Új hozzászólás Aktív témák

• #51587 S_x96x_S addikt

  Új Válasz 2026-04-03 14:52:23 #51587

  Új hozzászólás

  Összes hozzászólása itt Válaszok az összes hozzászólására itt Válaszok erre a hozzászólásra

  Privát üzenet küldése

  

  S_x96x_S

  addikt

  ( security, GDDR6 )
  https://gddr.fail/
  nvidia GDDR6, GDDR6X -es rendszereket érintheti,
  és az RTX 3060 , RTX 6000 Ampere - biztos érintett ( mert azokat tesztelték )
  ( ez főleg a datacenteres felhasználóknál lehet probléma. )

  -------

  "GPU Memory Exploits
  The GDDRHammer and GeForge teams independently developed exploits that utilize Rowhammer bit flips on Graphics Processing Units (GPUs) to enable a full takeover of Central Processing Unit (CPU) memory from an unprivileged GPU kernel, enabling an attacker to read and write all of the CPU's memory. In addition, we developed novel Rowhammer techniques for GPUs that result in a dramatic increase in the number of bit flips found on GDDR6 memory."

  ---

  "In this work, we provide a Rowhammer characterization of 25 GDDR6 GPUs, including Ampere and Ada 6000 GPUs. "

  GDDRHammer: Greatly Disturbing DRAM Rows — Cross-Component
  Rowhammer Attacks from Modern GPUs :
  https://gddr.fail/files/gddrhammer.pdf
  "Abstract—While Rowhammer has been extensively studied in
  CPU-based memory systems, a very recent work by Lin et
  al. (USENIX Security ‘25) extended this line of research to
  GDDR6 GPU memory, demonstrating the first Rowhammer bit
  flips on NVIDIA GPUs. However, they tested only a single GPU
  and observed just 8 flips across 4 DRAM banks. Moreover,
  their proof-of-concept exploit only demonstrated degradation
  of a deep neural network’s inference, leaving both the extent
  of GPUs’ susceptibility to Rowhammer and the impact of said
  bit flips largely unexplored.
  We address this gap by exploring both the prevalence and
  impact of Rowhammer on GPUs. First, we develop techniques
  for dramatically amplifying Rowhammer on modern GDDR6-
  based GPUs. By utilizing the inherent parallelism in GPUs
  and developing new techniques for bypassing Rowhammer
  mitigations on GPUs, we are able to produce 129 bit flips per
  DRAM bank on average, demonstrating a 64x increase over
  prior work. We also present a comprehensive characterization
  of GPUs’ Rowhammer susceptibility by testing more than 25
  GPUs across multiple systems. Our findings show that nearly
  all tested RTX A6000 GPUs remain vulnerable under realistic
  configurations despite hardware-level mitigations, demonstrat-
  ing that Rowhammer is far more prevalent on GDDR6 memory
  than previously understood.
  We also show the impact of Rowhammer on GPUs by
  demonstrating the first GPU-to-CPU Rowhammer exploit, with
  a practical end-to-end attack wherein an attacker flips bits in
  the GPU’s memory and gains read and write access to all of
  the host CPU’s memory."

  -----

  GeForge: Hammering GDDR Memory to Forge GPU Page Tables for Fun and Profit
  https://gddr.fail/files/GeForge.pdf
  "Abstract—Over the years, Rowhammer has been leveraged to
  mount a wide range of attacks against system main memory.
  While a recent study has revealed that GPU memory is
  similarly vulnerable, the security implications remain largely
  under-explored. To advance this line of research, we introduce
  GeForge, an end-to-end Rowhammer attack that exploits
  bit flips induced in GPU memory to achieve system-level
  compromise. At its core, GeForge corrupts GPU page tables to
  seize control of address translation, enabling arbitrary access
  to the entire GPU memory. Moreover, by exploiting a special
  mapping feature in the GPU page table, GeForge extends its
  reach to directly access host memory.
  To make GeForge practical under default system settings,
  we develop novel techniques that eliminate restrictive assump-
  tions in prior work. Our techniques include a method for
  aligning offline-profiled physical address mappings to runtime
  GPU allocations and a memory massaging strategy that steers
  target GPU page table structures into vulnerable locations via
  the stock driver allocator. In addition, we improve the hammer-
  ing pattern to trigger many more bit flips than prior work.
  With these approaches, we successfully mount GeForge on
  widely deployed NVIDIA GPUs, including both workstation-
  class and consumer-grade ones. We show that GeForge allows
  an attacker to arbitrarily read and modify data across GPU
  contexts. More crucially, we demonstrate that GeForge can
  help the attacker escalate privileges to root on the host system."

  ------

  újságirós értelmezés:
  https://arstechnica.com/security/2026/04/new-rowhammer-attacks-give-complete-control-of-machines-running-nvidia-gpus/
  New Rowhammer attacks give complete control of machines running Nvidia GPUs
  Both GDDRHammer and GeForge hammer GPU memory in ways that compromise the CPU

Új hozzászólás Aktív témák