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d-Matrix Adopts NVIDIA NVLink Fusion for Rack-Scale XPU Deployment

d-Matrix will integrate its Raptor inference XPUs with NVIDIA NVLink Fusion, MGX racks and Spectrum-X networking for rack-scale AI factory deployment.

Inference chipmaker d-Matrix announced adoption of NVIDIA NVLink Fusion to connect its next-generation Raptor XPUs to NVIDIA's scale-up and scale-out networking, MGX rack architecture, and broader AI factory platform. NVIDIA claims 3x lower XPU-to-XPU latency than off-the-shelf Ethernet and 3 TB/s per-XPU all-to-all bandwidth via sixth-generation NVLink. d-Matrix plans to integrate Vera CPUs, ConnectX-9 SuperNICs, BlueField-4 DPUs and Spectrum-X Ethernet, with racks able to work alongside Vera Rubin NVL72 GPU systems. Other NVLink Fusion partners include AWS, Arm, Intel, Fujitsu, Marvell, MediaTek, Samsung and Cadence.

NVIDIA Blogupdated · 13h agofirst · 6d agoAI industry 2 sources

Cortex Xpanse

Palo Alto Unit 42 Cortex Xpanse product-category page published with no article text available for classification.

The URL resolves to the Cortex Xpanse product category listing on the Unit 42 blog rather than a research article. No article body was provided, so no vulnerabilities, incidents, or research findings can be extracted.

Palo Alto Unit 42 · 28d agoIndustry

How XPUs Meet a World-Class AI Factory

NVIDIA argues AI factories with custom XPUs and NVLink Fusion connectivity must optimize tokens-per-second, tokens-per-watt, cost and uptime.

NVIDIA published a blog explaining that AI factories running continuously are economically defined by delivered output: tokens per second, tokens per watt, cost per token, utilization and uptime. It argues hyperscalers and AI-native companies building custom XPUs need infrastructure designed as a complete factory rather than collections of individual accelerators. The piece promotes NVIDIA's NVLink Fusion and full-stack XPU connectivity as the foundation for such world-class AI factory builds.

NVIDIA Blog · 23d agoAI industry

2,000 Leaked Documents Reveal How Russia Turns Engineering Students Into GRU Cyber Operators

Leaked Bauman Moscow State Technical University files reveal a hidden GRU training pipeline feeding APT28 and Sandworm units.

More than 2,000 leaked Bauman Moscow State Technical University documents show that Department No. 4, a hidden program inside the Military Training Center, trained roughly 250 career and reserve students for GRU cyber and intelligence roles across six academic years. Graduates were linked to Military Unit 26165 (APT28), Unit 74455 (Sandworm/APT44) and Unit 29155, and former Unit 26165 commander Viktor Netyksho was involved in department oversight. Reporting by The Insider, The Guardian, Le Monde, Der Spiegel and other outlets, with independent analysis by DomainTools, estimates 10-15 students annually were selected for GRU-related assignments before graduating.

Security Affairs · 13d agoThreat actor1

Leaked Russian Cyber-Operations Training Materials

Leaked Bauman university records reveal a formalized Russian pipeline training GRU cyber personnel, linking a graduate to Sandworm's Military Unit 74455.

Leaked training materials from Bauman university describe a force-generation mechanism feeding graduates into General Staff components, including the GRU and directorates responsible for protected communications, cryptography and information security. A 2024 graduate of Department No. 4, Aleksei Kondrashov, was linked to Military Unit 74455, the GRU unit known as Sandworm, which conducted destructive attacks including the 2017 NotPetya attack. Researchers say the leak shows Russian cyber capability is institutionally sustained through recruitment pipelines beyond the familiar APT28 and Sandworm brand names.

Schneier on Security · 15d agoThreat actor

Unit 42 Deep and Dark Web Service Archives

Palo Alto Networks Unit 42 describes its Deep and Dark Web service monitoring underground forums for compromised credentials and leaked data.

Unit 42's Deep and Dark Web Service page describes monitoring underground forums to identify compromised credentials and leaked data. Analysts investigate suspicious content, escalate prioritized findings, and deliver actionable intelligence to customer SOCs. The page is a service description rather than a news report or incident disclosure.

Palo Alto Unit 42 · 29d agoIndustry

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face Blog · Aug 18, 2026AI tools & infra1

Cortex XSIAM Archives

Palo Alto Networks positions Cortex XSIAM as a purpose-built platform to simplify security operations and speed incident remediation.

The Unit 42 blog page is a product category archive for Cortex XSIAM. The platform is marketed as purpose-built for SecOps transformation, simplifying security operations and accelerating incident remediation against current and future threats. No research findings, incidents, or vulnerabilities are discussed.

Palo Alto Unit 42 · 8d agoIndustry 6 sources

Jackrong/Qwopus3.8-27B-Flash-GGUF — new model trending #26 on Hugging Face

Community fine-tune Qwopus3.8-27B-Flash, built on Qwen3.8-27B, cuts agent reasoning latency with 12.8% faster decoding and 80.7% MTP acceptance.

Jackrong released Qwopus3.8-27B-Flash, a fine-tune of Qwen3.8-27B optimized for long-running agent workloads, reporting 12.8% faster decoding and 80.7% multi-token-prediction acceptance. Training used roughly 1.5 million teacher-scored SFT examples filtered to the top 10%, followed by reinforcement training with NVIDIA NeMo-RL and GSPO. The author notes an explicit trade-off: MMLU-Pro mixed-set scores are lower than the base model, and a known bug can produce incorrect Python indentation. Author-provided benchmarks have not been independently verified.

Hugging Face trending models · 12d agoModel release1

Ai Security Assessment

Unit 42's AI security assessment page describes Palo Alto Networks' offering for evaluating AI system security; no article text is available.

The item is a Palo Alto Networks Unit 42 product category page for 'AI security assessment' with no article body. It likely indexes Unit 42 content or services related to assessing the security of AI systems. No concrete incidents, vulnerabilities, or research findings are described.

Palo Alto Unit 42 · 19d agoAI safety & security

XHToken/Spark-X2.5-4B-GGUF — new model trending #30 on Hugging Face

XHToken released GGUF weights of Spark-X2.5-4B, a compact model with 1M-token context and 200+ language support, under Apache 2.0.

The Hugging Face repository provides BF16 GGUF conversions of Spark-X2.5-4B, a compact general-purpose language model for conversation, writing, translation, reasoning, coding, tool use, and agentic workflows. The model uses a hybrid attention architecture, supports a native context length up to 1M tokens, and covers more than 200 languages. Local inference is supported through Ollama and LM Studio via an XHToken llama.cpp fork, with a --think=false flag to disable thinking mode for faster responses. Released under Apache License 2.0; it was trending #30 on Hugging Face at publication.

Hugging Face trending models · 19d agoModel release

X-AuT: Progressive Audio-Encoder Compression for Speech LLMs with Cross-Scale Distillation

XPeng AI's X-AuT prunes speech LLM audio encoders, cutting Qwen3-ASR-0.6B error from 5.61% to 5.27% with fewer parameters.

X-AuT is a progressive compression framework for speech LLM audio encoders that selects layer combinations via short behavioral probes and restores pruned models using cross-scale distillation and LoRA finetuning while keeping the language-model backbone frozen. Compressing Qwen3-ASR-0.6B from 18 to 16 audio-encoder layers lowered macro-average error from 5.61% to 5.27% on ten Chinese-English benchmarks. A 14-layer model reached 5.75% error with 20.7% fewer audio-tower parameters, and progressive pruning outperformed direct pruning (5.75% vs 6.73%).

Hugging Face daily papers · 7d agoAI research

Comfy-Org/YuE2 — new model trending #30 on Hugging Face

m-a-p's YuE2-3B music generation model and SheetSage2 audio encoder are repackaged in bf16 for ComfyUI and trending #30 on Hugging Face.

Comfy-Org published repackaged bf16 safetensors files for m-a-p's YuE2-3B model and its SheetSage2 audio encoder, organized into ComfyUI checkpoints and audio encoder folders. The repository links to the original m-a-p/YuE2-3B and m-a-p/SheetSage2 model pages and is currently trending #30 on Hugging Face.

Hugging Face trending models · 6d agoModel release 2 sources

Cyberattack forces UT San Antonio to delay start of fall semester

UT San Antonio delayed fall semester start by three days after a weekend cyberattack was caught at the network edge before core systems.

The University of Texas at San Antonio, which serves more than 42,000 students, moved its fall semester start from August 19 to August 24 after a weekend cyberattack on its academic network. Officials said the intrusion attempt was caught at the edge of the network before reaching core systems and that no evidence of data theft has been found. The university took systems and services offline for review, causing phone system outages and password reset tool delays. The incident follows the Instructure Canvas breach during spring finals week that exposed data tied to millions of students and staff worldwide.

Help Net Security · 29d agoExploit / PoC

Idira Archives

Unit 42 page describes Idira, a Palo Alto Networks product providing dynamic privilege controls and zero standing privilege for AI agents.

The Unit 42 product page describes Idira as delivering dynamic privilege controls to humans, machines, and AI agents. It claims AI-driven discovery of hidden risks, just-in-time enforcement of zero standing privilege, and full lifecycle governance on a single control plane. The page contains no news, incident, or release details.

Palo Alto Unit 42 · 16d agoTools

Uncensored AI sold on hacking forum as alternative to ChatGPT and Claude jailbreaks

Sophos found Luciferus, an uncensored AI subscription service likely built on Qwen, sold on the Exploit forum and capable of generating working malware code.

Sophos Counter Threat Unit found an ad for 'Luciferus' posted August 24 on the Exploit forum by a persona named 'Optimus_Prime', claiming a proprietary 120-billion-parameter model that answers requests without ethical restrictions. Sophos assesses with low confidence it is based on Alibaba's open-source Qwen family. Forum tiers cost $35-$75/month, while the website lists Junior/Middle/Pro tiers at $22-$47.14; a test prompt on the Junior tier returned Python remote access trojan source code. Sophos warns such services lower barriers for less skilled cybercriminals and outlast jailbroken mainstream LLMs.

Help Net Security · 1d agoAI safety & security

Threat Bulletin

Palo Alto Networks Unit 42 published a threat bulletin, but no article body was available for detailed analysis.

The feed item contained only the title 'threat bulletin' with no article text. No specific incidents, actors, or vulnerabilities could be extracted from the available content.

Palo Alto Unit 42 · 20d agoAdvisory

Qatar’s Digital Boom Has a Blind Spot: What the 2025-26 Threat Data Is Telling Us

Cyble's Qatar Threat Landscape Report 2025-26 finds Qilin dominated local ransomware while access brokers concentrated on Qatari BFSI and retail access sales.

Cyble's Qatar Threat Landscape Report 2025-26 describes a concentrated threat environment where Qilin accounted for essentially all observed ransomware activity in the country in 2025, including an October campaign, with The Gentleman, Everest, Crypto24, and Payload sharing the space in 2026. Access brokers are selling compromised access, with BFSI and retail accounting for more than half of underground listings, while the education sector sees the most breach and leak incidents. Exploitation activity surged for enterprise remote-access products from Microsoft, Fortinet, Ivanti, and Citrix. The report was published ahead of the CYSEC Qatar summit and cites Qatar's data privacy law and National Cyber Security Agency initiatives.

Cyble · 9d agoThreat actor in the wild

Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

Hugging Face published a tutorial on training and finetuning multi-vector embedding models using the Sentence Transformers library.

Hugging Face's blog walks through training and finetuning multi-vector embedding models with Sentence Transformers. Multi-vector approaches store multiple vectors per document to support late-interaction retrieval. The post is a practical guide for developers building retrieval pipelines with the library.

Hugging Face Blog · 22d agoAI tools & infra1

Unit 42 - Latest Cyber Security Research

Unit 42 briefing warns frontier AI models compress exploit development timelines and highlights 2026 incident response report findings on AI-accelerated attacks.

Palo Alto Networks Unit 42 published a threat briefing and Global Incident Response Report arguing that frontier AI models enable threat actors to move from initial access to exfiltration in minutes rather than months. The report found attacks are 4x faster, 65% of initial access is driven by identity-based techniques, and 87% of attacks unfold across multiple surfaces. The briefing offers CISO guidance on prioritizing defenses against AI-accelerated, automated attacks.

Palo Alto Unit 42 · 28d agoAI safety & security

Next

Palo Alto Networks product-category page describing Next-Generation Firewall threat detection, including encrypted traffic; no standalone article.

The page is a product category listing for Palo Alto Networks Next-Generation Firewalls, stating the products detect known and unknown threats, including in encrypted traffic, using intelligence from many thousands of customer deployments. It contains no research findings, vulnerabilities, or incident details relevant to defenders.

Palo Alto Unit 42 · 28d agoIndustry

Nous Research Adds One-Click Local Model Setup to Hermes Desktop

Nous Research's Hermes Desktop now offers one-click local model setup that reads hardware, picks a fitting quantization, downloads weights, and configures llama.cpp automatically.

Hermes Desktop, the MIT-licensed build of the open-source Hermes Agent, now sets up local models in one click: it reads the machine's hardware, selects a model that fits, downloads weights, and configures the inference runtime. It manages a pinned llama.cpp build with CUDA, Metal, Vulkan, HIP, and CPU backends, and shows green/amber/red memory-fit verdicts per catalog model before download. Quantization floors at 4-bit, and recommended models guarantee at least a 64K context window protected by ordered RAM offload (expert weights first, never the attention cache). It runs on macOS 12+, Windows 10/11, and Linux with no account required for local models.

MarkTechPost · 11d agoAI tools & infra1

Generative Late-Interaction Embeddings For Visual Document Retrieval

GLIE compresses visual document retrieval embeddings to four vectors per page while retaining nearly 80% of uncompressed nDCG@5 accuracy.

Researchers analyzing late-interaction retrieval embeddings found they lie exactly on the unit sphere and concentrate near a manifold of intrinsic dimension five to six. GLIE learns a few k vectors per page that serve as a lightweight index and a basis to regenerate the full embedding set for exact rescoring of top candidates at query time. On ViDoRe v1 with four vectors per page, GLIE retains nearly 80% of uncompressed nDCG@5 versus 70% for the best prior post-hoc method, using a 415K-parameter network trained in under three GPU-minutes on 1,000 pages.

Hugging Face daily papers · 7d agoAI research

PEEP: A Browser RAT Posing as a Chrome Extension

SOCRadar's STRU analyzed PEEP, an emerging Chromium-based RAT disguised as a Chrome extension enabling post-exploitation control of browsers.

SOCRadar's Threat Research Unit (STRU) identified and analyzed PEEP, a Chromium-based post-exploitation toolkit distributed as a browser extension. PEEP provides RAT-style capabilities while posing as a legitimate Chrome extension. It is assessed as an emerging threat worth monitoring by defenders.

SOCRadar · 12d agoMalware

Tracking Elirks Variants in Japan: Similarities to Previous Attacks

Unit 42 links new Elirks backdoor variants attacking Japanese organizations to 2012 Taiwan attacks, delivered via spear-phishing PDFs exploiting Adobe Flash CVE-2011-0611.

Unit 42 analyzed new Elirks backdoor variants found in an attack on a Japanese business, noting strong similarities to 2012 attacks on Taiwanese ministries. The backdoor retrieves its C2 address from attacker-created accounts on Japanese blog and SNS services. Recent deliveries used an airline e-ticket lure named "E-TKT" with a PDF exploiting Adobe Flash CVE-2011-0611. Shared infrastructure and tactics with the Scarlet Mimic campaign suggest possible ongoing cyber espionage across East Asia.

Palo Alto Unit 42 · Aug 17, 2026Threat actor in the wildCVE-2011-0611

DavidAU/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NEO-CODER-MAX-MTP-GGUF — new model trending #8 on Hugging Face

A new Qwen3.8-27B GGUF fine-tune claims ARC-C 735 at 8-bit with thinking tokens cut 2x-10x versus the base model.

Independent creator DavidAU released a GGUF fine-tune of Qwen3.8-27B built with Unsloth, claiming ARC-C of 735 at 8-bit and 719 at 4-bit, trending #8 on Hugging Face. The 'TURBO' variant cuts thinking tokens by one half to as much as one tenth while retaining output quality and detail. The repo ships both regular and MTP quants and claims gains over the base model across seven benchmarks, using 'Cold Fusion (GAIN + Unsloth)' and 'Fable Fusion 711' training methods.

Hugging Face trending models · 15d agoModel release

Attack hides malware in PNGs and drops custom reverse tunnel on victims' machines

A ClickFix social engineering wave delivers a multi-stage attack that hides malware in PNG files and installs a custom reverse tunnel.

The Register reports a new wave of ClickFix social engineering attacks that trigger a multi-stage infection chain on victim machines. The attack reportedly conceals malware inside PNG image files and deploys a custom reverse tunnel tool for attacker access. Further technical details are limited in the available text.

The Register · Security · 16d agoMalware in the wild

Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI

Hugging Face released @huggingface/kernels, a library offering 200+ WebGPU compute kernels to accelerate AI inference locally in browsers.

Hugging Face introduced the @huggingface/kernels package, bundling more than 200 optimized WebGPU compute kernels for running AI workloads locally. The release targets browser-based and on-device inference, reducing reliance on server-side compute. No article body was available beyond the title, so benchmark results and supported models are not specified.

Hugging Face Blog · 16d agoAI tools & infra