URLhaus: malware_download Malicious URLs

Hunt Hypothesis

This detection identifies adversaries leveraging known malicious URLs to distribute malware downloads, a tactic often used in initial access or execution phases of an attack chain. Proactively hunting for these specific URLhaus-tagged indicators within Azure Sentinel is critical to intercepting early-stage infections before they establish persistence or exfiltrate sensitive data from the environment.

IOC Summary

Threat: malware_download Total URLs: 2 Active URLs: 0

KQL: Url Dns Hunt

// Hunt for DNS resolution of URLhaus malicious domains
// Threat: malware_download
let malicious_domains = dynamic(["175.148.152.255", "175.148.154.150"]);
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(["175.148.152.255", "175.148.154.150"]);
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

References

• URLhaus

False Positive Guidance

Here are specific false positive scenarios for the URLhaus: malware_download detection rule in an enterprise environment, along with recommended filters or exclusions:

• Automated Patch Management Scans

  • Scenario: Enterprise endpoint management tools (e.g., Microsoft Endpoint Configuration Manager, Ivanti, or Jamf) periodically scan the internet for security updates and patch definitions. These agents often query known update repositories that URLhaus may flag as “malware_download” due to high traffic volume or shared IP ranges with malicious actors, even though the content is legitimate.
  • Filter/Exclusion: Create an exclusion rule for specific Service Accounts (e.g., svc-patch-agent, jamf-provisioner) and whitelist the known update repository domains (e.g., *.microsoft.com, updates.ivanti.com).

• Software Development & CI/CD Pipeline Artifacts

  • Scenario: Build servers running continuous integration tools (e.g., Jenkins, GitLab Runners, or Azure DevOps) frequently download large binary artifacts, SDKs, and dependencies from public package registries (like Maven Central, npmjs, or PyPI). URLhaus may classify these high-volume downloads as potential malware distribution points if the specific URLs are newly registered or shared among multiple tenants.
  • Filter/Exclusion: Exclude traffic originating from CI/CD Server IP ranges and whitelist the specific package registry domains (e.g., repo.maven.apache.org, registry.npmjs.org) to prevent alerts on routine build jobs.

• IT Administration & Asset Discovery Tasks

  • Scenario: Scheduled administrative tasks using tools like SolarWinds Service Desk, ServiceNow Discovery, or ** Lansweeper** perform network-wide asset discovery and software inventory checks. These processes often trigger downloads of license keys