Search: “NVIDIA”

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CategoryAll Vulnerability 166 Ransomware 114 AI industry 108 Exploit / PoC 72 Malware 70 Policy & legal 46 Data breach 41 Industry 38 AI safety & security 26 Model release 20 Threat actor 20 Research 14 AI research 14 AI tools & infra 13

SeverityAll critical 248 high 172 medium 114 low 89 info 172

New GPUThor Rowhammer Defeats ECC on NVIDIA RTX A6000 to Gain Host Root Access

University of Toronto researchers present GPUThor, a Rowhammer attack that defeats ECC on NVIDIA RTX A4000-A6000 GDDR6 GPUs and achieves host root access.

GPUThor uses non-uniform hammering to bypass Target Row Refresh and overcome SECDED ECC on NVIDIA Ampere workstation GPUs with GDDR6 memory, inducing 72,000 to 377,552 bit flips per gigabyte across RTX A6000, A5000, A4500, and A4000 cards. Triple-bit silent data corruption enables host privilege escalation to root with the IOMMU enabled, reusing GPUBreach page-table corruption techniques, and double-bit DUEs allow escalation when the IOMMU is disabled during a ~10 ms lazy-service window. The attack cut end-to-end escalation time on the A6000 from 21.9 hours to 1.1 minutes. Reported to NVIDIA, Google, Microsoft, and AWS on April 29, 2026; findings were embargoed until August 25, 2026, and no CVE identifier was assigned.

The Hacker NewsSep 8, 16:03 UTC · 7d agoResearch1

New physical attacks are quickly diluting secure enclave defenses from Nvidia, AMD, and Intel

Ars Technica · SecurityOct 29, 13:40 UTC · Oct 29, 2025Research

Excelero's NVMesh deployed by the Science and Technology Facilities Council

Help Net SecurityNov 19, 00:00 UTC · Nov 19, 2019Research

Friday Squid Blogging: Giant Squid vs. Blue Whale

Schneier on SecuritySep 19, 21:06 UTC · Sep 19, 2025Research

Hacking GSM A5 crypto algorithm by using commodity hardware

Security AffairsOct 25, 05:52 UTC · Oct 25, 2016Research

Automobile Camouflage to Hide from Flock Cameras

Schneier on Security highlights a printed vehicle-camouflage pattern tested to defeat Flock surveillance cameras and Axon body cameras.

The post discusses covering cars with printed patterns designed to fool Flock automated license-plate recognition software, with testing reportedly done against Flock and Axon body cameras. Reader comments question effectiveness against other ALPR vendors, Flock's RF MAC-address upgrade, and whether such camouflage might become regulated. The page also contains off-topic comment threads about anti-bot over-blocking and privacy.

Schneier on SecuritySep 7, 11:06 UTC · 8d agoResearch

The Story of Colossus

Schneier on SecurityMay 6, 11:11 UTC · May 6, 2021Research

New SHA-1 Attack

Schneier on SecurityJan 8, 09:38 UTC · Jan 8, 2020Research

U.S. Builds World's Fastest Supercomputer

The Hacker NewsJun 11, 14:09 UTC · Jun 11, 2018Research

New DDRop Attack Breaks Intel TDX and AMD SEV-SNP Confidential Computing

DDRop uses a sub-$200 DDR5 interposer to drop memory writes, breaking Intel TDX and AMD SEV-SNP confidentiality guarantees.

Researchers at KU Leuven, ETH Zurich, Durham University, and Google will present DDRop at ACM CCS 2026, a first active interposer attack on DDR5 that silently drops memory writes so processors keep reading stale encrypted data, exploiting the missing freshness guarantee in Intel TDX, Intel Scalable SGX, and AMD SEV-SNP. On Intel TDX's default logical integrity mode it enabled reading victim VM memory, toggling debug mode, and forging remote attestation; AMD SEV-SNP was limited to copying pages between VMs. TDX's stronger cryptographic integrity blocks cross-VM attacks but likely not attestation forgery. The team will release board designs, firmware, and attack code on GitHub; no evidence of real-world use exists and no simple patch is available.

The Hacker Newsupdated 09:57 UTC · 13h agofirst Sep 14, 16:58 UTC · 1d agoResearch 2 sources

An Open-Source End-to-End FHE Implementation for Privacy-Preserving Llama 3 8B Inference

Odin runs Llama-3-8B fully homomorphic encrypted inference on a single H100 in 366 seconds, a 4.51x speedup over THOR.

Odin is an open-source end-to-end GPU CKKS implementation for privacy-preserving Llama-3-8B inference that co-designs ciphertext packing with model execution. A feature-major cross-layer layout unifies residual connections and layer interfaces, while transient intra-operator layouts serve linear projections and attention, avoiding intermediate repacking of QK^T softmax outputs. Minimax polynomial approximation with input-range control reduces polynomial degree and multiplicative depth for nonlinear ops. With 128-token input, Odin evaluates all 32 Transformer layers on one NVIDIA H100 80 GB in 366.4 s using 58.9 GiB peak memory, versus 1651.9 s for the THOR baseline, a 4.51x speedup.

arXiv cs.CRSep 11, 02:51 UTC · 4d agoResearch