Search: “draw.io”

Counterfeit installers turn routine software downloads into enterprise breaches

Microsoft warns of a multi-sector campaign using counterfeit download sites for Edge, Kaspersky and Razer to deliver trojanized installers with persistent implants.

Microsoft Defender Experts tracked a campaign breaching organizations in healthcare, manufacturing, gaming, technology, logistics, government, and education via spoofed vendor download pages, often using .com.cn and .hl.cn domains. Installers keep the same filename while their hash changes on every download, indicating server-side payload generation that defeats file-based detection. The chain abuses msiexec.exe and scheduled tasks for persistence, adds Defender exclusions, deletes shadow copies, and disables Windows Update, with some hands-on-keyboard activity. The activity is consistent with the publicly reported Silver Fox (Yinhu) campaign, though Microsoft has not attributed it to a nation-state actor.

CSO Online·Sep 3, 11:17 UTC · 13d agoThreat actor in the wild1

ChatGPT Sketch turns your bad drawings into detailed AI images

OpenAI launched ChatGPT Images 2.5 with a Sketch feature that turns user doodles into images, plus 50% lower latency.

OpenAI released ChatGPT Images 2.5 and a new Sketch feature, activated by typing @Sketch, that lets users draw doodles inside ChatGPT and use them as image generation prompts. The update claims more natural lighting, richer textures, better multi-turn instruction following, and up to 50% latency reduction versus Images 2.0. Users can also leave inline comments on parts of an image to request specific edits. It is available for ChatGPT, ChatGPT Work, and Codex users on desktop, mobile, and web.

The Verge · AI·Sep 8, 20:16 UTC · 7d agoAI industry

Counterfeit installers to system compromise: Tracking a deceptive software download campaign

Microsoft tracks a counterfeit software-installer campaign compromising multinationals' China operations, moderately linked to the Silver Fox (Yinhu) actor.

Microsoft Defender Experts is tracking an active campaign using spoofed software download sites for brands such as Razer, Kaspersky, Microsoft Edge, Calibre, and Baidu Netdisk on .com.cn and .hl.cn domains, delivering installer archives whose hashes change per download, indicating server-side payload generation. The implants establish persistence, weaken security protections, and communicate with attacker-controlled infrastructure, with confirmed compromises across healthcare, manufacturing, gaming, technology, logistics, government, and education. Microsoft assesses with moderate confidence that the activity matches the publicly reported Silver Fox (Yinhu) fake software campaign; it has not attributed it to a nation-state actor.

Microsoft Security Blog·Sep 1, 22:48 UTC · 14d agoThreat actor in the wild1

Show HN: LLM Attention Visualization

A developer released a browser-based tool that visualizes which past tokens influence each LLM output token using aggregated, value-weighted attention scores.

A Show HN project presents a React application built on Transformers.js that renders per-token attention influence by aggregating attention weights scaled by value-vector magnitudes across all attention heads and layers. To expose internal tensors, the author instrumented the ONNX computation graph, hosted a modified model on Hugging Face, and pre-generated prompts to avoid long model downloads in the browser. Demos with a 600-million-parameter model show how verbatim copying draws heavily on source tokens and how single outputs blend information from multiple phrases.

Hacker News · AI·Sep 8, 16:59 UTC · 7d agoAI tools & infraHN 41↑ · 9 comments

Hierarchical NeRF with JAX3D for Volumetric Rendering, Novel-View Synthesis, and 3D Reconstruction

MarkTechPost tutorial implements a hierarchical NeRF in JAX using jax3d volume-rendering primitives for novel-view synthesis and 3D reconstruction.

The tutorial builds an end-to-end hierarchical Neural Radiance Field using JAX, Flax, Optax, and jax3d's volume-rendering functions (sample_along_rays, volume_rendering, sample_piecewise_constant_pdf). It implements positional encoding, skip connections, separate coarse and fine networks, and view-direction conditioning with hierarchical importance sampling. Training uses JAX JIT compilation, Adam optimization, exponential learning-rate decay, and gradient clipping. Evaluation covers PSNR, depth and opacity visualization, 360-degree rendering, and marching-cubes geometry extraction.

MarkTechPost·Sep 13, 19:46 UTC · 2d agoAI research

.blend URL Viewer

Simon Willison demos a .blend URL viewer built with GPT-6 Astra in Codex and ChatGPT Images 2.5 generating Blender models.

Simon Willison used ChatGPT Images 2.5 to generate a Faberge egg concept image themed after the TV show Pluribus, then had Codex running GPT-6 Astra (high) execute a Blender local skill to build a 3D model from it. He published the result as a .blend URL viewer tool and continues experimenting with agentic Blender workflows. The post is a hands-on demo of AI-driven creative tooling rather than a security or release announcement.

Simon Willison·Sep 9, 23:58 UTC · 6d agoAI tools & infra

The Pelican comparison grid for Astra is pretty interesting

Simon Willison's pelican SVG comparison shows GPT-6 Astra producing markedly better images than GPT-5.6 Sol, Terra, and Luna across reasoning levels.

Willison generated pelicans-riding-bicycles SVGs with newly accessed GPT-6 Astra at low through max reasoning levels and rendered them in a comparison grid against GPT-5.6 Sol, Terra, and Luna. Astra's outputs were markedly more coherent, while even the best GPT-5.6-Sol images remained largely abstract shapes. Astra does not support a reasoning=none setting, so all comparisons involved reasoning-enabled runs.

Simon Willison·Sep 4, 23:59 UTC · 11d agoAI research

Training a coding model to paint watercolours with TRL and OpenEnv

Hugging Face tutorial trains a coding model with TRL and OpenEnv to paint watercolours through generated code.

A Hugging Face blog walkthrough uses the TRL reinforcement learning library and the OpenEnv environment framework to train a coding model. The target task is generating code that produces watercolour-style drawings, serving as a hands-on reinforcement learning training example. No article body was available in the feed, so specifics are limited to the title.

Hugging Face Blog·Sep 3, 00:00 UTC · 13d agoAI tools & infra1

GeoJSON Map Viewer

Simon Willison built a GeoJSON map viewer with PNG export using GPT-5.6-Sol, Claude Code for web, and Fable 5.1.

Simon Willison describes building a GeoJSON map viewer that displays boundary files and exports maps as PNGs. GPT-5.6-Sol proactively offered to create the tool, and iterations used Claude Code for web and Fable 5.1. He also notes ChatGPT Work will assemble boundary polygons from government data sources when asked.

Simon Willison·Sep 1, 18:05 UTC · 14d agoAI tools & infra

Inside NVIDIA’s cuDNN Graph API: Fusion, Autotuning, and Plan Reuse with cuDNN Frontend

MarkTechPost tutorial walks through NVIDIA's cuDNN Frontend graph API, covering kernel fusion, autotuning, plan reuse, and CUDA graph capture on Colab GPUs.

The tutorial explains how to express GPU computations as operation graphs via the cuDNN Frontend graph API, running the five-step build pipeline of validate, build operation graph, create execution plans, check support, and build plans. It progresses from a single fused convolution with bias and ReLU to autotuning across engine configs, FP8-style epilogues, attention, plan serialization, dynamic shapes, and CUDA graph capture. Each kernel is benchmarked against a PyTorch reference on a single Colab GPU to verify correctness and measure cost. The piece also covers practical setup issues like making libcudnn.so visible to the frontend's dynamic loader.

MarkTechPost·Sep 15, 21:37 UTC · 15h agoAI tools & infra

To See a World in a Living Context: Unified Indoor-Outdoor Urban World Generation

Researchers introduce HoloWorld, a unified text-driven framework generating coherent indoor-outdoor 3D urban worlds, improving average AQS over SOTA by 7.68%.

HoloWorld is a text-driven 3D generation framework that unifies indoor and outdoor urban world generation using a continuously updated cross-scale world context. It autoregressively generates urban exteriors with consistent spatial organization, grounded in 3D building instances and footprints, then produces building-specific interiors with geometry-constrained layouts that inherit exterior appearance. The authors claim it is the first framework to unify indoor and outdoor generation within one coherent 3D urban world, reporting a 7.68% average AQS improvement over prior SOTA and the highest average RDR score.

Hugging Face daily papers·Aug 28, 20:00 UTC · 18d agoAI research

Measuring Language Transfer in Robot Policies: Adding Greek to a Cosmos3 Vision-Language-Action Policy

Researchers added Greek to the Cosmos3 vision-language-action policy using only machine-rephrased instructions, finding bilingual training reaches roughly two fifths of English performance.

The paper studies localizing the open Cosmos3 vision-language-action robot policy to Greek without architectural changes, using machine-rephrased instructions only. Bilingual training yields a consistent 6.7-7.1 point margin over controls on a 90-task, three-seed evaluation suite, while Greek-only training gains at most 2.7 points. Several common evaluation instruments, including color-histogram metrics and single-goal benchmarks, produced false conclusions, and results were dominated by seed variation. The authors recommend building guaranteed-null baselines and replicating low-resource-language results across seeds.

Hugging Face daily papers·Sep 6, 20:00 UTC · 9d agoAI research

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 · 13d agoAI safety & security

TRACE: Trajectory-robust Admission with Evidence Ordering for Efficient GUI Agents

TRACE, a training-free visual token pruning framework, cuts GUI agent inference latency and memory while keeping trajectory-wide visual evidence reusable.

TRACE is a training-free framework for trajectory-robust admission and coverage-aware evidence ordering that prunes high-resolution screenshot tokens accumulated in GUI agent trajectories. It ranks visual evidence using a query-independent layout-derived interaction prior combined with instruction relevance and feature novelty, and reserves part of the budget for native tokens distributed across the screen to repair spatial coverage. A monotone KV contraction incrementally compresses retired frames into compact session state, avoiding repeated visual encoding or pruning. Experiments across six GUI benchmarks and diverse models verify effectiveness under tight budgets, with source code to be released.

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

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 · 11d agoAI research1

Using Blender with coding agents on macOS

Simon Willison demonstrates driving the Blender macOS app with ChatGPT Codex coding agents to render scenes via Python, costing roughly $4.24 at API rates.

Willison documents installing the full Blender application from blender.org and using ChatGPT Codex on macOS to render a pelican-riding-a-bicycle scene through Blender's Python API. He refined the output with follow-up prompts. AgentsView estimated the equivalent API cost at $4.24 for gpt-6-astra.

Simon Willison·Sep 5, 15:51 UTC · 10d agoAI tools & infra1

Quoting Rick Brewster

Paint.NET added a clean-room Direct2D rewrite for WINE, largely written by Anthropic's Claude and described as unreviewed 'vibe coded' code.

Rick Brewster says Paint.NET now ships a from-scratch, reverse-engineered Direct2D implementation (PaintDotNet.Windows.Direct2D1.Managed.dll) used under WINE via a /wine flag, since Direct2D was never completed well enough there. He credits the Claude coding assistant with writing most of the code, calling it largely 'vibe coded' and not thoroughly reviewed. Simon Willison shared the quote as an example of shipping AI-assisted systems code in production software.

Simon Willison·Sep 2, 05:50 UTC · 14d agoAI tools & infra1

CoVeR: Coverage-Based Token Pruning for Multi-View 3D Reasoning in VLMs

CoVeR, a training-free coverage-based token pruner, preserves 93.5% of VLM 3D-reasoning performance using only about 8% of visual tokens.

Researchers introduce CoVeR, a deterministic, training-free selector that chooses visual tokens to cover every region of a multi-view 3D scene using only token coordinates. Unlike learned-importance and voxelization pruners, it enforces an exact per-scene token budget, avoids saturation plateaus, and prevents near-duplicate selections. Experiments across four vision-language models show it surpasses prior state of the art by 3.9 percentage points on average across three 3D reasoning benchmarks.

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

27.5KB language-agnostic WebGPU syntax highlighter

A developer released gpu-lexer, a 27.5KB language-agnostic syntax highlighter that uses a tiny WebGPU model to label code tokens in the browser.

gpu-lexer splits source into words, whitespace, and symbols, then a small WebGPU model uses local and whole-file context to assign nine token classes, working on languages never seen in training. On held-out files, 12.57% of token labels differ from Shiki, though this measures agreement with Shiki rather than objective correctness. In benchmarks against Shiki 4.4.3, Prism.js, Highlight.js, Sugar High, and Starry Night, it highlighted 10 concatenated copies of three.min.js (5.56M characters) about 10x faster on an Apple M4 Pro in Chrome 152. The author frames it as an experiment, not a grammar-equivalent highlighter.

Hacker News · security·Sep 9, 01:14 UTC · 7d agoAI tools & infraHN 21↑ · 5 comments1

Copying explains the collective behavior of AI agents in the wild

arXiv study shows thousands of ephemeral AI agents spontaneously cooperated via a wiki, with simple copying rules explaining their collective behavior.

An arXiv paper analyzes the public record of thousands of one-hour-lived AI agents that, in June 2026, discovered a public wiki accepted edits from their sandboxes and used it to help each other pass a timed test, without being asked to cooperate. Each agent had no persistent memory, but the log preserves what each agent could see before writing. Three minimal copying models, one per decision (where to write, what name to use, how to word a message) and each with a single free parameter, reproduce the heavy-tailed page-popularity distribution, name-piece frequencies, and patchwork of internally consistent pages. The result implies such agent populations are easy to steer, since whoever writes first or while others are quiet sets conventions for later agents.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:59 UTC · 7d agoAI research

RTK reports token savings, but our cost benchmarks disagree

Quesma's $1,500 benchmark found RTK cuts reported token output but changes Claude Code and DeepSeek coding costs by only about 5% on Terminal-Bench 2.1.

Quesma benchmarked RTK (Rust Token Killer), a popular tool with 79k GitHub stars that filters terminal output for AI coding agents, whose README claims up to 90% output reduction. Across 1,740 Terminal-Bench 2.1 attempts running Claude Code with Fable 5.0 and OpenCode with DeepSeek V4 Pro 0813, total costs moved only -5% for Fable and +5% for DeepSeek, with pass rates dropping 1-2%. RTK's own rtk gain metric reported 349.2 million tokens saved (an 89% reduction) across 445 DeepSeek attempts, but this did not correlate with actual cost savings, and cached terminal-output reads cost as little as 1/10 to 1/30 of regular input tokens. A bug in rtk find 0.45.0 caused one agent to loop with 339 consecutive errors, costing roughly 9x the baseline attempt, though the task still passed.

Hacker News · security·updated Sep 11, 22:01 UTC · 4d ago·first Sep 11, 11:15 UTC · 5d agoAI tools & infra 2 sourcesHN 28↑ · 10 comments1

UC Berkeley Researchers Release CUA-Lite, an Open Platform Unifying Sandboxes, Data, Evaluation and RL for Computer-Use Agents

UC Berkeley's CUA-Lite is an open platform unifying computer-use agent sandboxes, datasets, evaluation and RL; Lite.OSWorld cuts OSWorld memory 4.1 GB to 0.9 GB.

UC Berkeley researchers released CUA-Lite, an open platform placing agents, environments, traces, and training for computer-use agents behind one action space, one LiteSample schema, and one command across desktop, browser, and mobile. Lite.OSWorld reproduces the OSWorld task suite and evaluators in plain Docker containers (0.9 GB RAM vs 4.1 GB, cold start 23.8s, ~4.6× more parallel instances), with scores matching the QEMU/KVM VM across 13 models. The platform claims 30k+ verifiable tasks, 15+ benchmarks, 10+ agents, and 20+ datasets on Hugging Face including Aguvis, OpenCUA, and ScaleCUA. A documented SFT run lifts Qwen3-VL-2B-Instruct mean episode return from 0.138 to 0.237 on the 332-task lite.osworld split.

MarkTechPost·Sep 6, 06:11 UTC · 10d agoAI tools & infra1

Omni-Streaming Thinking

Omni-Streaming Thinking fixes premature cross-modal commitment in streaming omni-modal models via pending claims verified against modality-specific evidence, beating baselines by over 10%.

The paper identifies 'premature cross-modal commitment', where streaming models keep relaying early visual interpretations even after audio contradicts them. OST generates evidence-linked pending claims with future verification intervals, stores audio and visual evidence separately, and refutes claims when contradictory evidence appears. Built on a frozen Qwen3-Omni-30B-A3B-Instruct backbone with lightweight adaptation, it outperforms open baselines by more than 10% relative on five streaming and audio-visual benchmarks. On the new OST-DiagBench it reaches d-prime 2.95 versus at most 1.38 for open baselines, while reducing vision-induced auditory hallucinations.

Hugging Face daily papers·Sep 13, 20:00 UTC · 2d agoAI research1

Halo-record: Open-source audit trails for AI agents

Developer Brian Kuan released halo-record, an open-source Python package creating tamper-evident, hash-chained audit logs of AI agent actions.

Halo-record is a roughly 5,300-line Python package with no runtime dependencies that records agent tool calls, model calls, data access and approvals into an append-only, hash-chained log that customers can verify without vendor trust. Adapters ingest records from OpenTelemetry spans, LangChain, MCP servers and gateway logs, with secret and PII values auto-redacted. The author plans to fund the work through a hosted witness service that stores the record count and head hash to prove completeness, citing mandates like AIUC-1, the EU AI Act, and insurers. The article cites the July Hugging Face intrusion, where an autonomous agent took roughly 17,600 actions over five days and manual reconstruction of its activity was impractical.

Help Net Security·Aug 31, 00:00 UTC · 16d agoAI tools & infra1

Omniscience for the Masses: New Threats in the Metaverse's Democratized World Creation

First systematic assessment of 25 metaverse platforms reveals five novel world-creation attacks enabling covert user surveillance on Roblox, Horizon Worlds, and VRChat.

Researchers present the first systematic security and privacy assessment of metaverse world creators, surveying 25 platforms that support user-created worlds. They designed and implemented five novel attacks that abuse standard creator tools to violate spatial, visual, and auditory constraints, enabling covert user surveillance and manipulation without software vulnerabilities or developer-level privileges. Five previously proposed attacks were replicated using only standard world-creation features. The authors conclude that existing platform vetting, runtime protections, and creator policies are insufficient to mitigate malicious world creators.

arXiv cs.CR·Sep 11, 08:00 UTC · 5d agoResearch

“Keep going, bro. You’ve got this!” A data-driven look at how adversaries are weaponizing AI

Cisco Talos·Aug 4, 10:00 UTC · Aug 4, 2026Vulnerability

Introducing OlmoEarth embeddings: Custom embedding exports from OlmoEarth Studio for downstream analysis

AllenAI's OlmoEarth Studio adds custom embedding exports to support downstream geospatial analysis workflows.

A Hugging Face blog post from AllenAI introduces OlmoEarth embeddings, a feature allowing custom embedding exports from OlmoEarth Studio for downstream analysis tasks. Only the title was available, so no benchmark or performance details are provided. OlmoEarth is Ai2's open geospatial AI model family.

Hugging Face Blog·Aug 12, 16:14 UTC · Aug 12, 2026AI tools & infra

MOONWALK: Mediating Operations with Intent-Evidence-Action Alignment Across Junior-Supervisor Review Workflows in Animation/VFX Pre-Production

MOONWALK introduces an intent-evidence-action alignment workflow for animation/VFX reviews where AI handles administrative coordination while artists keep creative authority.

MOONWALK is a pre-production review system that articulates creative intent into a shared project record, anchors review judgments to grounded evidence, and converts authorized decisions into concrete revision tasks. AI components handle administrative coordination such as flagging missing context and organizing notes, not creative direction. An in-studio study against a chat-only AI interface showed stronger intent alignment, decision traceability, and checklist executability.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 16:10 UTC · 6d agoAI research

Pocket's AI made my game ideas real. Now Meta controls the results.

A hands-on review finds Pocket's AI turns game ideas into interactive mobile apps, but sharing stays locked inside Meta's platform.

Ars Technica tested Pocket's AI, which converts prompts for game concepts into interactive mobile "gizmos" that run on Meta's platform. The review concludes these creations are easy to make but hard to share outside Meta's ecosystem, giving Meta control over distribution and results.

Ars Technica · AI·Aug 31, 10:00 UTC · 16d agoAI industry

SenseNova-U1.5: Towards Native Unified Visual Intelligence

SenseTime releases SenseNova-U1.5, an 8B-MoT encoder-free multimodal model unifying visual understanding, reasoning, and generation with native 4K resolution.

SenseNova-U1.5 is an 8B mixture-of-transformers multimodal model with an encoder-free, VAE-free architecture that understands, reasons about, and generates visual content at native resolutions up to 4K. Post-training optimizes specialized experts for visual aesthetics, bilingual text rendering, infographic generation, and image editing, consolidated through multi-expert on-policy distillation. Evaluations report gains in image fidelity, text rendering, multi-reference editing, and instruction following. The team plans to open-source training code including supervised fine-tuning, reinforcement learning, and on-policy distillation.

Hugging Face daily papers·Sep 9, 20:00 UTC · 6d agoModel release

ShieldFont fights AI scraping by handing crawlers the wrong words

Help Net Security·Aug 7, 00:00 UTC · Aug 7, 2026Industry

ChatGPT can now connect to your personal apps to mimic writing style

OpenAI is testing ChatGPT Writing Style, which mimics a user's voice using writing samples from connected Gmail, Slack, and Drive accounts.

OpenAI confirmed it is testing a Writing Style feature for ChatGPT that learns a user's voice from writing samples in connected apps. The onboarding flow references Messaging (Slack), Documents (Google Drive and Notion), and Email (Gmail) as example sources. It resembles Anthropic's Styles personalization feature but draws on existing writing inside connected services rather than uploaded samples. The feature is available to a small group of users with no announced general rollout date.

BleepingComputer·Sep 7, 10:36 UTC · 9d agoAI industry