Adversaries may be using beaconing techniques to maintain command and control over compromised systems, leveraging irregular communication patterns to evade detection. SOC teams should proactively hunt for this behavior in Azure Sentinel to identify potential C2 activity early and prevent further compromise.
KQL Query
let starttime = 1d;
let TimeDeltaThresholdInSeconds = 60; // we ignore beacons diffs that fall below this threshold
let TotalBeaconsThreshold = 4; // minimum number of beacons required in a session to surface a row
let JitterTolerance = 0.2; // tolerance to jitter, e.g. - 0.2 = 20% jitter is tolerated either side of the periodicity
CommonSecurityLog
| where DeviceVendor == "Fortinet"
| where TimeGenerated > ago(starttime)
// eliminate bad data
| where isnotempty(SourceIP) and isnotempty(DestinationIP) and SourceIP != "0.0.0.0"
// filter out deny, close, rst and SNMP to reduce data volume
| where DeviceAction !in ("close", "client-rst", "server-rst", "deny") and DestinationPort != 161
// map input fields
| project TimeGenerated , SourceIP, DestinationIP, DestinationPort, ReceivedBytes, SentBytes, DeviceAction
// where destination IPs are public
| where ipv4_is_private(DestinationIP) == false
// sort into source->destination 'sessions'
| sort by SourceIP asc, DestinationIP asc, DestinationPort asc, TimeGenerated asc
| serialize
// time diff the contact times between source and destination to get a list of deltas
| extend nextTimeGenerated = next(TimeGenerated, 1), nextSourceIP = next(SourceIP, 1), nextDestIP = next(DestinationIP, 1), nextDestPort = next(DestinationPort, 1)
| extend TimeDeltainSeconds = datetime_diff("second",nextTimeGenerated,TimeGenerated)
| where SourceIP == nextSourceIP and DestinationIP == nextDestIP and DestinationPort == nextDestPort
// remove small time deltas below the set threshold
| where TimeDeltainSeconds > TimeDeltaThresholdInSeconds
// summarize the deltas by source->destination
| summarize count(), StartTime=min(TimeGenerated), EndTime=max(TimeGenerated), sum(ReceivedBytes), sum(SentBytes), makelist(TimeDeltainSeconds), makeset(DeviceAction) by SourceIP, DestinationIP, DestinationPort
// get some statistical properties of the delta distribution and smooth any outliers (e.g. laptop shut overnight, working hours)
| extend series_stats(list_TimeDeltainSeconds), outliers=series_outliers(list_TimeDeltainSeconds)
// expand the deltas and the outliers
| mvexpand list_TimeDeltainSeconds to typeof(double), outliers to typeof(double)
// replace outliers with the average of the distribution
| extend list_TimeDeltainSeconds_normalized=iff(outliers > 1.5 or outliers < -1.5, series_stats_list_TimeDeltainSeconds_avg , list_TimeDeltainSeconds)
// summarize with the smoothed distribution
| summarize BeaconCount=count(), makelist(list_TimeDeltainSeconds), list_TimeDeltainSeconds_normalized=makelist(list_TimeDeltainSeconds_normalized), makeset(set_DeviceAction) by StartTime, EndTime, SourceIP, DestinationIP, DestinationPort, sum_ReceivedBytes, sum_SentBytes
// get stats on the smoothed distribution
| extend series_stats(list_TimeDeltainSeconds_normalized)
// match jitter tolerance on smoothed distrib
| extend MaxJitter = (series_stats_list_TimeDeltainSeconds_normalized_avg*JitterTolerance)
| where series_stats_list_TimeDeltainSeconds_normalized_stdev < MaxJitter
// where the minimum beacon threshold is satisfied and there was some data transfer
| where BeaconCount > TotalBeaconsThreshold and (sum_SentBytes > 0 or sum_ReceivedBytes > 0)
// final projection
| project StartTime, EndTime, SourceIP, DestinationIP, DestinationPort, BeaconCount, TimeDeltasInSeconds=list_list_TimeDeltainSeconds, Periodicity=series_stats_list_TimeDeltainSeconds_normalized_avg, ReceivedBytes=sum_ReceivedBytes, SentBytes=sum_SentBytes, Actions=set_set_DeviceAction
// where periodicity is order of magnitude larger than time delta threshold (eliminates FPs whose periodicity is close to the values we ignored)
| where Periodicity >= (10*TimeDeltaThresholdInSeconds)
id: 3255ec41-6bd6-4f35-84b1-c032b18bbfcb
name: Fortinet - Beacon pattern detected
description: |
'Identifies patterns in the time deltas of contacts between internal and external IPs in Fortinet network data that are consistent with beaconing.
Accounts for randomness (jitter) and seasonality such as working hours that may have been introduced into the beacon pattern.
The lookback is set to 1d, the minimum granularity in time deltas is set to 60 seconds and the minimum number of beacons required to emit a detection is set to 4.
Increase the lookback period to capture beacons with larger periodicities.
The jitter tolerance is set to 0.2 - This means we account for an overall 20% deviation from the infered beacon periodicity. Seasonality is dealt with automatically using series_outliers.
Note: In large environments it may be necessary to reduce the lookback period to get fast query times.'
severity: Low
requiredDataConnectors:
- connectorId: Fortinet
dataTypes:
- CommonSecurityLog
queryFrequency: 1d
queryPeriod: 1d
triggerOperator: gt
triggerThreshold: 0
tactics:
- CommandAndControl
relevantTechniques:
- T1071
- T1571
query: |
let starttime = 1d;
let TimeDeltaThresholdInSeconds = 60; // we ignore beacons diffs that fall below this threshold
let TotalBeaconsThreshold = 4; // minimum number of beacons required in a session to surface a row
let JitterTolerance = 0.2; // tolerance to jitter, e.g. - 0.2 = 20% jitter is tolerated either side of the periodicity
CommonSecurityLog
| where DeviceVendor == "Fortinet"
| where TimeGenerated > ago(starttime)
// eliminate bad data
| where isnotempty(SourceIP) and isnotempty(DestinationIP) and SourceIP != "0.0.0.0"
// filter out deny, close, rst and SNMP to reduce data volume
| where DeviceAction !in ("close", "client-rst", "server-rst", "deny") and DestinationPort != 161
// map input fields
| project TimeGenerated , SourceIP, DestinationIP, DestinationPort, ReceivedBytes, SentBytes, DeviceAction
// where destination IPs are public
| where ipv4_is_private(DestinationIP) == false
// sort into source->destination 'sessions'
| sort by SourceIP asc, DestinationIP asc, DestinationPort asc, TimeGenerated asc
| serialize
// time diff the contact times between source and destination to get a list of deltas
| extend nextTimeGenerated = next(TimeGenerated, 1), nextSourceIP = next(SourceIP, 1), nextDestIP = next(DestinationIP, 1), nextDestPort = next(DestinationPort, 1)
| extend TimeDeltainSeconds = datetime_diff("second",nextTimeGenerated,TimeGenerated)
| where SourceIP == nextSourceIP and DestinationIP == nextDestIP and DestinationPort == nextDestPort
// remove small time deltas below the set threshold
| where TimeDeltainSeconds > TimeDeltaThresholdInSeconds
// summarize the deltas by source->destination
| summarize count(), StartTime=min(TimeGenerated), EndTime=max(TimeGenerated), sum
| Sentinel Table | Notes |
|---|---|
CommonSecurityLog | Ensure this data connector is enabled |
Scenario: Scheduled System Backup Using Veeam Backup & Replication
Description: A legitimate scheduled backup job using Veeam may generate periodic traffic to an external backup server, mimicking beaconing behavior.
Filter/Exclusion: Exclude traffic originating from Veeam backup servers or associated with known backup jobs using the src_ip or job_name fields.
Scenario: DNSSEC Validation via Unbound
Description: Unbound DNS resolver may periodically query external DNS servers for DNSSEC validation, creating regular intervals between internal and external IP contacts.
Filter/Exclusion: Exclude traffic involving Unbound DNS resolver (e.g., src_ip matching Unbound server IP) or queries related to DNSSEC validation.
Scenario: Windows Task Scheduler Running Maintenance Scripts
Description: A scheduled task running a maintenance script (e.g., using PowerShell or CMD) may establish periodic connections to an external server for updates or data synchronization.
Filter/Exclusion: Exclude traffic initiated by known maintenance tasks using the process_name or command_line fields, or filter by task_name if available.
Scenario: Cloud Sync with Microsoft OneDrive or Dropbox
Description: Cloud sync tools like OneDrive or Dropbox may periodically sync files with external servers, resulting in regular contact patterns that resemble beaconing.
Filter/Exclusion: Exclude traffic from known sync clients (e.g., process_name like OneDrive.exe or dropbox.exe) or filter by application or service_name.
Scenario: Network Time Protocol (NTP) Synchronization
Description: NTP clients may synchronize time with external NTP servers, creating periodic contact patterns that could be mistaken for beaconing.
Filter/Exclusion: Exclude traffic related to NTP (e.g., application field indicating N