NVIDIA is warning customers to activate System Degree Error-Correcting Code mitigation to guard in opposition to Rowhammer assaults on graphical processors with GDDR6 reminiscence.
The corporate is reinforcing the advice as new analysis demonstrates a Rowhammer assault in opposition to an NVIDIA A6000 GPU (graphical processing unit).
Rowhammer is a {hardware} fault that may be triggered via software program processes and stems from reminiscence cells being too shut to one another. The assault was demonstrated on DRAM cells however it may possibly have an effect on GPU reminiscence, too.
It really works by accessing a reminiscence row with sufficient read-write operations, which causes the worth of adjoining information bits to flip from one to zero and vice-versa, inflicting the in-memory info to alter.
The impact may very well be a denial-of-service situation, information corruption, and even privilege escalation.
System Degree Error-Correcting Codes (ECC) can protect the integirty of the info by including redundant bits and correcting single-bit errors to keep up information reliability and accuracy.
In workstation and information middle GPUs the place VRAM handles massive datasets and exact calculations associated to AI workloads, ECC have to be enabled to stop essential errors of their operation.
NVIDIA’s safety discover notes that researchers on the College of Toronto confirmed “a possible Rowhammer assault in opposition to an NVIDIA A6000 GPU with GDDR6 Reminiscence” the place System-Degree ECC was not enabled.
The educational researchers developed GPUHammer, an assault methodology to flip bits on GPU reminiscences.
Though hammering is tougher on GDDR6 due to larger latency and sooner refresh in contrast with CPU-based DDR4, the researchers had been capable of display that Rowhammer assaults on GPU reminiscence banks is feasible.
Aside from the RTX A6000, the GPU maker additionally recommends enabling System-Degree ECC for the next merchandise:
Information Heart GPUs:
- Ampere: A100, A40, A30, A16, A10, A2, A800
- Ada: L40S, L40, L4
- Hopper: H100, H200, GH200, H20, H800
- Blackwell: GB200, B200, B100
- Turing: T1000, T600, T400, T4
- Volta: Tesla V100, Tesla V100S
Workstation GPUs:
- Ampere RTX: A6000, A5000, A4500, A4000, A2000, A1000, A400
- Ada RTX: 6000, 5000, 4500, 4000, 4000 SFF, 2000
- Blackwell RTX PRO (latest workstation line)
- Turing RTX: 8000, 6000, 5000, 4000
- Volta: Quadro GV100
Embedded / Industrial:
- Jetson AGX Orin Industrial
- IGX Orin
The GPU maker notes that newer GPUs like Blackwell RTX 50 Sequence (GeForce), Blackwell Information Heart GB200, B200, B100, and Hopper Information Heart H100, H200, H20, and GH200, include built-in on-die ECC safety, which does nor require an intervention from the consumer.
One approach to test if System Degree ECC is enabled is to make use of an out-of-band methodology that makes use of the system’s BMC (Baseboard Administration Controller) and {hardware} interface software program, just like the Redfish API, to test the “ECCModeEnabled” standing.
Instruments like NSM Kind 3 and NVIDIA SMBPBI can be used for configuration, although they require entry to the NVIDIA Associate Portal.
A second In-Band methodology additionally exists, utilizing the nvidia-smi command-line utility from the system’s CPU to test and allow ECC the place supported.
Rowhammer represents an actual safety concern that would trigger information corruption or allow assaults in multi-tenant environments like cloud servers the place susceptible GPUs could also be deployed.
Nevertheless, the actual threat is context-dependent, and exploiting Rowhammer reliably is difficult, requiring particular situations, excessive entry charges, and exact management, making it an assault troublesome to execute.
Whereas cloud assaults could also be rising extra subtle, attackers nonetheless succeed with surprisingly easy methods.
Drawing from Wiz’s detections throughout hundreds of organizations, this report reveals 8 key methods utilized by cloud-fluent menace actors.