ThreatFox: Venus Stealer IOCs

Hunt Hypothesis

This detection rule identifies the presence of Venus Stealer malware by monitoring for specific indicators of compromise associated with its credential and cryptocurrency data exfiltration capabilities. Proactive hunting is essential to rapidly isolate compromised endpoints before attackers leverage stolen browser cookies and login credentials to pivot laterally or access financial assets within the Azure Sentinel environment.

IOC Summary

Malware Family: Venus Stealer Total IOCs: 12 IOC Types: md5_hash, sha1_hash, sha256_hash

KQL: Hash Hunt

// Hunt for files matching known malicious hashes
// Source: ThreatFox - Venus Stealer
let malicious_hashes = dynamic(["5380e9b758ebf56f00edd53c2a13aef5", "a1e0a69ab5c44a9be73f9eba32320f97375f6183", "b4ebdf938bd45a11dc5d139bee18e7692e5c98c7511af9026558ef7d281d8c33", "fae010372ab55addd31e97079a4e1b31", "ae2ea23bf77f28d657af0f47d95148419de1ee37812504d61cac0c36dc38e701", "a7b01ecdb80cd09cf2d6181732d909606621cdb1", "f62ce2042c61e211449cc1d1cc3fca94", "a05e2a5c5b4b93447ad06a728f9e41ce9c65d876c87daa59ae2d8ead067d2192", "3e7002d2684c7de7207056c12a7bb5e47fa40f28", "1e395ee2e054a17a8e0117a0fe104b20", "562c8468f2906fb537d378a6d53684795f91a6fc514f461cb938f53fb37fee14", "57eb7f349a222c9aba45d710e974bbad37a5cd5e"]);
DeviceFileEvents
| where SHA256 in (malicious_hashes) or SHA1 in (malicious_hashes) or MD5 in (malicious_hashes)
| project Timestamp, DeviceName, FileName, FolderPath, SHA256, InitiatingProcessFileName
| order by Timestamp desc

Required Data Sources

References

• ThreatFox — Venus Stealer

False Positive Guidance

Here are 5 specific false positive scenarios for the ThreatFox: Venus Stealer IOCs detection rule, including targeted filters and exclusions suitable for an enterprise environment:

• Scenario: Legitimate Phishing Simulation Campaigns

  • Context: Security teams frequently run internal phishing simulations using tools like KnowBe4 or Proofpoint. These campaigns often distribute emails containing malicious-looking attachments (e.g., .docx with macros) or links to simulated landing pages that mimic the behavior of Venus Stealer’s entry vectors.
  • Filter/Exclusion: Create an exclusion rule based on the source domain and sender address. Exclude traffic originating from internal simulation domains (e.g., @phishing-sim.internal, @knowbe4.com) or specific IP ranges associated with the training platform. Additionally, filter out events where the user agent indicates a known internal test account (e.g., user-agent: "PhishSimBot").

• Scenario: Scheduled Credential Backup Jobs via RMM Tools

  • Context: Remote Monitoring and Management (RMM) tools like ManageEngine Desktop Central, Lansweeper, or PDQ Deploy often execute scheduled jobs to audit browser cookies, extract saved passwords from local profiles, and scan for cryptocurrency wallet files as part of routine asset inventory or compliance checks. These actions mimic the exfiltration behavior of Venus Stealer.
  • Filter/Exclusion: Implement a process-based exclusion for known RMM service executables (e.g., DesktopCentral.exe, LansweeperAgent.exe). Add a time-window filter to exclude alerts triggered during standard maintenance windows (e.g., 02:00–04:00 UTC) where these backup jobs are historically scheduled.

• Scenario: Browser Extension Updates and Synchronization

  • Context: Enterprise-wide deployment