ThreatFox: Sliver IOCs | SOC Hunt Feed

Hunt Hypothesis

This hunt detects adversaries leveraging the Sliver post-exploitation framework to establish command-and-control channels, facilitate lateral movement, and maintain persistence across compromised endpoints. Proactively hunting for these indicators in Azure Sentinel is critical because Sliver’s modular design allows attackers to evade standard signature-based defenses, necessitating a proactive search for its specific IOCs to identify stealthy, advanced intrusions early in the kill chain.

IOC Summary

Malware Family: Sliver Total IOCs: 7 IOC Types: ip:port

Type	Value	Threat Type	First Seen	Confidence
ip:port	`89[.]106[.]83[.]136:36366`	botnet_cc	2026-09-01	75%
ip:port	`185[.]165[.]171[.]71:31337`	botnet_cc	2026-09-01	75%
ip:port	`85[.]239[.]144[.]103:31337`	botnet_cc	2026-09-01	75%
ip:port	`149[.]104[.]90[.]17:31337`	botnet_cc	2026-09-01	75%
ip:port	`185[.]242[.]235[.]16:31337`	botnet_cc	2026-09-01	75%
ip:port	`89[.]34[.]90[.]139:31337`	botnet_cc	2026-09-01	75%
ip:port	`91[.]92[.]144[.]21:55535`	botnet_cc	2026-09-01	75%

KQL: Ip Hunt

// Hunt for network connections to known malicious IPs
// Source: ThreatFox - Sliver
let malicious_ips = dynamic(["185.242.235.16", "91.92.144.21", "85.239.144.103", "89.106.83.136", "89.34.90.139", "185.165.171.71", "149.104.90.17"]);
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(["185.242.235.16", "91.92.144.21", "85.239.144.103", "89.106.83.136", "89.34.90.139", "185.165.171.71", "149.104.90.17"]);
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 — Sliver

False Positive Guidance

Here are 4 specific false positive scenarios for the ThreatFox: Sliver IOCs detection rule, including context and suggested filters/exclusions:

Scenario: Automated Patch Deployment via SCCM/Intune
- Context: Enterprise Endpoint Management tools like Microsoft Configuration Manager (SCCM) or Intune often utilize PowerShell scripts to deploy security updates. These scripts frequently establish outbound HTTPS connections to update servers that may share IP ranges or certificate thumbprints with known Sliver C2 infrastructure, triggering the rule due to similar TLS handshake patterns or specific User-Agent strings used by the deployment agents.
- Suggested Filter/Exclusion: Create an exclusion for traffic originating from the CcmExec.exe (SCCM) and Microsoft.IntuneManagementAgent.exe processes connecting to known internal update distribution points (e.g., *.update.microsoft.com or specific internal FQDNs). Additionally, whitelist the specific SHA-1/SHA-256 certificate hashes used by these management servers.
Scenario: Scheduled PowerShell Maintenance Jobs
- Context: IT operations teams often schedule recurring maintenance tasks (e.g., log rotation, database backups, or inventory scans) using Task Scheduler running powershell.exe. If these scripts utilize the System.Net.HttpWebRequest class to query external APIs for status reporting, they may mimic Sliver’s beaconing behavior. The rule might flag the periodic HTTP POST requests as Sliver C2 heartbeats if the script uses a generic or custom User-Agent string.
- Suggested Filter/Exclusion: Implement a logic filter that excludes alerts where the parent process is TaskScheduler.exe and the command line contains specific keywords like “maintenance,” “backup,” or “inventory.” Furthermore, exclude traffic from known internal IP ranges dedicated to the Operations team’s jump hosts.
**Scenario: DevOps CI/CD Pipeline Execution