Potential DGADomain Generation Algorithm detected via Repetitive Failures - Anomaly based ASIM DNS Solution
| 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 |
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
queryPeriod: 14d
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)
entityMappings:
- fieldMappings:
- columnName: SrcIpAddr
identifier: Address
entityType: IP
queryFrequency: 1d
OriginalUri: https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/DNS Essentials/Analytic Rules/PotentialDGADetectedviaRepetitiveFailuresAnomalyBased.yaml
tags:
- SchemaVersion: 0.1.6
Schema: ASimDns
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.'
kind: Scheduled
version: 1.0.2
eventGroupingSettings:
aggregationKind: AlertPerResult
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}}'
status: Available
severity: Medium
requiredDataConnectors: []
triggerOperator: gt
triggerThreshold: 0
customDetails:
AnomalyScore: score
DNSQueries: DNSQueries
baseline: baseline
Total: Total
tactics:
- CommandAndControl
id: 01191239-274e-43c9-b154-3a042692af06
relevantTechniques:
- T1568
- T1008