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Cisco Warns of Seven ClamAV Flaws, Two With Public PoCs

Cisco warns of seven ClamAV denial-of-service flaws in Secure Endpoint Connector, two with public PoCs; patches due in August.

Cisco warned that seven ClamAV denial-of-service vulnerabilities, tracked as CVE-2026-20337 through CVE-2026-20339 and CVE-2026-20345 through CVE-2026-20348, affect the Secure Endpoint Connector on Windows, macOS and Linux. Two flaws, CVE-2026-20337 (CVSS 7.5, out-of-bounds write) and CVE-2026-20338 (memory double-free), have public proof-of-concept code, but Cisco PSIRT reports no evidence of malicious exploitation. Fixes shipped in ClamAV 1.5.4, with Cisco patches due in August and no workaround available. Windows is rated high risk because ClamAV runs with elevated privileges there.

Security Affairs·Aug 11, 16:05 UTC · Aug 11, 2026VulnerabilityCVE-2026-20337CVE-2026-20338CVE-2026-20339+4 CVEs

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ClamAV Vulnerabilities Affecting Cisco Products: August 2026

Cisco patched ClamAV vulnerabilities that allow remote attackers to cause denial-of-service conditions, rated High only for Windows-based platforms.

Cisco released an advisory covering multiple ClamAV vulnerabilities that could let a remote attacker interrupt scanning operations with a denial of service. Software updates are available for affected Cisco platforms, and no workarounds exist. The Security Impact Rating is High for Windows-based platforms because ClamAV runs there in a privileged security context.

Cisco Security Advisories·Aug 13, 20:11 UTC · Aug 13, 2026Advisory

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ZDI-26-583: Clam AntiVirus 7z Archive Parsing Integer Overflow Remote Code Execution Vulnerability

Zero Day Initiative discloses CVE-2026-20215, an integer overflow in ClamAV's 7z archive parsing enabling remote code execution, rated CVSS 8.4.

The Zero Day Initiative published ZDI-26-583 for an integer overflow in Clam AntiVirus's 7z archive parsing. A remote attacker can execute arbitrary code when the antivirus processes a crafted archive, with attack vectors varying by implementation. The flaw is tracked as CVE-2026-20215 and rated CVSS 8.4. The advisory does not mention active exploitation.

ZDI Published Advisories·Aug 13, 05:00 UTC · Aug 13, 2026VulnerabilityCVE-2026-202151

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Security Affairs newsletter Round 590 by Pierluigi Paganini

Weekly Security Affairs newsletter roundup aggregating top cybercrime, malware, APT and AI security stories including ExfilSquad, Kimwolf v7 and Kimsuky AI use.

This is the Round 590 weekly newsletter from Security Affairs, linking to the week's major stories rather than reporting a single incident. Headlines include ExfilSquad extortion, a 7.3M chess.com record leak, Kimwolf botnet v7, SharePoint exploitation after a public PoC, Kimsuky integrating AI, and China-linked autonomous-style attacks. It is a digest and promotional item with no standalone technical details.

Security Affairs·Aug 16, 08:31 UTC · Aug 16, 2026Industry

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Identifying a BOLA Vulnerability in Harbor, a Cloud

Unit 42 found a BOLA flaw, CVE-2024-22278 (CVSS 6.4), letting Maintainers improperly alter Harbor project metadata; fixed in versions 2.9.5, 2.10.3, and 2.11.0.

Unit 42 researchers identified a broken object-level authorization flaw, CVE-2024-22278, in Harbor, a CNCF-graduated cloud-native container registry with 1.8 million downloads. The flaw (CVSS 6.4) lets users with the Maintainer role create, update, and delete project metadata, actions reserved for ProjectAdmin, risking data exposure, integrity compromise, and circumvention of vulnerability scanning. Harbor patched the issue in versions 2.9.5, 2.10.3, and 2.11.0. The finding came from Unit 42's automated BOLA detection tool built on generative AI.

Palo Alto Unit 42·Aug 17, 12:35 UTC · Aug 17, 2026VulnerabilityCVE-2024-22278

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⚡ Weekly Recap: VMware Exploits, Windows 0-Day, MCP Attacks, Browser Hijacks and More

Weekly recap: suspected China-nexus APT exploited VMware vCenter CVE-2026-59310, Lazarus used Windows zero-day CVE-2026-68820, and macOS flaw dropped Monero miners.

The week's top stories included a suspected China-nexus APT exploiting VMware vCenter CVE-2026-59310 (CVSS 9.8), a directory-traversal flaw enabling arbitrary code execution, with backdoors, reverse SSH and Babuk-derived ransomware deployed, per QUIRSO. NCSC-NL reported active exploitation of macOS Screen Sharing flaw CVE-2026-65400 (CVSS 9.8) to install Monero miners on systems with port 5900 exposed. Lazarus Group exploited Windows zero-day CVE-2026-68820 (CVSS 7.0) in Operation Dream Job, delivering ForestTiger and Troy backdoors to defense and aerospace targets. GeoServer patched a critical SQL injection flaw exploited within hours of disclosure, and Jamf analyzed the new Amnesia Stealer for macOS with live browser control.

The Hacker News·Aug 17, 17:57 UTC · Aug 17, 2026Exploit / PoC in the wildCVE-2026-59310CVE-2026-65400CVE-2026-688201

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Researchers Uncover 10,000+ Malware Loaders Behind YouTube and SEO Poisoning Campaign

Unit 42 uncovers CL-CRI-1171, a two-year pay-per-install campaign distributing 10,000+ OfferLoader samples via YouTube and SEO poisoning.

Palo Alto Networks Unit 42 tracked a campaign as CL-CRI-1171, an infection-as-a-service platform operating for at least two years. It used 11 YouTube gaming channels with hundreds of thousands of subscribers and SEO-poisoned download pages for trojanized WinDirStat and Bluetooth driver installers to distribute OfferLoader, a disposable loader embedded in Inno Setup installers. Payloads delivered included Insomnia RAT (Node.js and Python backdoors), ARKTunnel (a WebSocket-based RAT using LSB steganography), and Docro Hijacker (Chrome browser hijacker), with later infections delivering GCleaner and Socks5Systemz. Over 200 rotating domains across .xyz, .cfd, .space, and .info TLDs were used, with gating filters that served broken links or decoy pages to scanners and researchers.

GBHackers·Sep 11, 12:24 UTC · 5d agoMalware in the wild2

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Cl0p Targets 40+ Organizations Through PTC Windchill Flaw

Cl0p claims over 40 organizations including Shell and Philips were breached by exploiting critical RCE CVE-2026-12569 in PTC Windchill and FlexPLM.

Cl0p claims more than 40 organizations were victimized via CVE-2026-12569 (CVSS 9.3), a critical deserialization-based remote code execution flaw in PTC Windchill PDMlink and FlexPLM, affecting releases prior to 11.0 M030; CISA added the flaw to its KEV catalog in June. ReliaQuest found the group deployed a custom web shell that maps vault data, decrypts all credentials in the Windchill keystore, and includes a Java class loader enabling arbitrary code execution, lateral movement, persistence, and large-scale data exfiltration without extra tooling. Named victims include Shell, Philips, Fiserv, Zebra Technologies, Ingersoll Rand, Toast, Mindray, and Apple lens supplier Largan Precision, with stolen data ranging from one gigabyte to multiple terabytes per target. The campaign mirrors Cl0p's earlier mass-exploitation extortion operations against MOVEit, Cleo, GoAnywhere, and Oracle E-Business Suite.

Security Affairs·Aug 21, 07:15 UTC · 26d agoRansomware in the wildCVE-2026-12569

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MicroHasTEE: Bare-Metal Haskell for Type-Level Peripheral Ownership on Armv8-M

MicroHasTEE expresses TrustZone secure and non-secure firmware as one typed Haskell program, catching peripheral-ownership inconsistencies at compile time.

MicroHasTEE is a multiparty Haskell framework that models both TrustZone firmware images as participants in a single typed program, using type-level capability ledgers to track peripheral acquisition, configuration, transfer, and finalization. MicroHs compiles the shared program twice to produce separate bare-metal Secure and Non-secure firmware images. The framework rejects inconsistent resource use, post-configuration attribution changes, wrong-domain callbacks, and calls to unregistered Secure services. A door-lock case study on an STM32U5 Nucleo board produced images of 232.7 KiB and 228.4 KiB of flash with roughly 220 KiB of SRAM per domain.

arXiv cs.CR·Sep 11, 08:34 UTC · 5d agoResearch1

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Wicked Problem, Parsimonious Solution: Securing Electric Vehicle Charging Station Software

Position paper proposes hierarchical software quality assurance to characterize and secure EV charging station software attack surfaces.

The authors argue that charging station supply-equipment software is a largely unprotected and poorly characterized attack surface in EV charging infrastructure. They advocate applying hierarchical software quality assurance (HSQA) to this specialized software, spanning from individual vulnerabilities such as CVEs to high-level characteristics like the CIA Triad. HSQA embeds quality and security considerations across the entire software development lifecycle to assess and improve charging station software security.

arXiv cs.CR·Sep 9, 17:37 UTC · 7d agoResearch

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Harnessing LLMs for Automating BOLA Detection

Unit 42's BOLABuster methodology uses LLMs to automate detection of broken object-level authorization vulnerabilities, uncovering flaws in Grafana, Harbor, and Easy!Appointments.

Palo Alto Unit 42 details BOLABuster, a methodology combining large language models with heuristics to automate detection of broken object-level authorization (BOLA) flaws, which traditional fuzzing and static analysis struggle to find. The approach uses LLM reasoning to understand application logic, map endpoint dependency relationships, and generate and interpret test cases. It found CVE-2024-1313 in Grafana, CVE-2024-22278 in Harbor, and 15 CVEs in Easy!Appointments. The team is continuing to hunt for BOLAs in open-source and internal projects.

Palo Alto Unit 42·Aug 17, 12:34 UTC · Aug 17, 2026ResearchCVE-2024-1313CVE-2024-22278CVE-2023-3285+14 CVEs

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Project CAV3RN continues: Google Apps Script as C2 relay and DNS-based C2 channel selection

Project CAV3RN continues targeting Israel, using Google Apps Script C2 relays and DNS-based channel routing in a .NET NativeAOT framework.

Kaspersky Securelist documents the continuation of Project CAV3RN operations against Israel. The modular .NET NativeAOT framework uses Google Apps Script as a C2 relay and DNS-based C2 channel selection, blending command traffic with legitimate Google services to evade detection.

Kaspersky Securelist·Aug 11, 10:00 UTC · Aug 11, 2026Threat actor in the wild

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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

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K-Bench: a clinically calibrated benchmark for evaluating large language models in high-risk mental health conversations

Clinician-calibrated K-Bench evaluates 125 LLM configurations on 200 high-risk mental health vignettes, exposing wide variation in suicide and violence risk handling.

K-Bench is a clinician-calibrated, protected benchmark evaluating 125 model configurations from 33 base models across 14 providers on 200 multi-turn vignettes covering suicide, self-harm, domestic violence, substance misuse and no-risk presentations. A frozen GPT-4o judge achieved 94.2% exact agreement with clinician consensus across 6,751 eligible comparisons from 151 clinician-rated transcripts. Leading models combined supportive conversation with combined-risk scores above 95, while risk exploration varied substantially among weaker configurations; therapeutic prompting helped weaker models and elevated reasoning produced no average improvement. A continuously updated public leaderboard is hosted at k-bench.ai with protected test materials.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 16:49 UTC · 2d agoAI safety & security

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TempCloze: Can Video-LLMs Identify the Missing Middle?

TempCloze benchmark tests Video-LLMs' temporal reasoning with 1,521 videos, finding temporal alignment is the primary failure mode across 31 models.

TempCloze is a video cloze benchmark in which models must identify the true missing middle clip given the beginning and ending clips, using 1,521 carefully filtered videos from seven sources, mostly long-take and egocentric footage. Distractors are constructed along three dimensions: Semantic, Alignment and Progression, with shared scenes and objects to reduce appearance cues. Evaluation of 10 proprietary and 21 open-source Video-LLMs found Alignment is the primary bottleneck, with models often recognizing plausible semantics and local event progression but struggling with temporal alignment.

Hugging Face daily papers·Aug 31, 20:00 UTC · 16d agoAI research

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Kaininja: Extending Native 3D Generators to the Part Level

KaiNinja extends TRELLIS.2 native 3D generation to part-level assets via a dual-volume O-Voxel representation, cutting whole-object Chamfer distance by 40%.

KaiNinja extends the TRELLIS.2 native 3D generator to produce part-level assets instead of one fused mesh, enabling downstream editing, rigging, and simulation. A dual-volume form of the O-Voxel representation solves the problem that a single volume cannot represent interfaces where two parts touch. The model needs no segmentation network, is partly trained on LLM-agent-authored part data, lowers whole-object Chamfer distance by 40%, and raises strict part F-score by 16% versus other part-generation pipelines.

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

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VectraRAT: An Undocumented Full-Stack MaaS Built From Scratch

SOCRadar's Threat Research Unit documents VectraRAT, a previously unreported full-stack Malware-as-a-Service platform built entirely from scratch.

SOCRadar's Threat Research Unit (STRU) documented VectraRAT, an undocumented Malware-as-a-Service platform. Unlike most MaaS offerings derived from leaked builders, VectraRAT was built entirely from scratch. The report details the platform's architecture and capabilities offered to affiliate customers.

SOCRadar·updated 14:36 UTC · 8h ago·first Sep 14, 12:50 UTC · 2d agoMalware 3 sources

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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

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Training a 3.8B LLM to 0.384 CORE for $998 – Hugo Vergnes

Independent developer Hugo Vergnes trained a 3.8B-parameter Llama-style model to 0.384 CORE on 65B tokens for $998 in 43 hours on rented B200s.

Hugo Vergnes trained little-lm, a 3.848B-parameter decoder-only LLM, on 65.3B tokens in 43 hours for $998 using rented NVIDIA B200s, scoring 0.384 on the CORE benchmark and beating nanochat d32 (0.310) at similar cost. The Llama-style architecture uses RMSNorm, RoPE, GQA with 24 query and 8 KV heads, relu-squared MLPs, QK-norm, and ResFormer-style value embeddings that account for 19% of parameters. Key wins included the Muon optimizer for matrix parameters, a trapezoidal learning-rate schedule with linear cooldown, FP8 training plus vocabulary padding for roughly 33% throughput gains, and the ClimMix dataset over FineWeb-Edu. The project, inspired by Karpathy's nanochat, was built as a config-driven YAML framework for small LLM training.

Hacker News · security·Sep 10, 02:04 UTC · 6d agoAI researchHN 28↑ · 2 comments1

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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 · 15d agoModel release

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CUA-Universe: A Scalable and Dynamic Environment for Hybrid GUI+CLI Agents

Researchers introduce CUA-Universe, a pipeline turning real desktop software into hybrid GUI+CLI agent environments, lifting a 9B model's OSWorld success rate.

CUA-Universe is an environment-to-data pipeline that converts real desktop applications into hybrid GUI+CLI environments, scaling to 16 applications via App-Forge, Task-Weave, and Path-Steer. Training on its harvested trajectories shifted a 9B model toward effective GUI+CLI orchestration, yielding +39.3 points on CUA-Verse, +16.8 points success rate on OSWorld, and +7.84 points on OSWorld-MCP while cutting steps and tokens by up to 57% and 60%. The work addresses the scarcity of scalable hybrid environments for computer-use agents.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:26 UTC · 12d agoAI research1

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Malware Hijacks Android Car Head Units

Kaspersky reports first known malware infecting Android car head units via firmware updaters, repurposing vehicles as BADBOX proxy nodes for ad fraud.

Kaspersky documented the first known malware infection of Android-based car head units, delivered through the built-in TWCore firmware updater on DoFun devices via an MQTT-driven installation flag. A multi-stage chain installs the JarService dropper and a loader that pulls a clicker and reverse proxy module ('zhima') used for ad fraud and proxy botnet infrastructure. The malware supports nine commands, including clipboard changes, HTTP requests, and JavaScript loading, checking in with C2 every 90 minutes. Kaspersky attributes the campaign with high confidence to MoYu Group, linked to the BADBOX botnet.

Security Affairs·Aug 22, 09:04 UTC · 25d agoMalware in the wild

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Automobile Camouflage to Hide from Flock Cameras

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

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

Schneier on Security·Sep 7, 11:06 UTC · 9d agoResearch

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Alissonerdx/Minimax-H3-ComfyUI — new model trending #30 on Hugging Face

Alissonerdx released a rank-64 LoRA sharpening videos from MiniMax H3 in ComfyUI via guide-latent conditioning, trending #30 on Hugging Face.

Alissonerdx published Minimax-H3-ComfyUI, a repository containing a rank-64 LoRA (minimax_h3_lms_v1.0_r64) that sharpens source videos while keeping them photorealistic. It targets the MiniMax H3 ref2va base model, runs with Comfy-Org's ComfyUI-ready weights, and uses the native MiniMaxH3AddGuide node for aligned guide-latent conditioning. The release ships with a ComfyUI workflow, eight before/after example videos, and an Apache 2.0 license.

Hugging Face trending models·Sep 6, 11:22 UTC · 10d agoModel release2

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Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution

Researchers propose a hierarchical multi-agent system that cuts ransomware analysis cost by 44% while reaching 96.57% detection accuracy.

An arXiv paper (2609.04820) presents a Cost-Aware Hierarchical Multi-Agent System (HMAS) for adaptive ransomware detection and family attribution. Specialized agents run static analysis first, with dynamic and memory modalities invoked only when confidence is insufficient or specialists disagree; a Meta Orchestrator balances accuracy against computational cost via a cost model, and a locally deployed LLM verifies difficult cases. The system achieved 96.57% accuracy, 0.96 F1-score, and 0.99 ROC-AUC for binary detection, and 0.90 macro-F1 for multiclass family attribution. Average analysis cost dropped 43.97% versus exhaustive analysis, with 56.05% of cases resolved using static evidence alone.

arXiv cs.CR·Sep 4, 07:17 UTC · 12d agoResearch

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llm 0.34

Version 0.34 of Simon Willison's llm CLI adds response-duration metrics to log output, plus bug fixes and faster log querying.

The open-source llm command-line tool for interacting with large language models released version 0.34. The headline change adds response duration in milliseconds and human-readable form to llm logs --usage Markdown output, plus a new duration_ms field in llm logs --short. The release includes several contributed bug fixes and a significant performance improvement to llm logs, alongside the related llm-openrouter 0.7.1 release.

Simon Willison·Sep 2, 19:23 UTC · 14d agoAI tools & infra1

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Android car head units infected with proxy botnet malware through built-in software updaters

Kaspersky found malware delivered via car head unit updaters, attributed to the MoYu Group's BADBOX operation, recruiting devices into a proxy botnet.

Kaspersky discovered malware delivered through the built-in TWCore system updater in Android-based car head units running DoFun infotainment firmware, turning devices into ad-fraud tools and nodes in a proxy botnet. The three-stage infection chain (JarService dropper, loader, and final payload supporting nine commands) installs the zhima reverse-proxy module, which Nokia's Deepfield team independently found on TV set-top boxes. Kaspersky attributes the operation with high confidence to the MoYu Group, linked to the BADBOX supply-chain botnet first identified by HUMAN Security in 2023. DoFun closed the gap after Kaspersky's responsible disclosure.

Help Net Security·Aug 24, 00:00 UTC · 23d agoMalware in the wild

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OpenBMB Releases MiniCPM5-2B: A 2.52B Dense Model Averaging 53.9 Across 34 Benchmarks and Built to Run On Device

OpenBMB released MiniCPM5-2B, a 2.52B-parameter Apache 2.0 on-device model averaging 53.9 across 34 benchmarks, ahead of Qwen3.5-4B.

OpenBMB released MiniCPM5-2B, a 2,516,756,480-parameter dense LlamaForCausalLM model with grouped-query attention and a 131,072-token context, under Apache 2.0, runnable via vLLM, SGLang, llama.cpp, and Ollama. It averages 53.9 across 34 benchmarks versus 51.1 for Qwen3.5-4B, with strong tool-use (97.1 on tau2-Bench Telecom) and code results (69.1 LiveCodeBench v6, 46.4 SWE-bench Verified). Training combined 400B tokens of deep-thinking SFT, critic-based JustRL II RL teachers, and on-policy distillation merging 16 RL experts; datasets and intermediate checkpoints were published alongside the weights.

MarkTechPost·Sep 7, 19:18 UTC · 9d agoModel release

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Sparks Fly: NVIDIA Accelerates Local AI at IFA 2026

NVIDIA announces local AI push at IFA 2026 with faster llama.cpp/vLLM inference, PAIR routing tool, and October RTX Spark PCs.

At IFA 2026, NVIDIA announced simplified local AI support for agents in Hermes Agent, OpenClaw, and Perplexity Portable Computer, plus new llama.cpp and vLLM optimizations delivering up to 1.9x faster local inference. NVIDIA also unveiled PAIR, a Personal AI Router for distributing inference across a local network's PCs, and compact RTX Spark Windows PCs from Lenovo and Acer arriving in October. The post recaps recent local-capable model releases including Nemotron 3.5 Lightning (30B), Qwen3.8-Flash-Next and Qwen3.8-27B, DeepSeek v4 Flash (284B MoE, 13B active), Meta Muse Glimmer (30B), Z.ai GLM-5.3-Flash, LTX 2.5, and MiniMax-H3 with the FastH3 distilled variant.

NVIDIA Blog·Sep 3, 16:00 UTC · 13d agoAI industry

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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 · 11d agoAI tools & infra1

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Large Language Models Develop Belief State Geometry In-Context

Probing six open-source LLMs on HMM-generated data shows belief states are linearly decodable (R² 0.83–0.99), suggesting in-context learning approximates Bayesian prediction.

Researchers prompted six open-source LLMs with data from 40 hidden Markov models selected for non-trivial belief structure and probed residual-stream activations for belief states (posteriors over hidden states). Belief states were linearly decodable with peak R² values of 0.83–0.99 across HMM/LLM combinations, spanning early to late layers. Patching and steering the probe-identified subspace preserved downstream prediction quality while control interventions degraded performance substantially, establishing functional relevance. The results provide representation-level evidence that in-context learning approximates optimal Bayesian prediction over a context-inferred generative model.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 16:17 UTC · 1d agoAI research1

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Finding Nemo(Claw): Networking Issue Allows for LLM Poisoning in OpenClaw

A networking flaw in Nvidia tooling lets attackers reach OpenClaw's local model server unauthenticated via the Ollama API, enabling persistent LLM poisoning.

Dark Reading reports that a networking issue in Nvidia's tooling can give attackers unauthenticated access to the local model server through the Ollama API. From there, attackers can poison the model used by the OpenClaw agent, creating persistent corruption of agent behavior. The finding highlights exposed local model servers as a security risk for self-hosted AI agent stacks.

Dark Reading·Aug 25, 19:50 UTC · 22d agoAI safety & security

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