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
customDetails:
SrcIps: SrcIps
baseline: baseline
TotalIPs: TotalIPs
AnomalyScore: score
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}}'
queryFrequency: 1d
queryPeriod: 14d
status: Available
kind: Scheduled
tactics:
- CommandAndControl
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/MultipleErrorsReportedForSameDNSQueryAnomalyBased.yaml
eventGroupingSettings:
aggregationKind: AlertPerResult
version: 1.0.2
triggerThreshold: 0
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.'
severity: Medium
relevantTechniques:
- T1568
- T1573
- T1008
id: cf687598-5a2c-46f8-81c8-06b15ed489b1
name: Detect DNS queries reporting multiple errors from different clients - Anomaly Based (ASIM DNS Solution)
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
requiredDataConnectors: []
tags:
- SchemaVersion: 0.1.6
Schema: ASimDns
entityMappings:
- fieldMappings:
- identifier: DomainName
columnName: DnsQuery
entityType: DNS
triggerOperator: gt