ThreatFox: Vidar IOCs

Hunt Hypothesis

This hunt hypothesis targets adversaries leveraging Vidar malware to compromise systems through phishing campaigns, subsequently exfiltrating critical credentials and sensitive data. Proactively hunting for these indicators in Azure Sentinel is essential to detect early-stage infections before attackers can establish persistence or execute large-scale data theft operations.

IOC Summary

Malware Family: Vidar Total IOCs: 2 IOC Types: url

KQL: Url Hunt

// Hunt for access to known malicious URLs
// Source: ThreatFox - Vidar
let malicious_urls = dynamic(["https://frontlinemakechange.com/", "https://genungsfishcamp.com/"]);
UrlClickEvents
| where Url has_any (malicious_urls)
| project Timestamp, AccountUpn, Url, ActionType, IsClickedThrough
| order by Timestamp desc

Required Data Sources

References

• ThreatFox — Vidar

False Positive Guidance

False Positive Scenarios for “ThreatFox: Vidar IOCs” Detection Rule

• Scenario 1: Scheduled Phishing Simulation Campaigns

  • Context: Security teams frequently run internal phishing simulations using platforms like KnowBe4, Proofpoint, or Microsoft Defender for Office 365. These campaigns often distribute test emails containing attachments (e.g., .docx, .pdf) that mimic the delivery vector of Vidar malware. If the simulation tool uses a specific hash or file signature that overlaps with the Vidar IOC list, legitimate employee interactions with these test emails will trigger alerts.
  • Suggested Filter/Exclusion: Create an exclusion rule based on the source IP ranges and sender domains of the internal security training platform (e.g., *.knowbe4.com, *.proofpoint.com). Additionally, exclude events where the user agent or process name matches the simulation client (e.g., KB-Phishing-Sim.exe) during known campaign windows.

• Scenario 2: Automated Backup and Data Exfiltration Jobs

  • Context: Vidar is characterized as a data exfiltration tool, meaning detection logic often monitors for outbound connections carrying large payloads or specific credential patterns. Enterprise environments utilize scheduled backup agents like Veeam, Rubrik, or Commvault that run nightly jobs to transfer sensitive data and credentials to cloud repositories (e.g., AWS S3, Azure Blob). These legitimate high-volume transfers can mimic the behavioral signature of Vidar’s exfiltration phase.
  • Suggested Filter/Exclusion: Implement a process-based exclusion for known backup services (e.g., VeeamTransport.exe, RubrikAgent.exe). Furthermore, add a filter to suppress alerts where the destination IP belongs to the organization’s designated cloud storage CIDR blocks or specific SaaS backup endpoints.

• **Scenario