Detect DNS queries reporting multiple errors from different clients - Anomaly Based ASIM DNS Solution
Id | cf687598-5a2c-46f8-81c8-06b15ed489b1 |
Rulename | Detect DNS queries reporting multiple errors from different clients - Anomaly Based (ASIM DNS Solution) |
Description | This rule makes use of the series decompose anomaly method to generate an alert when multiple clients report errors for the same DNS query. This rule monitors DNS traffic over a period of 14 days to detect possible similar C2 communication originating from different clients. It utilizes ASIM normalization and is applied to any source that supports the ASIM DNS schema. |
Severity | Medium |
Tactics | CommandAndControl |
Techniques | T1568 T1573 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/MultipleErrorsReportedForSameDNSQueryAnomalyBased.yaml |
Version | 1.0.2 |
Arm template | cf687598-5a2c-46f8-81c8-06b15ed489b1.json |
let threshold = 2.5;
let min_t = ago(14d);
let max_t = now();
let dt = 1d;
let Errors = dynamic(['NXDOMAIN', 'SERVFAIL', 'REFUSED']);
// 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(starttime=todatetime(ago(2d)), endtime=now())
| where TimeGenerated > maxSummarizedTime and EventResultDetails in (Errors)
| 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(starttime=todatetime(ago(3d)), endtime=now())
| where TimeGenerated > maxSummarizedTime and EventResultDetails in (Errors)
| 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(starttime=todatetime(ago(4d)), endtime=now())
| where TimeGenerated > maxSummarizedTime and EventResultDetails in (Errors)
| 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 in (Errors)
| project-rename SrcIpAddr=SrcIpAddr_s, DnsQuery=DnsQuery_s, Count=count__d, EventTime=EventTime_t
| extend Count = toint(Count)
);
allData
| make-series TotalIPCount=dcount(SrcIpAddr) on EventTime from min_t to max_t step dt by DnsQuery
| extend (anomalies, score, baseline) = series_decompose_anomalies(TotalIPCount, threshold, -1, 'linefit')
| mv-expand anomalies, score, baseline, EventTime, TotalIPCount
| extend
anomalies = toint(anomalies),
score = toint(score),
baseline = toint(baseline),
EventTime = todatetime(EventTime),
TotalIPs = tolong(TotalIPCount)
| where EventTime >= ago(dt)
| where score >= threshold * 2
| join kind=inner(allData | where TimeGenerated>ago(dt) | summarize SrcIps = make_set(SrcIpAddr,1000) by DnsQuery) on DnsQuery
| project-away DnsQuery1
relevantTechniques:
- T1568
- T1573
- T1008
name: Detect DNS queries reporting multiple errors from different clients - Anomaly Based (ASIM DNS Solution)
requiredDataConnectors: []
entityMappings:
- fieldMappings:
- identifier: DomainName
columnName: DnsQuery
entityType: DNS
triggerThreshold: 0
id: cf687598-5a2c-46f8-81c8-06b15ed489b1
tactics:
- CommandAndControl
version: 1.0.2
customDetails:
baseline: baseline
SrcIps: SrcIps
TotalIPs: TotalIPs
AnomalyScore: score
queryPeriod: 14d
alertDetailsOverride:
alertDisplayNameFormat: "[Anomaly] Multiple errors for the same DNS query has been detected - '{{DnsQuery}}'"
alertDescriptionFormat: |-
Multiple errors were detected on different clients for the same DNS query. These unsuccessful responses can be an indication of C2 communication.
Baseline for total clients reporting errors for this DNS query: '{{baseline}}'
Current count of clients reporting errors for this DNS query: '{{TotalIPs}}'
Clients requesting this DNS query include:
'{{SrcIps}}'
triggerOperator: gt
kind: Scheduled
tags:
- Schema: ASimDns
SchemaVersion: 0.1.6
eventGroupingSettings:
aggregationKind: AlertPerResult
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/MultipleErrorsReportedForSameDNSQueryAnomalyBased.yaml
queryFrequency: 1d
severity: Medium
status: Available
description: |
'This rule makes use of the series decompose anomaly method to generate an alert when multiple clients report errors for the same DNS query. This rule monitors DNS traffic over a period of 14 days to detect possible similar C2 communication originating from different clients. 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 dt = 1d;
let Errors = dynamic(['NXDOMAIN', 'SERVFAIL', 'REFUSED']);
// 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(starttime=todatetime(ago(2d)), endtime=now())
| where TimeGenerated > maxSummarizedTime and EventResultDetails in (Errors)
| 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(starttime=todatetime(ago(3d)), endtime=now())
| where TimeGenerated > maxSummarizedTime and EventResultDetails in (Errors)
| 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(starttime=todatetime(ago(4d)), endtime=now())
| where TimeGenerated > maxSummarizedTime and EventResultDetails in (Errors)
| 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 in (Errors)
| project-rename SrcIpAddr=SrcIpAddr_s, DnsQuery=DnsQuery_s, Count=count__d, EventTime=EventTime_t
| extend Count = toint(Count)
);
allData
| make-series TotalIPCount=dcount(SrcIpAddr) on EventTime from min_t to max_t step dt by DnsQuery
| extend (anomalies, score, baseline) = series_decompose_anomalies(TotalIPCount, threshold, -1, 'linefit')
| mv-expand anomalies, score, baseline, EventTime, TotalIPCount
| extend
anomalies = toint(anomalies),
score = toint(score),
baseline = toint(baseline),
EventTime = todatetime(EventTime),
TotalIPs = tolong(TotalIPCount)
| where EventTime >= ago(dt)
| where score >= threshold * 2
| join kind=inner(allData | where TimeGenerated>ago(dt) | summarize SrcIps = make_set(SrcIpAddr,1000) by DnsQuery) on DnsQuery
| project-away DnsQuery1
{
"$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
"contentVersion": "1.0.0.0",
"parameters": {
"workspace": {
"type": "String"
}
},
"resources": [
{
"apiVersion": "2024-01-01-preview",
"id": "[concat(resourceId('Microsoft.OperationalInsights/workspaces/providers', parameters('workspace'), 'Microsoft.SecurityInsights'),'/alertRules/cf687598-5a2c-46f8-81c8-06b15ed489b1')]",
"kind": "Scheduled",
"name": "[concat(parameters('workspace'),'/Microsoft.SecurityInsights/cf687598-5a2c-46f8-81c8-06b15ed489b1')]",
"properties": {
"alertDetailsOverride": {
"alertDescriptionFormat": "Multiple errors were detected on different clients for the same DNS query. These unsuccessful responses can be an indication of C2 communication. \n\nBaseline for total clients reporting errors for this DNS query: '{{baseline}}'\n\nCurrent count of clients reporting errors for this DNS query: '{{TotalIPs}}'\n\nClients requesting this DNS query include:\n'{{SrcIps}}'",
"alertDisplayNameFormat": "[Anomaly] Multiple errors for the same DNS query has been detected - '{{DnsQuery}}'"
},
"alertRuleTemplateName": "cf687598-5a2c-46f8-81c8-06b15ed489b1",
"customDetails": {
"AnomalyScore": "score",
"baseline": "baseline",
"SrcIps": "SrcIps",
"TotalIPs": "TotalIPs"
},
"description": "'This rule makes use of the series decompose anomaly method to generate an alert when multiple clients report errors for the same DNS query. This rule monitors DNS traffic over a period of 14 days to detect possible similar C2 communication originating from different clients. It utilizes [ASIM](https://aka.ms/AboutASIM) normalization and is applied to any source that supports the ASIM DNS schema.'\n",
"displayName": "Detect DNS queries reporting multiple errors from different clients - Anomaly Based (ASIM DNS Solution)",
"enabled": true,
"entityMappings": [
{
"entityType": "DNS",
"fieldMappings": [
{
"columnName": "DnsQuery",
"identifier": "DomainName"
}
]
}
],
"eventGroupingSettings": {
"aggregationKind": "AlertPerResult"
},
"OriginalUri": "https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/MultipleErrorsReportedForSameDNSQueryAnomalyBased.yaml",
"query": "let threshold = 2.5;\nlet min_t = ago(14d);\nlet max_t = now();\nlet dt = 1d;\nlet Errors = dynamic(['NXDOMAIN', 'SERVFAIL', 'REFUSED']);\n// calculate avg. eps(events per second)\nlet eps = materialize (_Im_Dns | project TimeGenerated | where TimeGenerated > ago(5m) | count | 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 );\n let 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] | where toscalar(eps) > 1000 | join (summarizationexist) on sumexist) | join (\n _Im_Dns(starttime=todatetime(ago(2d)), endtime=now())\n | where TimeGenerated > maxSummarizedTime and EventResultDetails in (Errors)\n | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated,1h)\n | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)\n ) on exists\n | project-away exists, maxv, sum*\n),\n(\n (datatable(exists:int, sumexist:bool)[1,false] | where toscalar(eps) between (501 .. 1000) | join (summarizationexist) on sumexist) | join (\n _Im_Dns(starttime=todatetime(ago(3d)), endtime=now())\n | where TimeGenerated > maxSummarizedTime and EventResultDetails in (Errors)\n | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated,1h)\n | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)\n ) on exists\n | project-away exists, maxv, sum*\n),\n(\n (datatable(exists:int, sumexist:bool)[1,false] | where toscalar(eps) <= 500 | join (summarizationexist) on sumexist) | join (\n _Im_Dns(starttime=todatetime(ago(4d)), endtime=now())\n | where TimeGenerated > maxSummarizedTime and EventResultDetails in (Errors)\n | summarize Count=count() by SrcIpAddr, DnsQuery, bin(TimeGenerated,1h)\n | extend EventTime = TimeGenerated, Count = toint(Count), exists=int(1)\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 in (Errors)\n | project-rename SrcIpAddr=SrcIpAddr_s, DnsQuery=DnsQuery_s, Count=count__d, EventTime=EventTime_t\n | extend Count = toint(Count) \n);\nallData\n| make-series TotalIPCount=dcount(SrcIpAddr) on EventTime from min_t to max_t step dt by DnsQuery\n| extend (anomalies, score, baseline) = series_decompose_anomalies(TotalIPCount, threshold, -1, 'linefit')\n| mv-expand anomalies, score, baseline, EventTime, TotalIPCount\n| extend\n anomalies = toint(anomalies),\n score = toint(score),\n baseline = toint(baseline),\n EventTime = todatetime(EventTime),\n TotalIPs = tolong(TotalIPCount)\n| where EventTime >= ago(dt)\n| where score >= threshold * 2\n| join kind=inner(allData | where TimeGenerated>ago(dt) | summarize SrcIps = make_set(SrcIpAddr,1000) by DnsQuery) on DnsQuery\n| project-away DnsQuery1\n",
"queryFrequency": "P1D",
"queryPeriod": "P14D",
"severity": "Medium",
"status": "Available",
"subTechniques": [],
"suppressionDuration": "PT1H",
"suppressionEnabled": false,
"tactics": [
"CommandAndControl"
],
"tags": [
{
"Schema": "ASimDns",
"SchemaVersion": "0.1.6"
}
],
"techniques": [
"T1008",
"T1568",
"T1573"
],
"templateVersion": "1.0.2",
"triggerOperator": "GreaterThan",
"triggerThreshold": 0
},
"type": "Microsoft.OperationalInsights/workspaces/providers/alertRules"
}
]
}