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Potential DGADomain Generation Algorithm detected via Repetitive Failures - Anomaly based ASIM DNS Solution

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Id01191239-274e-43c9-b154-3a042692af06
RulenamePotential DGA(Domain Generation Algorithm) detected via Repetitive Failures - Anomaly based (ASIM DNS Solution)
DescriptionThis 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.
SeverityMedium
TacticsCommandAndControl
TechniquesT1568
T1008
KindScheduled
Query frequency1d
Query period14d
Trigger threshold0
Trigger operatorgt
Source Urihttps://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/PotentialDGADetectedviaRepetitiveFailuresAnomalyBased.yaml
Version1.0.2
Arm template01191239-274e-43c9-b154-3a042692af06.json
Deploy To Azure
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
customDetails:
  baseline: baseline
  Total: Total
  AnomalyScore: score
  DNSQueries: DNSQueries
alertDetailsOverride:
  alertDisplayNameFormat: "[Anomaly] Potential DGA (Domain Generation Algorithm) originating from client IP: '{{SrcIpAddr}}' has been detected."
  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}}'    
eventGroupingSettings:
  aggregationKind: AlertPerResult
tags:
- Schema: ASimDns
  SchemaVersion: 0.1.6
status: Available
triggerThreshold: 0
relevantTechniques:
- T1568
- T1008
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/PotentialDGADetectedviaRepetitiveFailuresAnomalyBased.yaml
requiredDataConnectors: []
queryPeriod: 14d
tactics:
- CommandAndControl
severity: Medium
triggerOperator: gt
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.'
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  
name: Potential DGA(Domain Generation Algorithm) detected via Repetitive Failures - Anomaly based (ASIM DNS Solution)
version: 1.0.2
kind: Scheduled
id: 01191239-274e-43c9-b154-3a042692af06
queryFrequency: 1d
entityMappings:
- entityType: IP
  fieldMappings:
  - columnName: SrcIpAddr
    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/01191239-274e-43c9-b154-3a042692af06')]",
      "kind": "Scheduled",
      "name": "[concat(parameters('workspace'),'/Microsoft.SecurityInsights/01191239-274e-43c9-b154-3a042692af06')]",
      "properties": {
        "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."
        },
        "alertRuleTemplateName": "01191239-274e-43c9-b154-3a042692af06",
        "customDetails": {
          "AnomalyScore": "score",
          "baseline": "baseline",
          "DNSQueries": "DNSQueries",
          "Total": "Total"
        },
        "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",
        "displayName": "Potential DGA(Domain Generation Algorithm) detected via Repetitive Failures - Anomaly based (ASIM DNS Solution)",
        "enabled": true,
        "entityMappings": [
          {
            "entityType": "IP",
            "fieldMappings": [
              {
                "columnName": "SrcIpAddr",
                "identifier": "Address"
              }
            ]
          }
        ],
        "eventGroupingSettings": {
          "aggregationKind": "AlertPerResult"
        },
        "OriginalUri": "https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/PotentialDGADetectedviaRepetitiveFailuresAnomalyBased.yaml",
        "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",
        "severity": "Medium",
        "status": "Available",
        "suppressionDuration": "PT1H",
        "suppressionEnabled": false,
        "tactics": [
          "CommandAndControl"
        ],
        "tags": [
          {
            "Schema": "ASimDns",
            "SchemaVersion": "0.1.6"
          }
        ],
        "techniques": [
          "T1008",
          "T1568"
        ],
        "templateVersion": "1.0.2",
        "triggerOperator": "GreaterThan",
        "triggerThreshold": 0
      },
      "type": "Microsoft.OperationalInsights/workspaces/providers/alertRules"
    }
  ]
}