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URLhaus: cowrie Malicious URLs

ioc-hunt HIGH URLhaus
CommonSecurityLogDnsEvents
iocurlhaus
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 URLhaus →
Retrieved: 2026-08-23T23:00:00Z · Confidence: medium

Hunt Hypothesis

This detection identifies adversary behavior where threat actors leverage Cowrie-tagged malicious URLs to distribute malware or establish initial command-and-control channels within the network. A SOC team should proactively hunt for these indicators in Azure Sentinel because early identification of such high-severity URLs enables rapid containment of potential lateral movement and prevents broader compromise before active exploitation occurs.

IOC Summary

Threat: cowrie Total URLs: 2 Active URLs: 1

URLStatusThreatDate Added
hxxp://51.210.44.30:8080/bot.pyofflinemalware_download2026-08-23
hxxp://176.65.139.202/telnet.shonlinemalware_download2026-08-23

KQL: Url Dns Hunt

// Hunt for DNS resolution of URLhaus malicious domains
// Threat: cowrie
let malicious_domains = dynamic(["176.65.139.202"]);
DnsEvents
| where Name has_any (malicious_domains)
| project TimeGenerated, Computer, Name, IPAddresses
| order by TimeGenerated desc

KQL: Url Proxy Hunt

// Hunt for web traffic to URLhaus malicious domains
let malicious_domains = dynamic(["176.65.139.202"]);
CommonSecurityLog
| where RequestURL has_any (malicious_domains) or DestinationHostName has_any (malicious_domains)
| project TimeGenerated, SourceIP, RequestURL, DestinationHostName, DeviceAction
| order by TimeGenerated desc

Required Data Sources

Sentinel TableNotes
CommonSecurityLogEnsure this data connector is enabled
DnsEventsEnsure this data connector is enabled

References

False Positive Guidance

Here are 4 specific false positive scenarios for the URLhaus: cowrie Malicious URLs detection rule, along with suggested filters or exclusions tailored for an enterprise environment:

Original source: https://urlhaus.abuse.ch/