ThreatFox: Aisuru IOCs

Hunt Hypothesis

This hunt detects adversary activity linked to the Aisuru threat actor by correlating three specific Indicators of Compromise (IOCs) across network and endpoint telemetry within Azure Sentinel. Proactively hunting for these signals is critical because early identification of Aisuru’s unique footprint allows the SOC team to isolate potential compromises before they escalate into broader lateral movements or data exfiltration events.

IOC Summary

Malware Family: Aisuru Total IOCs: 3 IOC Types: ip:port

KQL: Ip Hunt

// Hunt for network connections to known malicious IPs
// Source: ThreatFox - Aisuru
let malicious_ips = dynamic(["206.189.94.70", "129.212.233.8", "147.182.217.141"]);
CommonSecurityLog
| where DestinationIP in (malicious_ips) or SourceIP in (malicious_ips)
| project TimeGenerated, SourceIP, DestinationIP, DestinationPort, DeviceAction, Activity
| order by TimeGenerated desc

KQL: Ip Hunt Device

// Hunt in Defender for Endpoint network events
let malicious_ips = dynamic(["206.189.94.70", "129.212.233.8", "147.182.217.141"]);
DeviceNetworkEvents
| where RemoteIP in (malicious_ips)
| project Timestamp, DeviceName, RemoteIP, RemotePort, InitiatingProcessFileName, ActionType
| order by Timestamp desc

Required Data Sources

References

• ThreatFox — Aisuru

False Positive Guidance

Here are 4 specific false positive scenarios for the ThreatFox: Aisuru IOCs detection rule in an enterprise environment, along with suggested filters or exclusions:

• Endpoint Security Agent Updates via Internal Repository

  • Scenario: The organization’s internal software update server (e.g., Microsoft Endpoint Configuration Manager (MECM) or Ivanti) distributes a security patch that includes the Aisuru threat intelligence feed. During the scheduled nightly maintenance window, thousands of endpoints simultaneously download and hash the new IOC database files, triggering network traffic matches against the rule’s IP/URL signatures.
  • Suggested Filter: Exclude traffic originating from the internal software distribution server subnets (e.g., 10.20.50.0/24) or filter events where the destination port is specific to the update protocol (e.g., TCP 8530 for SCCM) and the user agent contains “ConfigMgr”.

• Scheduled Threat Intelligence Feed Ingestion by SIEM

  • Scenario: The Security Operations Center runs a scheduled job using Splunk Add-on for Microsoft Windows or Elastic Stack (Logstash) to ingest daily threat feeds from external vendors. This ingestion process involves the SIEM server establishing outbound connections to Aisuru’s public API endpoints to fetch and validate the latest Indicators of Compromise (IOCs), which mimics the behavior of an infected host querying a C2 server.
  • Suggested Filter: Create an exclusion for the specific static IP address of the SIEM ingestion server or filter events where the source process name is logstash.exe, splunkd.exe, or the scheduled task name contains “ThreatFeedIngestion”.

• IT Admin Manual Investigation and Sandbox Analysis

  • Scenario: A senior SOC analyst or IT administrator manually investigates a suspected campaign by downloading sample