Search: “hardware-acceleration”

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DomainAll Cyber AIWindow24h 3d 7d 30d AllIn the wild Important only Show duplicates

CategoryAll AI industry 3 Malware 3 Policy & legal 3 Industry 2 Exploit / PoC 2 Research 1 Phishing & fraud 1 Data breach 1

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Top 10 Best Endpoint Encryption Software in 2026

A 2026 roundup of ten endpoint encryption products argues the engines are solved and buyers should choose management layers like Intune, Sophos, or Trellix.

The guide ranks ten endpoint encryption options, arguing BitLocker and FileVault have won the engine war so the real purchase decision is the management layer for compliance proof, key escrow, and cross-platform policy. Microsoft BitLocker with Intune is named the baseline for Windows estates, with Sophos, ESET, Trend Micro, Check Point, Trellix, and others covering mixed or regulated fleets. It also warns that TrueCrypt-lineage freeware is unmaintained and that Kaspersky cannot be sold to US customers.

Cyber Security NewsSep 10, 08:15 UTC · 6d agoIndustry

Arm Mali G2-Ultra NX GPU: desktop-class mobile gameplay with AI-native graphics

Arm unveiled Mali G2-Ultra NX, its first AI-native mobile GPU with in-shader neural acceleration, third-gen ray tracing, and up to 24% higher benchmark performance.

Arm announced the Mali G2-Ultra NX, the first AI-native Mali GPU, integrating neural accelerators directly into shader cores alongside a new execution engine and third-generation hardware ray tracing. It introduces Neural Super Sampling (NSS), Neural Frame Rate Upscaling (NFRU), and Neural Super Sampling and Denoising (NSSD); the Neural Dawn demo with Sumo Digital showed up to 4x performance efficiency and 70% lower external memory traffic versus native rendering. Arm claims up to 24% higher benchmark performance, 13% lower DRAM traffic on ray tracing benchmarks, and up to 120 FPS with NFRU. Over 14 billion Mali GPUs have shipped to date.

Hacker News · AISep 8, 04:06 UTC · 8d agoAI industry HN 71↑ · 53 comments1

Speculative Decoding in vLLM on AMD GPUs

vLLM benchmarks speculative decoding on AMD Instinct MI300X and MI355X GPUs across five drafting methods including EAGLE-3 and native MTP.

The vLLM project documents draft-and-verify speculative decoding support for AMD GPUs via ROCm, comparing native MTP, Gemma 4 MTP, EAGLE-3, DFlash, and DSpark drafting approaches. Output-token throughput effects varied with drafting method, proposal length, model family, draft checkpoint, workload, and acceptance behavior. The post also covers how to enable each method plus practical tuning and observability considerations.

Hacker News · AISep 7, 09:26 UTC · 9d agoAI tools & infra HN 141↑ · 52 comments1

FreqSpaNet: Frequency and Spatial Learning of SFPF for Physical Layer Hardware Integrity Detection

FreqSpaNet learns spatio-frequency polarization fingerprints to detect unauthorized wireless hardware replacement, reaching 96.31% mean AUROC across seven replacement scenarios.

FreqSpaNet is a representation learning network for open-set hardware anomaly detection using spatio-frequency polarization fingerprints (SFPFs), which capture device-dependent responses across frequencies and directions. A frequency branch models local variations among neighboring frequencies while a geometry-aware spatial branch models directional relationships via angular information, combined through adaptive fusion and complementary pretraining. It achieves a mean AUROC of 96.31%, 9.05 points above the baseline, and is verified under seven hardware replacement scenarios.

arXiv cs.AI / cs.LG / cs.CLSep 15, 17:32 UTC · 1d agoAI research1

AMD security advisory (AV26-879)

Canadian Centre for Cyber Security advisory AV26-879 lists vulnerabilities across AMD EPYC, Ryzen, Threadripper, Instinct, and embedded processors, urging updates.

The September 3, 2026 advisory states AMD is affected by processor vulnerabilities as of September 2, 2026, spanning 2nd-4th Gen EPYC, Ryzen 3000-7045 series, Athlon, Threadripper, Radeon PRO V620, Instinct MI300A, and embedded product lines. It specifies required microcode package versions for each affected family and encourages users and administrators to review AMD's links and apply updates as they become available.

Canadian Centre for Cyber SecuritySep 3, 15:05 UTC · 13d agoAdvisory

PHAT: PHotonic Accelerator for TFHE

PHAT photonic accelerator using optically addressed phase-change memory speeds TFHE bootstrapping FFTs 2.14x-5.10x over the prior ASIC accelerator.

Researchers propose PHAT, an electro-photonic accelerator for TFHE fully homomorphic encryption built on optically addressed phase-change memory (OPCM) processing-in-memory. The architecture adds OPCM-based FFT units, a twiddle-stationary dataflow, and a scheduling mechanism to maximize FFT utilization for TFHE bootstrapping. It achieves 2.14x-5.10x speedups across four real-world TFHE workloads versus the state-of-the-art ASIC accelerator, improving feasibility of privacy-preserving computation in the cloud.

arXiv cs.CRSep 10, 14:30 UTC · 6d agoResearch

OPEN-1B: A Fully Auditable Training Run

Open-1B releases a 1B-parameter model with bitwise-reproducible training, letting independent auditors verify every step of the run on commodity hardware.

The paper introduces a 'fully auditable' tier of model transparency: every training operation is reproducible with bitwise certainty on heterogeneous commodity hardware by imposing definite ordering on GPU kernel reductions, data batch ordering, and collective communication. Because replaying a full run on one machine is infeasible, a collective verification scheme lets many independent auditors certify individual steps covering the whole run. The authors release Open-1B with its full pretraining dataset, every intermediate checkpoint, the training codebase, and an audit harness. This rules out undisclosed data, injected biases, or backdoors that proof-of-learning or proof-of-training-data techniques cannot exclude.

arXiv cs.AI / cs.LG / cs.CLSep 15, 16:23 UTC · 1d agoAI research

Import AI 470: No rights for machines; automating environment generation with SPADE; and building better GPU kernels with Hawkeye

METR analysis finds AI accelerating cyber vulnerability discovery, while SPADE self-play environment generation improves Qwen3 reasoning benchmark scores at 30B scale.

Import AI 470 discusses a METR research note reporting differential acceleration from AI: major acceleration in reported cyber vulnerabilities (cURL, OpenSSL, Firefox, Microsoft, NVD, OSV), minor acceleration in mathematics, and no measurable acceleration in AI-research optimization benchmarks. It also covers SPADE, a self-play framework from a multi-university team (University of Washington, Stanford, MIT, CMU, and others) that co-evolves executable training environments and agent capability using Environment Designer and Reasoning Agent roles with hint-based regret rewards. Trained on Qwen3-4B-Instruct-2507, Qwen3-8B, and Qwen3-30B-A3B-Instruct-2507 via GRPO (400 rollouts of 25 environments), SPADE lifted the 30B-A3B game-environment suite average to 58.3, +8.1 over base, and improved tool-use results across backbones. The issue also references Hawkeye for building better GPU kernels.

Import AIAug 24, 13:12 UTC · 23d agoAI research

Implementation of Machine Learning Workflows with NVIDIA cuML, RAPIDS, GPU Benchmarking, Explainability, Clustering, and Model Inference

Hands-on tutorial implements NVIDIA cuML and RAPIDS to GPU-accelerate scikit-learn-style ML workflows with benchmarking, clustering, and inference.

The tutorial demonstrates NVIDIA cuML as a GPU-accelerated machine learning framework, using cuml.accel to speed up unmodified scikit-learn scripts with zero code changes and the native cuML API for CuPy/cuDF interoperability. It benchmarks CPU versus GPU implementations of PCA, K-Means, nearest-neighbor search, logistic regression, random forests, and DBSCAN on datasets up to 200,000 samples with 64 features. It also builds GPU pipelines with UMAP, t-SNE, and HDBSCAN, validates GPU-generated SHAP explanations, uses the FIL library for forest inference, and covers model serialization and GPU/CPU portability.

MarkTechPostSep 13, 01:42 UTC · 3d agoAI tools & infra

Why Scaling AI Compute Performance Requires a New Power Architecture

NVIDIA argues AI factories need 800 VDC power distribution as dense GPU racks outgrow traditional AC-based delivery.

NVIDIA's blog contends each generation of accelerated computing demands higher rack density and more efficient, scalable power distribution. It frames the bottleneck as how power moves from the grid to the GPU rather than raw wattage, and describes limitations of traditional AC power delivery. NVIDIA advocates a new 800 VDC power architecture for AI factories.

NVIDIA BlogAug 11, 15:00 UTC · Aug 11, 2026AI industry

Previewing Ultrafast mode: GPT-5.6 Sol at up to 14X the speed

OpenAI previews Ultrafast, an API service tier running GPT-5.6 Sol up to 14x faster via Cerebras at up to 750 output tokens per second.

OpenAI announced a preview of Ultrafast, a new API service tier that runs GPT-5.6 Sol at up to 14 times the speed of standard inference. The tier is powered by Cerebras hardware and delivers up to 750 output tokens per second. The offering targets latency-sensitive developer workloads on OpenAI's API platform.

OpenAI NewsAug 13, 10:00 UTC · Aug 13, 2026AI tools & infra

GPU-CFR: 80x Faster Counterfactual Regret Minimization by Compiling the Game to Static Dataflow and CUDA Graph Replay

GPU-CFR compiles counterfactual regret minimization into static dataflow with CUDA Graph Replay, achieving 29.8-80.4x speedups over prior GPU solvers.

The paper presents a compiler and runtime that turns any fixed game's CFR iteration into a static dataflow graph of flat arrays and precomputed indices, cutting framework operations by up to 18.1x. Because shapes and buffer addresses never change, CUDA Graph Replay records the iteration once and replays it with a single launch. On one A100 across an eight-game suite, GPU-CFR runs 29.8-80.4x faster than the fastest prior GPU CFR and 14-258x faster than the CPU implementation LiteEFG on the four largest games, while reproducing reference iterates bitwise on CPU.

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:58 UTC · 6d agoAI research3· 1 read

New hardware device can RAM into encrypted memory, expose your data

Researchers built a $200 DDR5 interposer that silently drops memory writes to break TDX, SGX, and SEV-SNP confidential VM integrity, requiring physical access.

Researchers from KU Leuven, ETH Zurich, Durham University, and Google demonstrated DDRop, a hardware interposer costing under $200 that corrupts DDR5 bus commands to silently drop writes to encrypted memory, enabling replay attacks on confidential VMs. Because scalable memory encryption lacks freshness checks, protected VMs keep computing on stale attacker-selected data; on an Intel TDX server the attack forces debug mode for plaintext memory reads or forges attestation reports, succeeding in under two minutes without crashing. Intel and AMD both called the attack out of scope for their cloud threat models, with no mitigation planned, and proposed cache line versioning appears still vulnerable. The full interposer design is being released as open-source hardware.

The Register · SecuritySep 14, 18:31 UTC · 2d agoResearch

Building a Linux GPU Driver for the M4 Mac Mini in One Month

Two developers built a fully OpenGL ES 3.0 compliant Linux GPU driver for the M4 Mac Mini in one month via clean-room reverse engineering.

Niklas and the author reverse engineered Apple's AGX GPU firmware ABI and user-space components in about a month, a process that normally takes years, producing an OpenGL ES 3.0 conformant driver fast enough to run Minecraft at 200fps on an M4 Mac Mini. The work was done transparently using hypervisor traces without examining Apple binaries, following clean-room practices, and included a custom shader compiler, command stream builder, and a full Linux kernel driver for the firmware ABI. The A18 Pro firmware ABI proved significantly more complex than the M1's, with 1.5x as many structs and twice as many pointers. All experiments and provenance evidence were published in public agx-re repositories.

Hacker News · AISep 15, 19:30 UTC · 1d agoResearch HN 40↑ · 5 comments

OptiPrime: Optimizing Private Inference through Protocol-Hardware Co-design

OptiPrime co-designs HE-MPC protocols with hardware acceleration to remove network communication bottlenecks in private DNN inference, beating Cheetah by up to 5.7x.

OptiPrime is a protocol-hardware co-optimization framework for private deep neural network inference based on hybrid homomorphic encryption (HE) and multi-party computation (MPC). It introduces a novel HE protocol for convolutions that reduces the number of transmitted output ciphertexts, addressing the network bottleneck that limits gains from commercial HE accelerators. A lightweight compression system reduces weight plaintext memory traffic by 10x, while a specialized dataflow maximizes on-chip reuse of intermediate ciphertexts. Experiments show up to 5.7x speedup over the Cheetah baseline on CPUs and 4.2x with an accelerator.

arXiv cs.CRSep 15, 09:29 UTC · 1d agoResearch

CHERI-D Reincarnate: efficient multicore CHERI temporal memory safety through allocation reincarnation (draft version)

CHERI-D Reincarnate adds allocation reincarnation to CHERI, quarantining generation IDs instead of memory to cut temporal memory-safety overheads on multicore systems.

The proposal extends CHERI-D temporal memory safety by quarantining exhausted generation IDs rather than memory slots, allowing freed memory immediate reuse through allocation reincarnation. It adds coherent ID caching and multicore support connecting physical coherence events to the virtually addressed ObjID buffer. The design was implemented as a hardware-software co-design across CHERI-Toooba FPGA softcore, QEMU, LLVM/Clang, and CheriBSD. Across evaluated workloads it substantially reduces memory-sweep frequency and quarantine overhead with low performance and hardware cost.

arXiv cs.CRSep 10, 14:19 UTC · 6d agoResearch

Chipmaker Patch Tuesday: Nvidia, AMD, Arm Issue Security Advisories

AMD, Arm, and Nvidia issued Patch Tuesday advisories fixing a Linux GPU driver DoS flaw, nine Mali GPU vulnerabilities, and two high-severity Triton defects.

AMD fixed CVE-2026-43603, a NULL pointer dereference in its Linux GPU kernel driver that can crash systems and cause denial-of-service, credited to SecMate researchers, with patches for EPYC, Ryzen, Radeon, and Instinct shipped in July and embedded variants due in October. Arm published an advisory covering nine Mali GPU vulnerabilities allowing use-after-free access, kernel information leaks, or DoS, releasing fixes for Valhall and 5th Gen GPU Architecture drivers, with Bifrost also affected. Nvidia updated Triton Inference Server for Linux to resolve two high-severity flaws, one causing DoS and one enabling information disclosure, data tampering, and DoS. Intel had issued no new advisories since the previous Patch Tuesday.

SecurityWeekSep 9, 16:22 UTC · 7d agoAdvisory CVE-2026-43603

Design Docs Are All You Need: An AI-native Machine-Learning Performance Tool

Researchers present SMART, an ML performance-modeling library regenerated by AI coding agents from natural-language design docs instead of code.

The paper describes SMART, a symbolic performance-modeling library whose main branch contains almost no code: the repository is a DAG of self-contained design documents, and coding sub-agents regenerate implementations from only the docs on version updates. Reliability rests on a worked-example doc style used as in-context demonstrations and a minimal operator IR with SymPy cost expressions, offering both fast analytical roll-up and fine-grained modulo-scheduling modes. Regenerated implementations reproduce hand-audited reference models, including DeepSeek-V3 serving on a TPU pod slice, to round-off precision.

arXiv cs.AI / cs.LG / cs.CLSep 4, 17:08 UTC · 12d agoAI research1

"They don't care about this": A Systematic Study of TEE Build Reproducibility in the Wild

91% of 115 surveyed TEE deployments across Intel SGX, TDX, and AMD SEV fail to provide reproducible builds needed for verifiable remote attestation.

A systematic study of 115 TEE deployments found 91% were not reproducible and 80% lacked both source code and a reference build, undermining remote attestation guarantees. Interviews with 12 developers of 50 Intel SGX projects confirmed that only one participant treats reproducibility as a development priority. The authors identify technical barriers such as embedded timestamps plus ecosystem-level issues like lack of build-environment control in multi-stakeholder projects, and call for holistic, committed reproducibility practices.

arXiv cs.CRSep 10, 11:43 UTC · 6d agoResearch

TPMSpy: Validation of Measured Boot Systems by Low-Level Tracing of TPM Usage

Researchers present TPMSpy, a platform-agnostic method validating TPM Measured Boot via low-level tracing, finding inconsistent Linux systemd measurements that break remote attestation and LUKS decryption.

An arXiv paper (2609.05011) introduces TPMSpy, a method that analyzes virtualized system–TPM interactions to independently reconstruct and validate TPM Event Logs without relying on the quoting mechanism, applicable to open and closed systems and demonstrated on Linux and Windows. A longitudinal analysis of Linux systems running systemd versions 245–258 (2020–2025) found wide divergence in Measured Boot usage, undocumented behavioral changes, and no common usage pattern. The authors report inconsistent measurement of user-space systemd services, which prevents reliable remote attestation and LUKS disk decryption on affected systems.

arXiv cs.CRSep 4, 11:23 UTC · 12d agoResearch

Miles v0.1: Production-Level Post-Training

Radix Ark open-sources Miles v0.1, a full-stack RL post-training framework demonstrated with asynchronous agentic RL on GLM-5.2 744B-A40B across 64 GB300 GPUs.

Miles v0.1 is a full-stack, open-source system for frontier-scale reinforcement-learning post-training, built on slime with rollout engines on SGLang and trainers supporting NVIDIA Megatron-LM and PyTorch FSDP backends plus three weight-synchronization transports. It supports full-parameter RL, LoRA RL, on-policy distillation, supervised fine-tuning, true-on-policy rollout-training alignment, and extends to diffusion models. The end-to-end case study ran fully asynchronous agentic RL on GLM-5.2 744B-A40B for terminal-use coding tasks on 64 NVIDIA GB300 GPUs with a median step time of 263 seconds over the first 30 measured steps. The code is open-sourced on GitHub.

Hugging Face daily papersSep 7, 20:00 UTC · 9d agoAI tools & infra

OpenAI’s GPT-5.6 Sol runs up to 14× faster with Ultrafast mode

OpenAI launched GPT-5.6 Sol Ultrafast mode in limited preview, running up to 14x faster at 750 tokens per second via Cerebras inference.

OpenAI's GPT-5.6 Sol Ultrafast mode is available in limited preview through the OpenAI API, delivering up to 14x faster processing and up to 750 output tokens per second, powered by Cerebras under the companies' ultra-low-latency inference partnership. Preview customers are testing it in production for coding, commerce, financial research, and support applications. OpenAI is also using Ultrafast internally for incident response tasks such as log analysis and trace review, and for research workflows with multiple same-day experiment iterations.

Help Net SecurityAug 14, 00:00 UTC · Aug 14, 2026AI industry

MetroLLM-Bench: Evaluating Language Models as Transit Kiosk Runtimes

MetroLLM-Bench is a 955-case benchmark testing language models as transit kiosk tool-calling runtimes across six real metro systems.

The benchmark covers 37-414-station metro systems and eleven task categories including routing, fare calculation, disruptions, accessibility, and adversarial input, with 14 deterministic and 8 semantic scoring components. Of 26 models from six vendors, a PEFT-tuned 4B Qwen 3.5 student scored 91.3 on Tier 1, exceeding GPT-5.6 (90.6/90.0), while Muse Glimmer 30B led the composite ranking. A deterministic rule-based baseline reached 84.6, and PEFT gains over base models shrank from +7.03 points at 2B to -0.91 at 27B.

Hugging Face daily papersSep 8, 20:00 UTC · 8d agoAI research

Hardware Fingerprinting FTQC via Quantum Decoder Timing

Quantum decoder timing on IBM Heron processors forms a side channel enabling device fingerprinting with 89% accuracy and workload inference.

The work demonstrates that wall-clock syndrome-decoding times on fault-tolerant quantum computers constitute a novel hardware side channel. Using per-shot decoder timings from three IBM Heron processors collected over 68 days, a passive observer can reconstruct detector-firing distributions, estimate logical error rate, infer code distance, and fingerprint the specific device with up to 89% accuracy versus 33% for random guessing. Noisy simulation based on Google's 105-qubit Willow processor distinguishes nine surface-code patches at 81% accuracy, showing the channel persists across vendors and code families.

arXiv cs.CRSep 10, 19:24 UTC · 6d agoResearch

USN-8727-1: Linux kernel (OEM) vulnerabilities

Ubuntu issued kernel security update USN-8727-1 for OEM kernels, fixing an Arm TLB invalidation flaw (CVE-2025-10263) allowing local privilege escalation.

Ubuntu released USN-8727-1, a security update for the OEM variant of the Linux kernel. It fixes CVE-2025-10263, in which certain Arm processors complete broadcast TLB invalidation before related memory writes are globally observed, potentially letting local attackers bypass memory protections or escalate privileges. The notice also corrects additional kernel flaws across ARM64, ARM32, RISC-V, S390 and other subsystems.

Ubuntu Security Noticesupdated Sep 7, 09:12 UTC · 9d agofirst Sep 7, 09:02 UTC · 9d agoAdvisory 6 sources CVE-2025-10263

UAT-10147 deploys SPECTRE: A cross-platform implant with Linux rootkit and BYOVD capabilities

Cisco Talos identifies UAT-10147 deploying the SPECTRE implant with cross-platform C2, credential theft, and kernel-level EDR bypass.

Cisco Talos reports that the tracked threat actor UAT-10147 is deploying a newly identified implant named SPECTRE. SPECTRE supports cross-platform command-and-control, process injection, credential theft, and anti-analysis protections. It also includes a Linux rootkit and BYOVD (bring your own vulnerable driver) capability enabling kernel-level EDR bypass, marking an evolution in commodity intrusion tooling.

Cisco TalosAug 20, 10:00 UTC · 27d agoThreat actor in the wild

Towards Standardized Evaluation of GPU Memory Safety with GMSBench

GMSBench provides 149 CUDA tests covering spatial, temporal, and concurrency GPU memory errors, exposing detection gaps in Compute Sanitizer.

GMSBench is a GPU memory safety benchmark comprising 149 self-contained CUDA tests spanning spatial, temporal, and concurrency errors across different GPU memory spaces and execution scenarios. The authors evaluate NVIDIA's Compute Sanitizer across multiple GPU architectures using the suite, exposing gaps in its detection coverage. The benchmark offers a standardized foundation for comparative evaluation of GPU memory safety mechanisms.

arXiv cs.CRSep 8, 15:11 UTC · 8d agoResearch

Delivering Vera: NVIDIA’s First CPU Built for Agents Is Shipping Now

NVIDIA's Vera CPU, its first processor built for AI agents, is now shipping at scale to partners across the AI ecosystem.

NVIDIA announced that Vera, its first CPU designed specifically for agentic AI workloads, has begun shipping at scale. Vice President of Hyperscale and HPC Ian Buck is hand-delivering early Vera CPU systems to organizations across the AI ecosystem, signaling full production availability of the data-center processor.

NVIDIA BlogAug 27, 13:00 UTC · 20d agoAI industry

Online Draft Co-Training for Speculative Decoding in Large-Scale, Long-Context RL Post-Training

NVIDIA researchers detail an end-to-end system for online draft co-training that speeds speculative decoding in large-scale long-context RL post-training.

The paper tackles scaling online draft co-training for speculative decoding in RL post-training, where rollout generation dominates cost. It extends packed, load-balanced zigzag ring attention to merge rank-local branch attention with causal main-sequence attention for context parallelism, and introduces TapChannel to transport target features across pipeline-parallel stages without changing the schedule. Experiments show co-trained drafts tracking the policy baseline with substantial rollout and end-to-end speedups up to 122B parameters and strong scaling at 256K tokens.

Hugging Face daily papersSep 6, 20:00 UTC · 10d agoAI research

Event-Native Symbolic-Temporal Spike Encoding Framework for Heterogeneous Cyber Streams

An event-native spike encoding framework lets recurrent spiking neural networks run intrusion detection directly on heterogeneous packet and CAN bus streams.

The paper maps heterogeneous cyber events—categorical identifiers, local frequency context, and inter-event timing—directly into sparse spike-compatible inputs for spiking neural networks. This avoids flow aggregation and fixed windows that add buffering latency and obscure temporal structure in traditional IDS pipelines. Compact recurrent SNNs under edge-oriented neuromorphic hardware constraints achieve a hybrid anomaly metric of 0.987 on packet-level Network IDS and 0.980 on message-level CAN IDS.

arXiv cs.CRSep 14, 15:55 UTC · 2d agoResearch

New DDRop Attack Breaks Intel TDX and AMD SEV-SNP With $159 DDR5 Device

DDRop uses a $159 DDR5 RDIMM interposer to silently drop memory writes and break Intel TDX and AMD SEV-SNP confidential VMs.

Researchers published DDRop, a physical attack built from about $159 in parts that uses a custom DDR5 RDIMM interposer to inject parity errors and silently discard selected cache-line writebacks. Intel TDX, Intel Scalable SGX, and AMD SEV-SNP are affected because they lack per-line cryptographic freshness, so processors can accept stale encrypted data as valid state. The team demonstrated deterministic plaintext copying between pages, malicious Secure EPT entry injection, forcing trust domains into debug mode, and forging attestation measurements. The attack requires privileged host control plus brief physical access, and researchers say no simple software patch exists.

Cyber Security NewsSep 15, 09:57 UTC · 1d agoResearch 2 sources