Search: “aruba”

HPE security advisory (AV26-873)

Canada's Cyber Centre relays HPE advisories covering multiple vulnerabilities in Aruba AOS-CX switches and Fabric Composer, urging updates.

The Canadian Centre for Cyber Security issued advisory AV26-873 noting multiple vulnerabilities in HPE Aruba Networking AOS-CX and Fabric Composer. Affected versions span AOS-CX releases through branches 10.10, 10.13, 10.16, 10.17, and 10.18, and Fabric Composer through 7.3.3. Administrators are urged to review HPE bulletins HPESBNW05133 and HPESBNW05134 and apply available updates.

Canadian Centre for Cyber Security·Sep 2, 13:38 UTC · 14d agoAdvisory

HPE security advisory (AV26-909)

Canada's Cyber Centre relayed HPE advisories covering vulnerabilities in Aruba ClearPass Policy Manager and HPE IceWall products.

Canadian Centre for Cyber Security advisory AV26-909, dated September 10, 2026, flags vulnerabilities in HPE products disclosed on September 9, 2026. Affected products include Aruba ClearPass Policy Manager versions prior to or equal to 6.11.14 and 6.12.8, and multiple HPE IceWall versions and models. Bulletins cover multiple ClearPass vulnerabilities, a remote bypass of security restrictions in IceWall, and an IceWall denial-of-service vulnerability; administrators are urged to review the bulletins and apply updates.

Canadian Centre for Cyber Security·updated 18:35 UTC · 2h ago·first Sep 10, 18:13 UTC · 6d agoAdvisory 2 sources

CVE-2026-73749: HPE ArubaOS-CX RCE

HPE patched CVE-2026-73749, a critical unauthenticated remote code execution flaw in ArubaOS-CX network switch software; affected devices need prompt updates.

HPE released patches for CVE-2026-73749, a critical unauthenticated remote code execution vulnerability in HPE Aruba Networking AOS-CX switch operating system. Published details are limited, but the flaw allows unauthenticated attackers to execute code on affected AOS-CX devices. Administrators running ArubaOS-CX should prioritize applying HPE's update.

SOCRadar·Sep 4, 14:36 UTC · 12d agoVulnerabilityCVE-2026-73749

Risks in IoT Supply Chain

Unit 42 analyzes multilayer IoT supply chain risks across hardware, firmware, and software, citing counterfeit Cisco switches and OpenWrt attacks.

Unit 42 examines weaknesses in the IoT supply chain ecosystem across hardware, firmware, operation, and vulnerability layers, noting that 89% of IT decision-makers reported IoT device growth and IDC forecast 41.6 billion connected IoT devices by 2025. Examples include counterfeit Cisco Catalyst 2960-X switches with possible backdoor access (F-Secure, July 2020), a March 2020 OpenWrt flaw enabling malicious update impersonation, and threat actor interest in TeamViewer remote support software. The report stresses that untracked third-party components and missing device inventories make it hard to assess vulnerability impact across vendors.

Palo Alto Unit 42·Aug 19, 12:05 UTC · 28d agoResearch

Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models

Researchers introduce KoNA, a benchmark exposing vision-language models' failures at selective non-compliance, plus fine-tuning that improves refusal and abstention accuracy.

KoNA is a benchmark for evaluating selective non-compliance in vision-language models across five categories: False Premise, Visual Inaccessibility, Universal Unknown, Task Feasibility and Safety. It tests both query-level and component-level non-compliance using paired single and compound queries, and evaluations across diverse VLMs show models often fail to refuse, correct or abstain appropriately, with failures worsening on compound queries. Fine-tuning VLMs on KoNA examples substantially improves non-compliance accuracy while largely maintaining performance on fully answerable tasks.

Hugging Face daily papers·Sep 3, 20:00 UTC · 13d agoAI research1

Apple security advisory (AV26-930)

CCCS relays Apple's September 14, 2026 security updates fixing vulnerabilities across iOS 27, macOS Tahoe 26.7, Sequoia 15.8, Safari, and other products.

The Canadian Centre for Cyber Security (AV26-930) notes that as of September 14, 2026, Apple has addressed vulnerabilities in iOS and iPadOS prior to 27, macOS Golden Gate prior to 27, macOS Tahoe prior to 26.7, macOS Sequoia prior to 15.8, plus tvOS, watchOS, visionOS 27, Safari, and Xcode prior to 27. The bulletin provides no CVE identifiers or exploitation details. Users and administrators are encouraged to review Apple's security releases and apply the updates.

Canadian Centre for Cyber Security·19:42 UTC · 1h agoAdvisory

Fake OpenAI Codex download tricks macOS users into installing malware

Cato Networks uncovered a malware campaign using sponsored search ads and fake OpenAI Codex pages to deliver an AMOS-like infostealer to macOS users.

Cato Networks researchers discovered a campaign using sponsored search results and a fake OpenAI Codex download portal on Google Sites to lure macOS users. Victims are instructed to paste a Terminal command that decodes a Base64-encoded URL and runs a multi-stage infection chain ending in a universal Mach-O binary. The delivery chain closely resembles Atomic macOS Stealer (AMOS), and related infrastructure impersonating Claude Code was also found. Operators use iframe-based hosting and path/device gating to evade analysts and automated scanners.

Help Net Security·Aug 25, 00:00 UTC · 22d agoMalware in the wild

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a generative time-aware transformer trained on 559 million MIMIC clinical events to model and forecast patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer designed to represent and forecast the full multimodal patient journey across medical images, time-series signals, categorical events, and clinical text. It was trained on over 559 million clinical events from 431,000 hospital visits covering 299,000 patients in the MIMIC dataset family. The architecture combines bidirectional time integration with a variational latent space to capture continuous patient state evolution and clinical stochasticity. NOAH supports autoregressive forecasting with time control, zero-shot classification, and counterfactual intervention simulation, with evaluations on 15 ICD chapters, 29 comorbidities, and time-to-event prediction.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:56 UTC · 8d agoAI research2

MongoDB security advisory (AV26-918)

Canadian Cyber Centre advisory AV26-918 urges patching MongoDB Server vulnerability fixed in 7.0.43, 8.0.32, 8.3.11, and 9.0.1.

The Canadian Centre for Cyber Security issued advisory AV26-918 on September 14, 2026, regarding a vulnerability in MongoDB Server. Affected versions include those prior to 7.0.43, 8.0.32, 8.3.11, 9.1.0-rc0, and 9.0.1. The fix shreds collection validator constants during parsing. Users and administrators are encouraged to review MongoDB's advisory and apply updates as they become available.

Canadian Centre for Cyber Security·Sep 14, 14:30 UTC · 2d agoAdvisory

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a time-aware generative transformer trained on 559 million MIMIC clinical events to forecast multimodal patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer trained on over 559 million clinical events from 431,000 hospital visits by 299,000 patients across the MIMIC dataset family. It uses bidirectional time integration and a variational latent space to model the stochastic evolution of patient states, natively processing medical images, time-series signals, categorical events, and structured or unstructured clinical records. The model supports autoregressive forecasting with optional time control, zero-shot classification, and counterfactual intervention simulation, with strong probing performance across clinical outcomes, 15 ICD chapters, and 29 comorbidities.

Hugging Face daily papers·Sep 7, 20:00 UTC · 9d agoAI research1

IFM/K2-Horizon-MoVA-36B-A4B — new model trending #15 on Hugging Face

IFM released K2-Horizon-MoVA-36B-A4B, an open-weights 36B-parameter MoE model with 4B active parameters and native 512K context.

IFM released the final checkpoint of K2-Horizon-MoVA-36B-A4B, a sparse Mixture-of-Experts model using Mixture-of-Values (MoVA) attention with 36B total and 4B active parameters. The model supports native 524,288-token context and reportedly outscores open-weight dense and MoE models up to 15x its size on agentic and reasoning benchmarks, while competing against closed frontier models. Intermediate checkpoints, training data, the training recipe, and training code are slated for public release.

Hugging Face trending models·Sep 1, 23:01 UTC · 14d agoModel release

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

Study finds zero-shot time-series foundation models underperform on CGM forecasting; fine-tuned Chronos-Bolt cuts RMSE up to 18.4% and dietary context adds signal.

The paper evaluates time-series foundation models for continuous glucose monitoring forecasting across eight public datasets covering Type 1 diabetes, Type 2 diabetes, and non-diabetes populations. Under a unified protocol, zero-shot foundation models did not consistently outperform baselines like Elastic Net and PatchTST, but lightweight fine-tuning did, with fine-tuned Chronos-Bolt reducing RMSE by 6.5%-18.4% in the T1D cohort and 8.6%-18.2% in the non-diabetes/T2D cohort. A residual-based fusion framework adding dietary context from CGMacros reduced overall RMSE by about 3% and postprandial RMSE by about 15% versus CGM-only baselines.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:43 UTC · 6d agoAI research

Nums AI Releases Causilo: A Tabular Foundation Model That Tops TabArena Among Single Models

Nums AI released Causilo, an Apache-2.0 tabular foundation model achieving the highest single-model Elo (1794) on TabArena for classification and regression.

Nums AI released Causilo 1.0.1, a pretrained in-context learning tabular foundation model for classification (up to 10 classes) and regression, with Apache-2.0 code and research-only weights on Hugging Face. It achieved the highest single-model TabArena Elo of 1792.9 overall, beating TabFM (1764.4) and EXAONE Tabular (1758.8), and a maintainer re-run placed it 3rd of 88 including system entries. It also ranked first by CRPS, R² and RMSE on ScoringBench across 101 datasets, and was fastest on fit and predict versus TabICLv2 and TabPFN-3 on an H100 GPU at 8.15 GiB memory. The model was pretrained only on synthetic data, uses cross-attention to keep cost linear in feature count, and version 1.0.1 adds quantile outputs via 999 native quantiles.

MarkTechPost·04:59 UTC · 16h agoModel release

This month in security with Tony Anscombe – August 2026 edition

ESET's August 2026 recap covers the Hugging Face hack, attacks on critical infrastructure, and a spoofed in-flight Wi-Fi network.

ESET's monthly video with Tony Anscombe recaps major cybersecurity stories from August 2026. Topics include the Hugging Face hack, attacks against critical infrastructure, and a spoofed in-flight Wi-Fi network used against passengers.

ESET WeLiveSecurity·Aug 31, 08:55 UTC · 16d agoIndustry

Edge0/Edge0-35B-A3B-preview — new model trending #30 on Hugging Face

Edge0 released a 35B sparse MoE model running in under 3 GiB of memory at 15 tok/s via SSD expert offload and int4 quantization.

Edge0-35b-a3b-preview is a 35B-parameter MoE (256 experts, 4 active per token) built on Qwen3.5-MoE 35B-A3B, shipped as a 4-bit checkpoint with LoRA and prerouter adapters under Apache 2.0. The edge0 framework streams expert weights from SSD on demand, bounding peak active memory at 2.9 GiB and achieving 14.9-17.7 tok/s decode on a Mac mini M4 Pro (MLX backend). Recover-LoRA distillation keeps the int4 model within 3.9 points of its fp16 base (79.2 vs 83.2 average on OpenCompass benchmarks including AIME 2026, HumanEval, GPQA-Diamond, MMLU-Pro, and IFBench).

Hugging Face trending models·Sep 8, 13:56 UTC · 8d agoModel release

CoRA-NAS: Coarse Ranking and Anchor-Residual Refinement for Neural Architecture Search

CoRA-NAS combines zero-cost proxy ranking with low-cost learning-curve refinement, achieving the best worst-space Spearman correlation across NAS benchmarks.

The paper proposes CoRA-NAS, a two-stage neural architecture search framework pairing a static ranking prior (CoRA-Rank) with learning-curve refinement (CoRA-Refine) that extrapolates early validation curves for sampled anchors and propagates residual corrections with an ExtraTrees model at about 1% of full training cost. Across NAS-Bench-201, NAS-Bench-101, TransNAS-Bench-101, and NATS-SSS it achieves mean Spearman correlations of 0.946, 0.715, 0.786, and 0.894 respectively, with the best worst-space correlation of 0.715 among compared methods. On NAS-Bench-201/CIFAR-100 its selected architecture reaches 73.32% accuracy versus a 73.37% ground-truth best.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:49 UTC · 6d agoAI research

Rebuilding AUTOMATIC1111 with Gradio Workflow

Hugging Face demonstrates rebuilding the AUTOMATIC1111 Stable Diffusion web interface using its Gradio Workflow framework.

Hugging Face published a post showing how to rebuild the AUTOMATIC1111 Stable Diffusion WebUI experience with the Gradio Workflow framework. The article body was unavailable, so details beyond the title are limited, but the piece appears to be a tutorial on composing interactive AI interfaces with Gradio Workflow components.

Hugging Face Blog·Sep 10, 00:00 UTC · 6d agoAI tools & infra

Weekly Update 515: Seeking Caffeine Utopia

Troy Hunt·Aug 3, 00:07 UTC · Aug 3, 2026Industry

The Hugging Face incident and the road ahead

OpenAI publishes findings from the Hugging Face security incident and outlines steps to strengthen AI model security, monitoring, and alignment.

OpenAI disclosed details of a security incident involving Hugging Face, the widely used AI model-sharing platform. The company says it is taking steps to strengthen AI model security, monitoring, and alignment in response. The post frames the incident as a catalyst for improving how model providers secure models and infrastructure.

OpenAI News·Aug 26, 00:00 UTC · 21d agoAI safety & security in the wild

The Hugging Face Hack Was Cheap Persistence at Work

Recorded Future analyzes the Hugging Face and OpenAI incident, arguing AI made attacker persistence cheap and alert-based defenses ineffective.

Recorded Future published an analysis of the security incident affecting Hugging Face and OpenAI. The authors argue AI did not make attackers smarter but drastically lowered the cost of maintaining persistent access. They contend that defenses built around alerts cannot keep up with this persistence model, with implications for detection strategy across AI supply chains.

Recorded Future·Aug 10, 00:00 UTC · Aug 10, 2026Data breach

MongoDB security advisory (AV26-911)

Canada's Cyber Centre warns MongoDB Java Driver and Laravel MongoDB (PHP) have vulnerabilities fixed in versions 5.11.1 and 5.11.0.

The Canadian Centre for Cyber Security (AV26-911) reports MongoDB vulnerabilities affecting the Java Driver prior to 5.11.1 and Laravel MongoDB (PHP) prior to 5.11.0. Fixed issues include a native heap use-after-free during cancellation racing a KMS credential fetch in reactive encryption (JAVA-6276) and a query builder fix forcing literal equality when 3-arg where clauses use '=' with array values (PHPLARA-260). Administrators are urged to review the advisories and apply the updates.

Canadian Centre for Cyber Security·Sep 11, 13:38 UTC · 5d agoAdvisory1

OpenAI: Hugging Face Incident a “Warning Shot” to the World

OpenAI says unauthorized message boards were central to the Hugging Face breach, calling it a warning shot for the AI industry.

OpenAI characterized the Hugging Face breach as a warning shot, revealing that unauthorized message boards were at the heart of the incident. The breach targeted Hugging Face, a widely used platform for hosting AI models and datasets. OpenAI's comments highlight growing security risks for shared AI infrastructure and model supply chains.

Infosecurity Magazine·Aug 27, 09:15 UTC · 20d agoData breach

Nuha-Speech: Building General-Purpose Arabic Speech-LLMs

Nuha-Speech initiative builds general-purpose Arabic speech-LLMs using a 1.5M-sample speech QA corpus and fine-tuned Qwen-Omni variants.

The paper introduces Nuha-Speech, an initiative covering dataset construction, model training, and evaluation for Arabic speech large language models. The authors built an Arabic Speech Question-Answering corpus of over 1.5 million training samples and used it for supervised fine-tuning of Qwen-Omni model variants at multiple scales. A tailored evaluation framework with diverse tasks and metrics is designed to assess Arabic speech capabilities under limited resource constraints.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:50 UTC · 6d agoAI research1

AlayaVista: Streaming World Modeling from Panoramic States to Perspective Video

AlayaVista is a camera-controllable streaming video world model that decouples panoramic scene evolution from perspective synthesis, trained on a 1,318-hour 4K dataset.

AlayaVista builds a 360-degree scene prior from a single perspective image, evolves it as a camera-conditioned panoramic latent state, and maps it to perspective video via a latent viewport renderer plus a perspective refiner. Chunk-autoregressive generation and few-step distillation enable efficient streaming. The authors introduce MUGEN, a real-world panoramic video dataset with 1,318 hours of at-least-4K video and rich semantic and geometric annotations.

Hugging Face daily papers·Sep 12, 20:00 UTC · 4d agoAI research

How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code

Hugging Face explains how Inference Endpoints, Jobs, and Buckets power semantic search on Papers with Code.

Hugging Face describes the infrastructure behind search on Papers with Code, built on its Inference Endpoints, Jobs, and Buckets services. The post is a product-focused engineering walkthrough with no security impact.

Hugging Face Blog·Aug 21, 00:00 UTC · 26d agoAI tools & infra

Pelican-Sim 1.0: A General World Model Simulator for Embodied Intelligence

Pelican-Sim 1.0 predicts future observations from visual context and robot actions; four-step autoregressive rollouts yield 5.67x speedup and raise policy success from 70% to 93%.

Pelican-Sim 1.0 is a general world model simulator for embodied intelligence that predicts future observations from visual context and robot actions using a 28-dimensional unified action space valid across heterogeneous embodiments. Sparse mixture-of-experts layers reduce FVD by 6.530 versus the dense backbone, and causal adaptation with few-step distillation yields a four-step autoregressive simulator achieving a 5.67-fold speedup over the 35-step model. Trained on roughly one million real-world and simulated trajectories, PSNR improves over the strongest baselines by 4.636 on AgiBotWorld Beta, 2.080 on RoboMIND, and 10.343 on RoboTwin. Downstream on RoboTwin, adding 500 generated trajectories to 50 demonstrations per task raises policy success from 70% to 93%, and policy evaluation reaches a Pearson correlation of 0.994.

Hugging Face daily papers·Sep 9, 20:00 UTC · 7d agoAI research

Prior Labs Releases TabPFN-3.5: A Tabular Foundation Model That Beats the Winning Otto Kaggle Solution With Default Settings

Prior Labs releases TabPFN-3.5, a 220M-parameter open-weights tabular foundation model that beats the 2015 Otto Kaggle winning score with default settings.

Prior Labs released TabPFN-3.5, a tabular foundation model that predicts in a single forward pass without per-dataset training or tuning. The base model grew from 53M to 220M parameters with a single multitask checkpoint, learned Fourier features, and in-context ECDF rank encodings. It scores 0.375 on the 2015 Otto Kaggle private leaderboard versus the winning 0.382 and claims first place on seven tabular benchmarks including TabArena and BeyondArena. Open weights cover the base, Fast (84M), and Thinking variants, but production use requires the Prior Labs API or a commercial license.

MarkTechPost·06:52 UTC · 14h agoModel release

Black Hat USA 2026 | The 'Breaking' News: The OpenAI–Hugging Face Incident

OpenAI engineers will reconstruct the OpenAI–Hugging Face incident at Black Hat USA 2026, covering attack paths, safeguards, and autonomous-system risks.

A Black Hat USA 2026 session by OpenAI security engineers and researchers will technically reconstruct the OpenAI–Hugging Face incident and its implications for AI security, cyber resilience, and alignment. The talk will address Black Hat Review Board topics including model safeguards, evaluation and containment practices, and defensive uses of AI. It will trace the attack path involving frontier models and discuss implications of increasingly autonomous systems for cybersecurity practitioners.

Dark Reading·Sep 15, 19:27 UTC · 1d agoAI safety & security

Black Hat USA 2026: What the Hugging Face hack tells us about human responsibility

ESET's Black Hat USA 2026 talk argues the Hugging Face hack involving OpenAI models shows autonomous intrusions increase the need for human oversight.

ESET presented a Black Hat USA 2026 session examining the Hacking Face incident that involved OpenAI models. The talk contends that as hacking becomes more autonomous, human responsibility and oversight become more important, not less. The piece is commentary on AI security accountability rather than disclosure of new technical details.

ESET WeLiveSecurity·Aug 13, 09:00 UTC · Aug 13, 2026AI safety & security

Async GRPO with LoRA across HF Jobs: a bucket, a proxy, and no NCCL

Hugging Face blog describes running async GRPO reinforcement learning with LoRA across HF Jobs using a storage bucket and proxy instead of NCCL.

A Hugging Face blog post titled 'Async GRPO with LoRA across HF Jobs: a bucket, a proxy, and no NCCL' explains an asynchronous Group Relative Policy Optimization training setup using LoRA adapters distributed across Hugging Face Jobs workers. The architecture coordinates training through an object storage bucket and a proxy server, removing the need for NCCL collective communication. No full article text was available at classification time.

Hugging Face Blog·Sep 10, 00:00 UTC · 6d agoAI tools & infra

Risky Bulletin: BEC campaign steals €35 million from French notaries

Hackers stole over €35 million from 500+ French notary offices in a four-year BEC campaign; ANSSI spent two years helping evict the attackers.

A business email compromise campaign breached more than 500 French notary offices — about 7% of all French notaries per the Conseil Supérieur du Notariat — over four years, stealing more than €35 million by phishing initial access and silently modifying wire transfer details. France's cybersecurity agency ANSSI worked for two years behind the scenes to help notaries remove the persistent attackers, who had deep access; officials also feared hackers could issue fake notarized acts such as marriage certificates or forged real estate deals. No forged documents have been found so far, but notaries have added two-factor authentication and in-person requirements for banking details, and banks added extra checks in 2024. The newsletter also notes other incidents, including a $320 million Bitcoin extraction from Blockstream's Liquid Network and a JetBrains Cadence breach via TeamCity servers.

Risky Business News·Sep 7, 03:42 UTC · 9d agoPhishing & fraud in the wild1