Peeling Back the Layers: Inside Vidar - From Virtualized Code to Stolen Credentials
This analysis covers a sophisticated variant of the Vidar infostealer malware that uses a custom virtual machine to obfuscate its code. It employs multiple anti-analysis techniques such as debugger detection, timing checks, sandbox evasion, and environment fingerprinting. Vidar targets credentials from Chromium and Gecko-based browsers, Azure authentication tokens, and FileZilla FTP credentials, while also capturing screenshots. It uses elevated privileges and hidden desktops for browser automation and exfiltrates stolen data via Telegram channels. The malware cleans up execution artifacts and uses DLL proxying through rundll32.exe to evade detection.
AI Analysis
Technical Summary
The Vidar infostealer variant analyzed uses a proprietary virtual machine to interpret custom bytecode, complicating reverse engineering efforts. It incorporates anti-analysis measures including NtQueryInformationProcess debugger detection, RDTSC timing checks, sandbox evasion by detecting antivirus processes and system resource checks, and environment fingerprinting. Vidar targets a range of sensitive data including browser credentials from Chromium and Gecko-based extensions, Azure authentication tokens, and FileZilla FTP credentials. It captures screenshots and leverages SeDebugPrivilege for elevated access. The malware creates hidden desktops to automate browser interactions and exfiltrates stolen data through Telegram channels. It also performs cleanup to remove traces of execution and proxies DLL execution through rundll32.exe to blend with legitimate Windows processes.
Potential Impact
Vidar compromises user credentials from multiple sources including web browsers and FTP clients, as well as Azure authentication tokens, potentially allowing attackers unauthorized access to user accounts and cloud resources. The malware's use of elevated privileges and stealth techniques increases the difficulty of detection and removal. Data exfiltration via Telegram channels enables attackers to receive stolen information covertly. The overall impact includes credential theft, potential account takeover, and privacy breaches.
Mitigation Recommendations
No official patch or remediation is available as this is malware rather than a software vulnerability. Mitigation focuses on detection and prevention through endpoint protection solutions capable of identifying Vidar's behavior and indicators, including its anti-analysis techniques and use of rundll32.exe for DLL proxying. Monitoring for suspicious use of SeDebugPrivilege and hidden desktop creation may aid detection. Network monitoring for unusual Telegram traffic could help identify data exfiltration attempts. Users should maintain updated antivirus and endpoint detection and response (EDR) tools and exercise caution with email attachments and downloads to prevent infection.
Indicators of Compromise
- hash: 4af273fab49d3ee6aa182111a2891ed5
- hash: de10359f98cf66d7cb534f6ec7c5101e
- hash: a20139421c881a47110838881e61b418814edb69
- hash: f03931b9008cbc798abc5a7c54be206e7331ab3b
- hash: 34c7929e60aa09bffdf458f4ee0b618f65d77e1b77e161f66fb835e35c405cc4
- hash: 398633479c7d8c0c93616f50d1faaa7f01b5864c89de0911812da60bf90e3358
- hash: 3a2e69ca13d76af3d9502d352802be4d6aa00cc675da69fccab33dc3a0c914fe
- hash: e42890753b9e9e08a29dab78db957677dfb9efd3dfa0aef84184d4257ad1a6f0
- hash: e618dd67445e12d7c2bd9dada402f522b5456d891a81c7d1b0978b6409f21322
Peeling Back the Layers: Inside Vidar - From Virtualized Code to Stolen Credentials
Description
This analysis covers a sophisticated variant of the Vidar infostealer malware that uses a custom virtual machine to obfuscate its code. It employs multiple anti-analysis techniques such as debugger detection, timing checks, sandbox evasion, and environment fingerprinting. Vidar targets credentials from Chromium and Gecko-based browsers, Azure authentication tokens, and FileZilla FTP credentials, while also capturing screenshots. It uses elevated privileges and hidden desktops for browser automation and exfiltrates stolen data via Telegram channels. The malware cleans up execution artifacts and uses DLL proxying through rundll32.exe to evade detection.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The Vidar infostealer variant analyzed uses a proprietary virtual machine to interpret custom bytecode, complicating reverse engineering efforts. It incorporates anti-analysis measures including NtQueryInformationProcess debugger detection, RDTSC timing checks, sandbox evasion by detecting antivirus processes and system resource checks, and environment fingerprinting. Vidar targets a range of sensitive data including browser credentials from Chromium and Gecko-based extensions, Azure authentication tokens, and FileZilla FTP credentials. It captures screenshots and leverages SeDebugPrivilege for elevated access. The malware creates hidden desktops to automate browser interactions and exfiltrates stolen data through Telegram channels. It also performs cleanup to remove traces of execution and proxies DLL execution through rundll32.exe to blend with legitimate Windows processes.
Potential Impact
Vidar compromises user credentials from multiple sources including web browsers and FTP clients, as well as Azure authentication tokens, potentially allowing attackers unauthorized access to user accounts and cloud resources. The malware's use of elevated privileges and stealth techniques increases the difficulty of detection and removal. Data exfiltration via Telegram channels enables attackers to receive stolen information covertly. The overall impact includes credential theft, potential account takeover, and privacy breaches.
Defensive Guidance
No official patch or remediation is available as this is malware rather than a software vulnerability. Mitigation focuses on detection and prevention through endpoint protection solutions capable of identifying Vidar's behavior and indicators, including its anti-analysis techniques and use of rundll32.exe for DLL proxying. Monitoring for suspicious use of SeDebugPrivilege and hidden desktop creation may aid detection. Network monitoring for unusual Telegram traffic could help identify data exfiltration attempts. Users should maintain updated antivirus and endpoint detection and response (EDR) tools and exercise caution with email attachments and downloads to prevent infection.
Technical Details
- Author
- AlienVault
- Tlp
- white
- References
- ["https://www.splunk.com/en_us/blog/security/inside-vidar-from-virtualized-code-to-stolen-credentials.html"]
- Adversary
- null
- Pulse Id
- 6aa0ff00a243a6e9885866ee
- Threat Score
- null
Indicators of Compromise
Hash
| Value | Description | Copy |
|---|---|---|
hash4af273fab49d3ee6aa182111a2891ed5 | — | |
hashde10359f98cf66d7cb534f6ec7c5101e | — | |
hasha20139421c881a47110838881e61b418814edb69 | — | |
hashf03931b9008cbc798abc5a7c54be206e7331ab3b | — | |
hash34c7929e60aa09bffdf458f4ee0b618f65d77e1b77e161f66fb835e35c405cc4 | — | |
hash398633479c7d8c0c93616f50d1faaa7f01b5864c89de0911812da60bf90e3358 | — | |
hash3a2e69ca13d76af3d9502d352802be4d6aa00cc675da69fccab33dc3a0c914fe | — | |
hashe42890753b9e9e08a29dab78db957677dfb9efd3dfa0aef84184d4257ad1a6f0 | — | |
hashe618dd67445e12d7c2bd9dada402f522b5456d891a81c7d1b0978b6409f21322 | — |
Threat ID: 6aa13a4facd9273b492fb50c
Added to database: 09/09/2026, 10:51:59 UTC
Last enriched: 09/09/2026, 10:52:06 UTC
Last updated: 09/09/2026, 23:59:03 UTC
Views: 17
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