Search: “QEMU”

Debian 13.7 ships the fixes behind 92 security advisories, updates 106 packages

Debian 13.7 'trixie' point release bundles 92 security advisories and 106 package updates, including kernel, glibc, u-boot and qemu fixes.

Debian shipped version 13.7 of 'trixie', folding in 92 previously published security advisories and corrections to 106 source packages, including six Linux kernel advisories (DSA-6381, DSA-6393, DSA-6405, DSA-6415, DSA-6466, DSA-6477). glibc fixes a buffer overflow (CVE-2026-5928) and buffer underflow (CVE-2026-5450), with 17 packages rebuilt against the updated library; qemu carries 25 CVEs including a secure boot bypass (CVE-2026-16288), imagemagick 24, wolfssl 15 and perl 13. Boot-chain fixes include a u-boot FIT image verification bypass (CVE-2026-46728), a BOOTP/DHCP buffer overread (CVE-2024-42040), and corrected intermediate certificate verification in sbsigntool. The installer was rebuilt with kernel ABI 6.12.107+deb13, and existing systems receive the fixes through normal package mirror updates.

Help Net Security·Sep 14, 07:40 UTC · 2d agoAdvisoryCVE-2026-5928CVE-2026-5450CVE-2026-34873+17 CVEs

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·Sep 4, 12:43 UTC · 12d agoModel release1

New Zapscape KVM Flaw Could Let Privileged L1 Guest Code Escape to Linux Hosts

The Hacker News·Aug 6, 17:58 UTC · Aug 6, 2026Exploit / PoC in the wildCVE-2026-64561CVE-2026-53359CVE-2026-46316

Benchmarking Qwen3.8 27B quantizations: 4-bit holds up, 1-bit collapses

Quesma benchmarks Qwen3.8 27B quantizations: 4-bit Q4_K_M matches BF16 on key benchmarks while 1-bit collapses to random chance.

Quesma spent roughly $3,000 on Modal GPUs testing Unsloth GGUF quantizations of Qwen3.8 27B across GPQA Diamond, IFBench, and Terminal-Bench 2.1. The 17 GB Q4_K_M quantization matched the 55 GB BF16 model on Terminal-Bench 2.1 and showed little degradation down to 4-bit, while the 2-bit UD-Q2_K_XL dropped noticeably. At 1-bit, scores on GPQA Diamond fell to random-guess levels, with longer reasoning making results worse, and reasoning effort settings significantly affected outcomes.

Hacker News · AI·Sep 8, 14:49 UTC · 8d agoAI researchHN 56↑ · 30 comments1

Redtail Payload Analysis [Guest Diary], (Wed, Sep 9th)

SANS guest analyst detonated a RedTail Linux sample from a DShield honeypot, finding process masquerading as php-fpm, monitoring-kill behavior, and a TCP listener.

A DShield honeypot captured multi-architecture RedTail Linux executables (ARM, ARM64, i686, RISC-V, x86-64) deployed via shell scripts. Dynamic analysis of the UPX-packed, statically linked x86-64 sample (SHA-256 63be5f38...d35e) in an isolated Ubuntu 24.04 VM on Proxmox showed it renamed its process via prctl(PR_SET_NAME), killed a filesystem-monitoring process, and opened a TCP listening socket while surviving processes posed as php-fpm or PostgreSQL-like workers. Differential memory images pre- and post-execution were captured from the hypervisor for forensics.

SANS Internet Storm Center·Sep 10, 12:58 UTC · 6d agoMalware in the wild1

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·Sep 1, 07:01 UTC · 15d agoModel release

Testing race conditions with memory access tracing and stack-based delay injection

Google Project Zero released MAccConc, Linux kernel tooling that traces memory accesses to explore and test race condition interleavings.

A Google Project Zero researcher published MAccConc (Memory Access Concurrency), tooling for exploring possible interleavings of multithreaded test cases in the Linux kernel, available on GitHub. The tools use KCOV with ASAN outline-mode instrumentation to record per-access memory traces, enabling automatic testing of all A-B-A interleavings plus terminal and GUI explorers for manual analysis. The work targets confirming race condition candidates, building reliable regression tests, and enabling concurrency fuzzing, drawing on ideas from SKI and Ned Williamson's sockfuzzer.

Google Project Zero·Sep 8, 07:00 UTC · 8d agoResearch1

unsloth/Qwen3.8-Flash-Next-GGUF — new model trending #21 on Hugging Face

Qwen released Qwen3.8-Flash-Next, an experimental 125B-parameter open-weight MoE previewing the Qwen4 architecture, with Unsloth shipping optimized GGUF quants.

Qwen released Qwen3.8-Flash-Next, an experimental open-weight preview of the architecture planned to underpin Qwen4. The model has 125B parameters with 6B activated, 512 experts (10 routed plus 1 shared), Qwen Sparse Attention (QSA), Gated DeltaNet, Gated Residual, and n-gram embeddings, with 262,144-token native context extendable to 1,000,000 tokens. Unsloth provides Dynamic 3.0 GGUF quantizations, and multi-token prediction (MTP) delivers 1.3-1.7x faster inference via llama.cpp or Unsloth Desktop.

Hugging Face trending models·Aug 26, 12:29 UTC · 21d agoModel release1

TuxBot v3: Inside an IoT Botnet Framework With LLM

Unit 42 uncovers TuxBot v3, an LLM-assisted IoT botnet framework with 17-architecture builds, Telnet brute-forcing, and DDoS capabilities.

Palo Alto Unit 42 identified TuxBot v3 Evolution, a modular IoT botnet framework derived from AISURU, Wuhan-lineage botnets, and MHDDoS. The C-based bot brute-forces Telnet with 1,496 credential pairs, targets over 30 IoT device families, and communicates with a Go-based C2 over encrypted TCP with multiple fallback mechanisms including DGA, P2P, and DNS TXT. LLM-assisted development left hallucinated crypto implementations and broken exploit modules in the analyzed samples, though roughly 70% of core functionality works. Researchers warn polished production builds likely exist, raising the threat potential.

Palo Alto Unit 42·Aug 19, 12:03 UTC · 28d agoMalware1

nvidia/Qwen3.8-Flash-Next-NVFP4 — new model trending #28 on Hugging Face

NVIDIA released an NVFP4 4-bit quantized build of Alibaba's Qwen3.8-Flash-Next, a 125B-parameter MoE vision-language model, via Model Optimizer.

The checkpoint quantizes Qwen3.8-Flash-Next — a hybrid-attention (Gated DeltaNet and Qwen Sparse Attention) Mixture-of-Experts model with 125B total and 6B activated parameters, plus 51B n-gram embeddings and 4B MTP — using NVIDIA Model Optimizer v0.46.0. NVFP4 benchmarks stay close to FP8: GPQA Diamond 91.5 vs 92.0, MMMU Pro 78.3 vs 77.1, Terminal-Bench 2.1 82.9 vs 83.3. It targets Blackwell B200/B300 GPUs, runs on vLLM, supports 262K context extendable to 1M tokens, and is licensed under the NVIDIA Open Model License with Qwen Community License 1.0.

Hugging Face trending models·Sep 2, 04:03 UTC · 14d agoModel release

UBoatRAT Navigates East Asia

Unit 42 discovers UBoatRAT, a new custom RAT targeting South Korean and video-game industry personnel, delivered via Google Drive with GitHub-based C2 and BITS persistence.

Unit 42 identified UBoatRAT, a new custom remote access trojan first found in May 2017, whose initial version used a public Hong Kong blog service and a compromised Japanese web server for command and control. The latest variants target personnel or organizations related to South Korea or the video games industry, are delivered through Google Drive, and masquerade as Microsoft Word, Excel, or folder icons. The RAT checks for virtualization software and domain join, retrieves its C2 address from a Base64-encoded string in a GitHub-hosted file, uses a custom XOR-encrypted C2 protocol, and maintains persistence via Windows Background Intelligent Transfer Service (BITS) jobs that survive reboots.

Palo Alto Unit 42·Aug 17, 12:55 UTC · Aug 17, 2026Malware in the wild1

LLaDA-UI: Bringing Block-wise Diffusion to Vision-Language GUI Agents

LLaDA-UI, a 16.7B block-wise diffusion vision-language GUI agent, outperforms Qwen2.5-VL-7B and beats Qwen3-VL-8B on four of six GUI benchmarks.

LLaDA-UI is a 16.7B-parameter MoE-based, block-wise diffusion vision-language GUI agent built on the LLaDA2.0-mini-base diffusion language backbone with a native-resolution vision encoder. It uses a two-stage pipeline: general multimodal pre-training followed by GUI-agent supervised fine-tuning on mobile, desktop, web, and grounding data. It substantially outperforms Qwen2.5-VL-7B and surpasses Qwen3-VL-8B on four of six reported GUI benchmarks, establishing block-wise diffusion as a practical paradigm for latency-sensitive multimodal agents.

Hugging Face daily papers·Sep 8, 20:00 UTC · 7d agoAI research

Risky Bulletin: Dutch intel services to get extensive new powers

Netherlands proposed a bill granting AIVD and MIVD expanded warrantless tapping, faster hacking powers, and forced data disclosure, citing Russia, China, and Iran threats.

The Dutch government introduced a bill greatly expanding surveillance powers of intelligence agencies AIVD and MIVD, allowing up to one year of tapping without pre-approval and simplified hacking operations against 'foreign adversaries'. Agencies could compel Dutch companies or citizens to provide data under threat of charges, share data with the private sector, and oversight bodies would merge into a new CTT board. The bill follows similar overhauls in Ireland, Germany, and France after Russia's invasion of Ukraine. The newsletter also reports Moonwell hacked for $8.7M, a Cosmos EVM bug exploited for ~$3M, ShinyHunters listing McKesson with claimed hundreds of millions of records, and a pro-Kremlin DDoS claim against Norway's government network.

Risky Business News·Aug 31, 03:25 UTC · 16d agoPolicy & legal

Qwen-Drive 1.0 tells you why it brakes, just don't expect the explanation to match the maneuver

Alibaba's Qwen-Drive 1.0 adds 3D perception and planning modules to Qwen3.5-4B for driving tasks, though explanations often mismatch maneuvers.

Qwen-Drive 1.0, built on Qwen3.5-4B, combines spatial perception, traffic question answering, and route planning in one vision-language model, adding a bird's-eye-view perception module and a Planning Expert trained via staged fine-tuning and reinforcement learning. The paper finds text-image models do not inherently grasp 3D space; spatial accuracy only improved when the base vision-language model itself was trained on spatial tasks, while avoiding catastrophic forgetting of general knowledge. The cut reinforcement learning-trained version halved road-departure rate in simulation from 24% to 12%, and the model beats specialized driving models in most of Qwen's benchmarks, but its explanations sometimes conflate causes like distant red lights and crossing children, and results partly rest on self-designed tests. The work follows prior findings from PaLM-E and a UC Santa Cruz adversarial sign attack on DriveLM showing VLM driving models' reasoning and spatial gaps.

The Decoder·Sep 7, 12:15 UTC · 9d agoAI research

Desktop and IoT threat statistics for Q2 2026

Kaspersky Securelist·Aug 10, 09:52 UTC · Aug 10, 2026Ransomware in the wildCVE-2026-33825CVE-2026-50751CVE-2026-50752

Show HN: Nari Qwen3-TTS and Qwen3-ASR – High accuracy, low latency and cost

Nari Labs claims top Coval voice AI benchmark rankings with low-latency, low-cost Qwen3-ASR and Qwen3-TTS inference endpoints.

Nari Labs says its Qwen3-ASR Fast endpoint ranks #1 in Coval's time-to-final-segment latency (p50 44 ms) with 3.6% WER at $0.12/hour, behind only AssemblyAI Universal 3.5 Pro on accuracy. Its Qwen3-TTS Fast ranks #2 in time-to-first-audio (p50 63 ms) and #1 in WER at 3.8%, priced at $10 per 1M characters. The company reports beating the official Qwen3 TTS Flash Realtime endpoint (8.8% WER, 692 ms median TTFA) and Baseten's dedicated endpoint (6.0% WER, 101 ms). Public beta APIs are moving to paid general availability with $20 in credits for existing accounts.

Hacker News · security·Sep 14, 16:07 UTC · 2d agoAI tools & infraHN 21↑ · 7 comments

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.CR·Sep 10, 14:19 UTC · 6d agoResearch

Qodana 2026.2 adds post-quantum crypto checks for JVM code

Help Net Security·Aug 3, 00:00 UTC · Aug 3, 2026Vulnerability

What your vendor says about PQC tells you if they are ready

Allot CTO outlines a telecom post-quantum migration playbook: inventory crypto, deploy hybrid ML-KEM on TLS first, and avoid missed interfaces.

Dr. Yaakov Stein, VP CTO of Allot, explains how mobile operators should triage post-quantum migration by data shelf life, protecting subscriber identity mappings, billing records, and call metadata that stay sensitive for years. He recommends starting with a comprehensive crypto inventory, then hybrid ML-KEM key exchange on TLS-protected 5G SBA and management interfaces, followed by IPsec backhaul and roaming links. Stein warns that migrations most often fail operationally through missed legacy interfaces such as SSH, RADIUS, or forgotten load balancers, and cites the early Kyber multi-packet TLS client hello issue as an example of middlebox incompatibility.

Help Net Security·Sep 1, 00:00 UTC · 15d agoIndustry

Retrofitting Code Using LLMs to Support Exceptional Behavior

EXCODER combines static/dynamic analysis with LLMs to retrofit exception-handling code, achieving 85.92% pass@1 with Qwen 2.5 Coder 32B on Java benchmarks.

The paper introduces the task of retrofitting existing code with Exception Related Code (throw statements, guarding conditions, try/catch blocks) so that given Exceptional Behavior Tests pass. EXCODER performs context engineering by integrating static and dynamic program analysis output with LLMs; it was evaluated on a benchmark built from 304 methods across 75 GitHub Java projects. Combined with Qwen 2.5 Coder 32B, EXCODER achieves pass@1, 5, and 10 rates of 85.92%, 86.18%, and 86.51%, roughly 13 percentage points over baseline, and manual inspection reveals remaining limitations.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 16:18 UTC · 7d agoAI research1

HyQuant: Hybrid-Precision Quantization for LLM Attention

HyQuant keeps most LLM attention states low-bit while preserving vertical-line tokens and local windows in high precision, maintaining near-lossless accuracy.

HyQuant is a hybrid-precision quantization framework for LLM attention that quantizes most attention states to low bits while keeping accuracy-critical vertical-line tokens and local-window states in full precision, selected via lightweight attention-pattern signals. In the prefill stage it uses a hybrid-precision attention operator, and in the decode stage it applies the same principle to KV-cache compression with fused dequantization and attention computation. Across diverse tasks, models, and datasets it maintains nearly lossless accuracy; code is available on GitHub.

Hugging Face daily papers·Aug 27, 20:00 UTC · 19d agoAI tools & infra1

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·Sep 5, 19:12 UTC · 10d agoAI tools & infra1

Nearly half of enterprises have no one leading PQC migration

Axiad survey finds 46% of enterprises lack a single leader for post-quantum cryptography migration despite most maintaining cryptographic inventories.

Axiad research on post-quantum cryptography (PQC) readiness found 75% of respondents maintain continuously updated inventories of certificates, keys, and algorithms, but 46% have no single person owning the migration. About half have never formally assessed whether public-facing infrastructure supports post-quantum key exchange. 67% said the harvest-now-decrypt-later threat is an active priority, with competing priorities, budget constraints, and lack of regulatory guidance cited as top obstacles; executives were more confident than PKI practitioners.

Help Net Security·Aug 21, 00:00 UTC · 26d agoPolicy & legal

ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF — new model trending #3 on Hugging Face

ISTA-DASLab releases GSQ-RCO non-uniform GGUF quantizations of Qwen3.8-27B down to 2.5 bpw, with task-lossless IQ3_S matching BF16 benchmark scores.

ISTA-DASLab released GGUF quantizations of Qwen3.8-27B produced with GSQ (Gumbel-Softmax Quantization) and RCO (Riemannian Constrained Optimization), non-uniform methods that allocate per-tensor precision via gradient-based search under a total size budget. Four checkpoints range from 2.50 bpw (8.4 GB) to 3.50 bpw (11.8 GB), plus a BF16 vision projector (mmproj) enabling multimodal use. The recommended IQ3_S build is task-lossless, matching the BF16 base exactly on AIME25 (100.00) and LiveCodeBench v6 (85.71) at roughly one fifth of the BF16 size. Optional -mtp variants add a Multi-Token Prediction head for speculative decoding in llama.cpp.

Hugging Face trending models·Aug 28, 18:38 UTC · 18d agoModel release1

Claude Fable 5.1's language is less "load-bearing" than its predecessor's

Arena.ai found Claude Fable 5.1 writes 30% longer answers with fewer em dashes, hedges, and validation phrases than Fable 5.

Arena.ai compared tens of thousands of high-reasoning Text Arena outputs from Anthropic's Claude Fable 5 and Fable 5.1. Fable 5.1's median answer length rose 30% to 414 words (from 319), remaining 21% shorter than Opus 5's 525. Em-dash usage fell from 16.2 to 11.0 per 1,000 words while semicolons rose to 6.09, hedges like 'perhaps' and 'arguably' dropped 36%, and praise appeared in 1.98% of responses versus 3.17%. Long content words fell from 42.6% to 38.6% and abstract nouns declined 25%, suggesting the successor's language is less 'load-bearing'.

The Decoder·Sep 10, 15:26 UTC · 6d agoAI research1

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, 00:00 UTC · 29d agoAI tools & infra1

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·updated Sep 12, 05:56 UTC · 4d ago·first Sep 11, 03:35 UTC · 5d agoModel release 7 sources

When the prompt becomes the payload: A practical pen-testing guide for GenAI, LLM and RAG applications

CSO Online publishes a practical penetration-testing guide for GenAI, LLM, and RAG applications, covering prompt injection, retrieval poisoning, and tenant isolation testing.

The guide frames LLM applications as attack graphs spanning prompts, retrieval layers, vector stores, tools, identities, and downstream APIs, arguing that conventional web testing misses instruction-vs-data channel risks. It builds on OWASP prompt injection guidance (direct vs. indirect injection) and NIST's 2025 adversarial machine-learning taxonomy, noting that RAG and fine-tuning do not remove injection risk. Recommended practices include documenting trust transitions across components, using canaries and synthetic records to avoid test side effects, running multi-turn and obfuscated injection campaigns, and verifying chains from poisoned documents to observable state changes. It also details testing RAG pipelines via controlled document poisoning across metadata, OCR layers, and code comments, plus cross-tenant isolation checks on retrieved document IDs.

CSO Online·Sep 9, 10:00 UTC · 7d agoAI safety & security1

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.

The Rosetta system for the AlexandriaX-2026 shared task fine-tunes a LoRA adapter on NileChat-3B for context-aware English-to-dialectal Arabic dialogue translation. The adapter was additionally pretrained on MADAR and PADIC dialect corpora for the unconstrained track. It achieved spBLEU 26.10 (4th, constrained) and 25.09 (5th, unconstrained). External dialect pretraining improved only two of thirteen dialects while slightly degrading overall performance, indicating negative transfer.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 16:15 UTC · 7d agoAI research1

[0day-rubbish] QuantaStor 6.8.3.018 Command injection in the alert-mail command via the smtpPassword field (8.8)

QuantaStor 6.8.3.018 has a CVSS 8.8 command injection in its alert-mail command, exploitable via the smtpPassword field.

0day Rubbish Research Team disclosed a command injection (CWE-78) in QuantaStor 6.8.3.018's alert-mail command, reachable through the smtpPassword field. The flaw scores CVSS 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H). No CVE identifier or evidence of active exploitation is mentioned in the disclosure.

Full Disclosure·Sep 8, 17:31 UTC · 8d agoVulnerability 2 sources

VU#308749: Remote Code Execution and Arbitrary File Read Vulnerabilities in Kaltura Servers

Insecure deserialization in Kaltura's legacy HTML5 Player V2 (mwEmbed) allows arbitrary file read and remote code execution; Player V7 is unaffected.

CERT/CC issued VU#308749 for two flaws in Kaltura's HTML5 Player V2 library (mwEmbed/html5lib), both caused by the same insecure deserialization bug. The flaws enable arbitrary file read and remote code execution via the exposed mwEmbedLoader.php endpoint. Affected versions include html5lib v2.45, v2.103 and earlier, and other v2.x releases; the currently supported Player V7 is unaffected. No evidence of exploitation was cited.

CERT/CC Vulnerability Notes·Aug 25, 16:11 UTC · 22d agoVulnerability

BreezeBlue/Breeze-TTS-2 — new model trending #19 on Hugging Face

BreezeBlue open-weights Breeze TTS 2, a bilingual text-to-speech model it ranks #1 among open-weight models on the Artificial Analysis TTS leaderboard.

BreezeBlue released open weights and Apache 2.0-licensed PyTorch inference code for Breeze TTS 2 on 2026-08-25. The text-to-speech model supports English and Chinese, voice cloning, reference-free voice design, voice direction, and inline vocal events like (laugh) and (sigh). Reported performance includes #1 open-weight ranking on the Artificial Analysis Elo leaderboard, under 40 ms time-to-first-audio, a 0.32 real-time factor on an NVIDIA H100, and about 7.7 GiB GPU memory for eager inference.

Hugging Face trending models·Aug 25, 16:39 UTC · 22d agoModel release

CTEM Is Not About the Stages. It’s About the Outcome.

Horizon3 argues CTEM programs should measure continuously reduced exposure rather than mapping technologies to Gartner's five stages.

Horizon3 contends that Continuous Threat Exposure Management should be judged by one outcome: continuously reducing attacker-reachable exposure, not by mapping a technology to each of Gartner's five stages. The post argues validation and verification, not visibility or closed tickets, provide evidence that attack paths are actually broken. It describes a Discover, Validate, Prioritize, Remediate, Verify, Repeat motion as its operationalization of CTEM.

Horizon3.ai·Sep 2, 13:11 UTC · 14d agoIndustry

G7 Urges Fast-Track on Quantum-Safe Cybersecurity Rules

G7 cybersecurity agencies led by France's ANSSI urged accelerated transition to post-quantum cryptography, prioritizing critical systems and phased, risk-based migration.

Under France's 2026 G7 Presidency, ANSSI, chairing the G7 Cybersecurity Working Group, published a September 3 call to action urging governments and organizations to begin quantum-safe (PQC) transitions now, reframing the quantum threat as near-term. The document, signed by the national cyber agencies of all G7 members and supported by the EU Commission and ENISA, outlines five priorities including national PQC strategies, R&D, public-private partnerships, and integrating PQC into cybersecurity requirements. It recommends cryptographic inventories, dependency mapping, prioritizing the most critical systems, and buying PQC-integrated products during normal renewal cycles. ANSSI will stop vetting non-quantum-safe products in 2027, with PQC mandatory in some security product procurement by 2030.

Infosecurity Magazine·Sep 4, 09:25 UTC · 12d agoPolicy & legal

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

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·Aug 28, 11:26 UTC · 19d agoModel release

ukisai/Swift-Qwen3.8-27b — new model trending #30 on Hugging Face

UkisAI releases Swift-Qwen3.8-27B, a Qwen3.8-27B derivative using 58.3% fewer thinking tokens with <1% performance loss and ~1.95x speed-up.

UkisAI released Swift-Qwen3.8-27B, a reasoning-efficient derivative of Qwen3.8-27B that cuts thinking-token usage by 58.3% while staying within 1% of base performance, yielding a 1.95x speed-up on several tasks. The model was fine-tuned by penalizing reasoning-marker tokens that trigger overthinking, plus a transfer component from BottleCap AI's ThinkingCap-Qwen3.6-27B. Benchmarks include GPQA-Diamond 88.28% (base 88.38%), MMLU-Pro 84.95% (base 85.47%), and AIME 2026 94.00% (base 98.67%), with mean-token reductions of roughly 27-46% across tests. GGUF weights are available on Hugging Face alongside enterprise licensing options.

Hugging Face trending models·Sep 8, 13:35 UTC · 8d agoModel release

Claude's new system prompt really doesn't want to reproduce song lyrics

Anthropic published updated Claude consumer system prompts, including changes steering the model away from reproducing song lyrics, likely over copyright concerns.

Anthropic publishes system prompts for Claude.ai and Claude mobile apps, including historic revisions, and has reorganized them into an index with per-model pages such as the Haiku 4.5 page showing the original October 15, 2025 prompt and an updated January 18, 2026 version. The latest consumer prompt strongly discourages reproducing song lyrics, a behavioral constraint likely tied to copyright considerations. Prompts for Claude Cowork and Claude Code are not included in the published set.

Simon Willison·Sep 2, 14:16 UTC · 14d agoAI safety & security

Future-Proofing the Internet: Akamai Achieves End-to-End PQC

Akamai says it achieved end-to-end post-quantum cryptography across its network to future-proof internet traffic.

Akamai announced it has achieved end-to-end post-quantum cryptography (PQC) across its services. The company frames the move as future-proofing the internet against quantum decryption threats. No article text was available; details are limited to the announcement title.

Akamai Blog·Aug 19, 08:00 UTC · 28d agoIndustry