Detection rules › Kusto
Potential DGA(Domain Generation Algorithm) detected via Repetitive Failures - Anomaly based (ASIM DNS Solution)
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.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Command & Control |
Telemetry coverage
| Provider | Record / event type |
|---|---|
| Sysmon | Event ID 22: DNSEvent (DNS query) |
Rule body
id: 01191239-274e-43c9-b154-3a042692af06
name: 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.'
severity: Medium
status: Available
tags:
- Schema: ASimDns
SchemaVersion: 0.1.6
requiredDataConnectors: []
queryFrequency: 1d
queryPeriod: 14d
triggerOperator: gt
triggerThreshold: 0
tactics:
- CommandAndControl
relevantTechniques:
- T1568
- T1008
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
entityMappings:
- entityType: IP
fieldMappings:
- identifier: Address
columnName: SrcIpAddr
eventGroupingSettings:
aggregationKind: AlertPerResult
customDetails:
DNSQueries: DNSQueries
AnomalyScore: score
baseline: baseline
Total: Total
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.\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}}'"
version: 1.0.2
kind: Scheduled
Stages and Predicates
Stage 0: let
let threshold = 2.5;
let min_t = ago(14d);
let max_t = now();
let timeframe = 1d;
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 <inlined as stages below>;
Stage 1: source
let allData
Stage 2: union
union of 4 branches
Stage 3: source
datatable
Stage 4: where
where /* macro: (toscalar(eps) > 1000) */
Stage 5: join
join (summarizationexist) on sumexist
Stage 6: join
join (_Im_Dns) on exists
Stage 7: project-away
project-away exists, maxv, sum*
Stage 8: source
datatable
Stage 9: where
where /* macro: (toscalar(eps) between (501 .. 1000)) */
Stage 10: join
join (summarizationexist) on sumexist
Stage 11: join
join (_Im_Dns) on exists
Stage 12: project-away
project-away exists, maxv, sum*
Stage 13: source
datatable
Stage 14: where
where /* macro: (toscalar(eps) <= 500) */
Stage 15: join
join (summarizationexist) on sumexist
Stage 16: join
join (_Im_Dns) on exists
Stage 17: project-away
project-away exists, maxv, sum*
Stage 18: source
DNS_Summarized_Logs_ip_CL
Stage 19: where
where EventResultDetails_s =~ "NXDOMAIN" and EventTime_t > min_t
Stage 20: project-rename
project-rename
Stage 21: extend
extend Count
Stage 22: summarize
summarize QueryCount by SrcIpAddr
Stage 23: extend
extend anomalies, baseline, score
Stage 24: mv-expand
mv-expand anomalies
Stage 25: extend
extend EventTime, Total, anomalies, baseline, score
Stage 26: where
where EventTime >= ago(86400s)
Stage 27: where
where score >= 5
Stage 28: join
join kind=inner (allData) on SrcIpAddr
Stage 29: project-away
project-away SrcIpAddr1
Indicators
These rows show field, operator, and value matches.
| Field | Kind | Values | Search |
|---|---|---|---|
EventResultDetails_s | eq |
| field:"EventResultDetails_s" kind:eq value:"NXDOMAIN" |
EventTime_t | cross_field_compare |
| field:"EventTime_t" kind:cross_field_compare value:"min_t" |
TimeGenerated | cross_field_compare |
| field:"TimeGenerated" kind:cross_field_compare value:"maxSummarizedTime" |
score | ge |
| field:"score" kind:ge value:"5" |
Output fields
These fields are emitted when the rule matches.
| Field | Source |
|---|---|
QueryCount | summarize |
SrcIpAddr | summarize |
anomalies | extend |
baseline | extend |
score | extend |
EventTime | extend |
Total | extend |