a042692af06
description: |
    'This rule makes use of the series decompose anomaly method to detect clients with a high NXDomain response count, which could be indicative of a DGA (cycling through possible C2 domains where most C2s are not live). An alert is generated when new IP address DNS activity is identified as an outlier when compared to the baseline, indicating a recurring pattern. It utilizes [ASIM](https://aka.ms/AboutASIM) normalization and is applied to any source that supports the ASIM DNS schema.'
relevantTechniques:
- T1568
- T1008
customDetails:
  Total: Total
  baseline: baseline
  DNSQueries: DNSQueries
  AnomalyScore: score
triggerThreshold: 0
alertDetailsOverride:
  alertDescriptionFormat: |-
    Client has been identified with high NXDomain count which could be indicative of a DGA (cycling through possible C2 domains where most C2s are not live). This client is found to be communicating with multiple Domains which do not exist.

    Baseline Domain or DNS query count from this client: '{{baseline}}'

    Current Domain or DNS query count from this client: '{{Total}}'

    DNS queries requested by this client inlcude: '{{DNSQueries}}'    
  alertDisplayNameFormat: "[Anomaly] Potential DGA (Domain Generation Algorithm) originating from client IP: '{{SrcIpAddr}}' has been detected."

ARM

{
  "$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/01191239-274e-43c9-b154-3a042692af06')]",
      "name": "[concat(parameters('workspace'),'/Microsoft.SecurityInsights/01191239-274e-43c9-b154-3a042692af06')]",
      "type": "Microsoft.OperationalInsights/workspaces/providers/alertRules",
      "kind": "Scheduled",
      "apiVersion": "2022-11-01-preview",
      "properties": {
        "displayName": "Potential DGA(Domain Generation Algorithm) detected via Repetitive Failures - Anomaly based (ASIM DNS Solution)",
        "description": "'This rule makes use of the series decompose anomaly method to detect clients with a high NXDomain response count, which could be indicative of a DGA (cycling through possible C2 domains where most C2s are not live). An alert is generated when new IP address DNS activity is identified as an outlier when compared to the baseline, indicating a recurring pattern. It utilizes [ASIM](https://aka.ms/AboutASIM) normalization and is applied to any source that supports the ASIM DNS schema.'\n",
        "severity": "Medium",
        "enabled": true,
        "query": "let threshold = 2.5;\nlet min_t = ago(14d);\nlet max_t = now();\nlet timeframe = 1d;\n// calculate avg. eps(events per second)\nlet eps = materialize (_Im_Dns\n  | project TimeGenerated\n  | where TimeGenerated > ago(5m)\n  | count\n  | extend Count = Count / 300);\nlet maxSummarizedTime = toscalar (\n  union isfuzzy=true \n      (\n      DNS_Summarized_Logs_ip_CL \n      | where EventTime_t >= min_t\n      | summarize max_TimeGenerated=max(EventTime_t)\n      | extend max_TimeGenerated = datetime_add('hour', 1, max_TimeGenerated)\n      ),\n      (\n      print(min_t)\n      | project max_TimeGenerated = print_0\n      )\n  | summarize maxTimeGenerated = max(max_TimeGenerated) \n  );\nlet summarizationexist = materialize(\n  union isfuzzy=true \n      (\n      DNS_Summarized_Logs_ip_CL\n      | where EventTime_t > ago(1d) \n      | project v = int(2)\n      ),\n      (\n      print int(1) \n      | project v = print_0\n      )\n  | summarize maxv = max(v)\n  | extend sumexist = (maxv > 1)\n  );\nlet allData = union isfuzzy=true\n      (\n      (datatable(exists: int, sumexist: bool)[1, false]\n      | where toscalar(eps) > 1000\n      | join (summarizationexist) on sumexist)\n      | join (\n          _Im_Dns(responsecodename='NXDOMAIN', starttime=todatetime(ago(2d)), endtime=now())\n          | where TimeGenerated > maxSummarizedTime\n          | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated, 1h)\n          | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)\n          )\n          on exists\n      | project-away exists, maxv, sum*\n      ),\n      (\n      (datatable(exists: int, sumexist: bool)[1, false]\n      | where toscalar(eps) between (501 .. 1000)\n      | join (summarizationexist) on sumexist)\n      | join (\n          _Im_Dns(responsecodename='NXDOMAIN', starttime=todatetime(ago(3d)), endtime=now())\n          | where TimeGenerated > maxSummarizedTime\n          | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated, 1h)\n          | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)\n          )\n          on exists\n      | project-away exists, maxv, sum*\n      ),\n      (\n      (datatable(exists: int, sumexist: bool)[1, false]\n      | where toscalar(eps) <= 500\n      | join (summarizationexist) on sumexist)\n      | join (\n          _Im_Dns(responsecodename='NXDOMAIN', starttime=todatetime(ago(4d)), endtime=now())\n          | where TimeGenerated > maxSummarizedTime\n          | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated, 1h)\n          | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)\n          )\n          on exists\n      | project-away exists, maxv, sum*\n      ),\n      (\n      DNS_Summarized_Logs_ip_CL\n      | where EventTime_t > min_t and EventResultDetails_s == 'NXDOMAIN'\n      | project-rename\n          SrcIpAddr=SrcIpAddr_s,\n          DnsQuery=DnsQuery_s,\n          Count=count__d,\n          EventTime=EventTime_t\n      | extend Count = toint(Count)\n      );\nallData\n| make-series QueryCount=dcount(DnsQuery) on EventTime from min_t to max_t step timeframe by SrcIpAddr\n// include calculated Anomalies, Score and Baseline\n| extend (anomalies, score, baseline) = series_decompose_anomalies(QueryCount, threshold, -1, 'linefit')\n| mv-expand anomalies, score, baseline, EventTime, QueryCount\n| extend\n  anomalies = toint(anomalies),\n  score = toint(score),\n  baseline = toint(baseline),\n  EventTime = todatetime(EventTime),\n  Total = tolong(QueryCount)\n| where EventTime >= ago(timeframe)\n| where score >= threshold * 2\n// Join allData to include DnsQuery details\n| join kind=inner(allData\n  | where TimeGenerated >= ago(timeframe)\n  | summarize DNSQueries = make_set(DnsQuery, 1000) by SrcIpAddr)\n  on SrcIpAddr\n| project-away SrcIpAddr1\n",
        "queryFrequency": "P1D",
        "queryPeriod": "P14D",
        "triggerOperator": "GreaterThan",
        "triggerThreshold": 0,
        "suppressionDuration": "PT1H",
        "suppressionEnabled": false,
        "tactics": [
          "CommandAndControl"
        ],
        "techniques": [
          "T1568",
          "T1008"
        ],
        "alertRuleTemplateName": "01191239-274e-43c9-b154-3a042692af06",
        "eventGroupingSettings": {
          "aggregationKind": "AlertPerResult"
        },
        "alertDetailsOverride": {
          "alertDescriptionFormat": "Client has been identified with high NXDomain count which could be indicative of a DGA (cycling through possible C2 domains where most C2s are not live). This client is found to be communicating with multiple Domains which do not exist.\n\nBaseline Domain or DNS query count from this client: '{{baseline}}'\n\nCurrent Domain or DNS query count from this client: '{{Total}}'\n\nDNS queries requested by this client inlcude: '{{DNSQueries}}'",
          "alertDisplayNameFormat": "[Anomaly] Potential DGA (Domain Generation Algorithm) originating from client IP: '{{SrcIpAddr}}' has been detected."
        },
        "customDetails": {
          "Total": "Total",
          "baseline": "baseline",
          "DNSQueries": "DNSQueries",
          "AnomalyScore": "score"
        },
        "entityMappings": [
          {
            "fieldMappings": [
              {
                "columnName": "SrcIpAddr",
                "identifier": "Address"
              }
            ],
            "entityType": "IP"
          }
        ],
        "status": "Available",
        "templateVersion": "1.0.2",
        "tags": [
          {
            "SchemaVersion": "0.1.6",
            "Schema": "ASimDns"
          }
        ],
        "OriginalUri": "https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/PotentialDGADetectedviaRepetitiveFailuresAnomalyBased.yaml"
      }
    }
  ]
}