ThreatFox: Aisuru IOCs | SOC Hunt Feed

Hunt Hypothesis

This detection rule identifies adversary activity by correlating five specific Indicators of Compromise (IOCs) linked to the Aisuru threat actor within Azure Sentinel logs. Proactive hunting for these IOCs is essential to rapidly detect early-stage intrusions and mitigate potential data exfiltration or lateral movement before they escalate into a full-scale incident.

IOC Summary

Malware Family: Aisuru Total IOCs: 5 IOC Types: ip:port

Type	Value	Threat Type	First Seen	Confidence
ip:port	`165[.]245[.]219[.]184:8001`	botnet_cc	2026-07-28	100%
ip:port	`207[.]154[.]240[.]223:8001`	botnet_cc	2026-07-28	100%
ip:port	`137[.]184[.]156[.]157:8001`	botnet_cc	2026-07-28	100%
ip:port	`178[.]128[.]22[.]21:8001`	botnet_cc	2026-07-28	100%
ip:port	`168[.]144[.]138[.]186:8001`	botnet_cc	2026-07-28	100%

KQL: Ip Hunt

// Hunt for network connections to known malicious IPs
// Source: ThreatFox - Aisuru
let malicious_ips = dynamic(["178.128.22.21", "165.245.219.184", "207.154.240.223", "168.144.138.186", "137.184.156.157"]);
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(["178.128.22.21", "165.245.219.184", "207.154.240.223", "168.144.138.186", "137.184.156.157"]);
DeviceNetworkEvents
| where RemoteIP in (malicious_ips)
| project Timestamp, DeviceName, RemoteIP, RemotePort, InitiatingProcessFileName, ActionType
| order by Timestamp desc

Required Data Sources

Sentinel Table	Notes
`CommonSecurityLog`	Ensure this data connector is enabled
`DeviceNetworkEvents`	Ensure this data connector is enabled

References

ThreatFox — Aisuru

False Positive Guidance

Here are 3-5 specific false positive scenarios for the ThreatFox: Aisuru IOCs detection rule, including suggested filters and exclusions tailored for an enterprise environment:

Scenario: Security Information and Event Management (SIEM) Ingestion of Threat Intelligence Feeds
- Context: The organization’s SIEM platform (e.g., Splunk or Microsoft Sentinel) automatically ingests daily threat intelligence feeds from vendors like Recorded Future or AlienVault OTX. These feeds often contain the specific Aisuru IOCs as part of a broader “Known Malware” dataset, triggering the detection rule when the feed parser processes these entries rather than actual endpoint activity.
- Filter/Exclusion: Create an exclusion based on the source hostname or process name. Exclude any events where Source Host matches the SIEM ingestion server (e.g., SIEM-INGEST-01) or where the Process Name is the feed parser utility (e.g., feed_parser.exe or splunk-hec).
Scenario: Scheduled Endpoint Protection Scans by Admin Tools
- Context: During nightly maintenance windows, the enterprise endpoint protection suite (e.g., CrowdStrike Falcon or Microsoft Defender for Endpoint) runs a scheduled “Threat Intelligence Update” job. This process downloads and validates the Aisuru IOC list against local databases to update its detection signatures, generating logs that mimic an active threat match.
- Filter/Exclusion: Implement a time-based exclusion window combined with a user context filter. Exclude events occurring between 02:00 and 04:00 UTC where the User Account is a service account (e.g., svc_antivirus_update) or the process path contains \Program Files\Endpoint Protection\.
Scenario: Automated Vulnerability Management Scans
- **Context