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Vulnerabilities & CVEs BleepingComputer 1 month ago

New GPUThor attack defeats NVIDIA ECC protection for root access

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CyberNew Threat Research Desk
• Original Reporting: BleepingComputer
CyberNew Threat Intel Assessment
Assessed Severity: HIGH
Impacted Surface
Enterprise Data & Identity Stores
Intelligence Sector
Vulnerabilities & CVEs

Analyst Takeaway

"A newly disclosed Rowhammer attack called GPUThor can bypass error-correcting code (ECC) protections on NVIDIA GPUs, enabling denial-of-service (DoS) and root-level privilege escalation. In a paper published by the University of Toronto, researchers say that GPUThor achieves far more practical bit-flip rates than past concepts like their own GPUHammer or GPUBreach , which became irrelevant after..."

Recommended Defense & Mitigation

  • Access Review: Audit administrative roles, enforce phishing-resistant MFA, and review privilege escalations.
  • Credential Rotation: Rotate high-privilege service credentials and tokens associated with impacted services.
Curated & Verified by CyberNew Threat Intelligence Desk Standard Defense Framework (NIST / MITRE ATT&CK)

New GPUThor attack defeats NVIDIA ECC protection for root access

A newly disclosed Rowhammer attack called GPUThor can bypass error-correcting code (ECC) protections on NVIDIA GPUs, enabling denial-of-service (DoS) and root-level privilege escalation.

In a paper published by the University of Toronto, researchers say that GPUThor achieves far more practical bit-flip rates than past concepts like their own GPUHammer or GPUBreach, which became irrelevant after ECC was introduced.

The attack was demonstrated against Ampere-class NVIDIA workstation GPUs with GDDR6 memory, including the RTX A4000, RTX A4500, RTX A5000, and RTX A6000, all widely used in AI and cloud infrastructure.

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GPUThor attack improvement

Rowhammer is the name for a class of attacks where memory rows are repeatedly accessed (“hammered”) in a way that increases the likelihood of bits in neighboring memory regions to flip, changing their state from one to zero or vice versa.

This can lead to data corruption and security risks. Since AI model training relies heavily on GPU power, a successful Rowhammer attack could have a devastating impact on the model's accuracy.

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Source Verification & Original Intelligence

This threat report was reviewed by CyberNew analysts and cross-referenced with primary security disclosures from BleepingComputer.

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