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ThreatFox: PureLogs Stealer IOCs

ioc-hunt HIGH ThreatFox
DnsEvents
infostealeriocthreatfoxwin-purelogs
This rule was pulled from an open-source repository and enriched with AI. Validate in a test environment before deploying to production.
View original rule at ThreatFox →
Retrieved: 2026-07-30T23:00:00Z · Confidence: high

Hunt Hypothesis

This hunt detects adversary behavior involving the deployment of PureLogs Stealer malware by monitoring for specific indicators of compromise that target sensitive data exfiltration and credential theft. A SOC team should proactively hunt for these IOCs in Azure Sentinel to identify early-stage infections before attackers can establish persistence or escalate privileges within the cloud environment.

IOC Summary

Malware Family: PureLogs Stealer Total IOCs: 6 IOC Types: domain

TypeValueThreat TypeFirst SeenConfidence
domainvoucher-01-static.combotnet_cc2026-07-30100%
domainrelay-01-static.combotnet_cc2026-07-30100%
domainrelay-02-static.combotnet_cc2026-07-30100%
domainstrang-02-static.combotnet_cc2026-07-30100%
domainadobeartsia.combotnet_cc2026-07-30100%
domainboltiviersoul.combotnet_cc2026-07-30100%

KQL: Domain Hunt

// Hunt for DNS queries to known malicious domains
// Source: ThreatFox - PureLogs Stealer
let malicious_domains = dynamic(["voucher-01-static.com", "relay-01-static.com", "relay-02-static.com", "strang-02-static.com", "adobeartsia.com", "boltiviersoul.com"]);
DnsEvents
| where Name has_any (malicious_domains)
| project TimeGenerated, Computer, Name, IPAddresses, QueryType
| order by TimeGenerated desc

Required Data Sources

Sentinel TableNotes
DnsEventsEnsure this data connector is enabled

References

False Positive Guidance

Here are 5 specific false positive scenarios for the ThreatFox: PureLogs Stealer IOCs detection rule, along with targeted filtering strategies:

Original source: https://threatfox.abuse.ch/browse/malware/win.purelogs/