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Google Open-Sources Mantis: A Modular Skills Toolkit That Lets Coding Agents Find, Reproduce and Patch Vulnerabilities

Google open-sourced Mantis, an Apache-2.0 modular skills toolkit that lets AI coding agents find, reproduce, and patch vulnerabilities with sandboxed verification.

Google released Mantis on GitHub under Apache 2.0 as a stack-agnostic set of slash-command skills that chain through the full vulnerability lifecycle: mining version history, building threat models, filtering findings, reproducing bugs in gVisor or network-disabled VMs, assembling exploit chains, patching, and scoring residual risk from 1 to 10. It runs with Gemini CLI, Antigravity CLI, the Google ADK, or comparable agent frameworks, and a supervisor skill (/mantis-meta-agent) can drive the whole loop. Google says the design targets the sub-7 percent true-positive rate of naive AI code scanning, and that its hierarchical summary tree cuts token overhead by over 85 percent. The toolkit is deployable for local and internal evaluation but not yet recommended for production.

MarkTechPost · 6d agoAI tools & infra

Introducing the Admin plugin for ChatGPT Work and Codex

OpenAI launched an Admin plugin for ChatGPT Work and Codex to manage workspace usage, members, permissions, and limits.

OpenAI introduced an Admin plugin for ChatGPT Work and Codex aimed at enterprise workspace administration. The plugin lets administrators analyze workspace usage, manage members and permissions, adjust usage limits, and act on admin requests. The announcement is a routine product feature launch with no security incident or vulnerability details.

OpenAI News · 22d agoAI industry

19 Chrome and Edge Extensions Found With Wallet-Stealing and Crypto

Socket found 19 malicious Chrome and Edge extensions, active since February 2024, stealing wallet seed phrases and credentials and draining crypto from about 80,000 users.

Socket researcher Karlo Zanki documented a cluster of 18 Chrome and one Edge extensions with wallet secret stealing and cryptocurrency draining capabilities, tracked as campaign Superior and possibly active since February 2024. The actor created 14 extensions and bought five legitimate ones, later pushing malicious updates; the largest, Enable Right Click & Copy, has roughly 80,000 installs across both browsers. The extensions maintain WebSocket C2 connections with endpoint rotation, strip CSP headers, and load 16 modules including multi-chain wallet drainers, hardware-wallet seed-phrase harvesters, credential grabbers, and ClickFix-style lures.

The Hacker News · 19d agoMalware in the wild

Nimbus Manticore Expands Toolset With TWOSTROKE

Group-IB found new infrastructure and TWOSTROKE-like malware used by IRGC-linked Nimbus Manticore, indicating expanded Middle East and Europe targeting.

Group-IB reported new Tortoiseshell infrastructure spanning Europe and the Middle East and two previously undocumented tools from IRGC-linked Nimbus Manticore (UNC1549): a reverse SSH tunneling utility connecting to 172.86.98.113 on port 443, and a C++ backdoor masquerading as wtsapi32.dll with three hard-coded C2 servers. The backdoor overlaps with TWOSTROKE and supports file transfer, execution, host information gathering, and persistence. Findings build on Kaspersky's report of the NightLedger backdoor and WebSocket tunnelers BridgeHead and ArcBridge, and suggest expanded targeting beyond the Middle East into Europe.

The Hacker News · 21d agoThreat actor in the wild

Context Engineering Inside the Harness: 4 Mechanisms That Beat Context Overflow and Goal Loss on Long-Horizon Tasks

Survey of four harness mechanisms—context budgeting, compaction, todo-state, and memory—that keep long-horizon LLM agents on task across 200+ tool calls.

The article details how agent harnesses, not larger context windows, solve context overflow and goal loss on long-horizon tasks, citing Chroma's Context Rot report showing 18 LLMs (GPT-4.1, Claude 4, Gemini 2.5, Qwen3) degrade on long inputs. Concrete implementations include LangChain Deep Agents offloading tool responses over 20,000 tokens to the filesystem and truncating old tool calls at 85% window usage, and Claude Code capping auto memory at 25KB while re-reading the 5 most recently modified files after compaction. OpenAI's Responses API now offers server-side compaction via context_management with a standalone /responses/compact endpoint, which Codex uses for long-running coding tasks. Manus reports a roughly 100:1 input-to-output token ratio per ~50-tool-call task, motivating todo.md state recitation to prevent goal drift.

MarkTechPost · 3d agoAI research1

Bring your spreadsheet data to life with Sheets canvas

Google added Sheets canvas to Workspace, letting users generate interactive dashboards, trackers, and charts from spreadsheet data via prompts.

Google introduced Sheets canvas, a Workspace feature that turns spreadsheet data into interactive dashboards, custom study trackers, and seating charts from a simple prompt. The announcement is a productivity feature launch with no described security impact or risk. No metrics, model details, or pricing are provided in the notice.

Google · AI · Aug 13, 2026AI industry

Dr. Claw: An AI Scientist Workspace for Vibe Research

Researchers release Dr. Claw, an open-source auditable workspace that wraps coding agents like Claude Code for end-to-end AI-assisted research workflows.

Paper 2609.00365 presents Dr. Claw, an open-source workspace that wraps existing coding-agent executors such as Claude Code and Gemini CLI in a controllable, human-in-the-loop research workflow. It uses persistent state objects, a reusable skill library, and multi-executor coordination to make research decisions auditable and recoverable, rather than adding another autonomous agent. Holding the executor fixed, Dr. Claw scores higher on research completeness than a bare command-line agent while preserving an auditable process trail. The code is released under AGPL-3.0 on GitHub (OpenLAIR/dr-claw).

Hugging Face daily papers · 16d agoAI research1

JarvisGUI: Towards Cross-Device GUI Agents with Dynamic Task Composition

JarvisGUI benchmark tests GUI agents on cross-device workflows across Android, Windows, and Ubuntu, revealing major gaps in state transfer and long-horizon reasoning.

JarvisGUI is a dynamic benchmark that formulates GUI tasks as input-output transformations under a lightweight type system, automatically composing multi-step cross-device workflows across Android, Windows, and Ubuntu virtual environments. Evaluation shows state-of-the-art open-source GUI agents struggle with state-transfer awareness, cross-platform contextual reasoning, and long-horizon dependency management, exposing a capability gap invisible to existing single-device benchmarks.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

ToolLoop: Closed-Loop Tool-Use Data Synthesis via Decomposed Generation and Dynamic Self-Feedback

ToolLoop introduces a closed-loop synthetic data framework whose 11K examples lift a 4B model to 86.40% on BFCL tool-use evaluation.

ToolLoop decomposes tool-use data synthesis into function-name sampling, backward derivation of user queries, and forward derivation of tool calls, with dynamic self-feedback at each stage. This shifts the paradigm from generate-then-filter to generate-verify-refine, reducing inefficient and imbalanced synthetic data. A 4B model trained on 11K synthetic examples reaches 86.40% accuracy on BFCL non-reasoning mode (86.07% in an Isolate variant excluding BFCL-overlapping functions) and 72.1% on ACEBench using only 18.3% of baseline training data.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research1

Slack can now vibe-code interactive charts and reports inside chats

Slack launched Slackforce Surfaces, letting Slackbot build interactive dashboards, reports, and microsites directly inside chat channels.

Slackforce Surfaces uses AI to gather context from conversations and connected apps such as Google Drive and Salesforce to generate shareable interactive reports, polls, dashboards, and presentations. Surfaces can be pinned to channels where colleagues can view, interact, and comment. The feature is available to all customers, including free users, with Slackbot enabled, and live data support starts in October.

The Verge · AI · 5d agoAI industry1

5 new ways to level up your learning with Search

Google promotes five Search study tools for students preparing for classes and standardized tests.

Google published a back-to-school post highlighting five ways to use Search tools when studying for classes and standardized tests. The post is promotional product guidance rather than a launch, research result, or security announcement.

Google · AI · 27d agoAI industry

Webinar: The forgotten Google Workspace access that can lead to a breach

BleepingComputer and Material Security will host a September 23, 2026 webinar on breaches caused by forgotten third-party Google Workspace integrations.

BleepingComputer announced a live webinar on September 23, 2026, titled 'Breach autopsy: How fast-growing companies are breached through Google Workspace' in partnership with Material Security. Speakers include Rajan Kapoor, VP of Security at Material Security, and Rick Fitzgerald, President of Fireside Consulting LLC. The session will examine real documented Google Workspace breaches involving overly permissive third-party integrations, social engineering entry paths, first-hours breach response decisions, and high-value security controls for lean security teams.

BleepingComputer · 8d agoIndustry

Technical Manual for a Toolkit for Measuring Contextual Individuation in Transformer Language Models

An open methodology toolkit measures whether transformer language models contextualize fixed word forms across domains using bridge forms and layer-wise silhouette analysis.

The manual documents an open toolkit built around 'bridge forms' - identical written words recurring across two or more subject domains with a different sense in each - to test whether transformer language models individuate word occurrences by context beyond the embedding layer. It covers declarative specification of bridge forms, Wikipedia corpus acquisition, occurrence localization, layer-wise representation extraction, domain-pairwise silhouette measurement, and visualization, justifying each choice against failure modes such as sense contamination and subword-tokenization misalignment. It is a methodological and implementation reference and reports no empirical results.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research

Webinar: How malicious OAuth apps can lead to Google Workspace breaches

BleepingComputer webinar will dissect two Google Workspace breaches caused by malicious OAuth apps and social engineering, hosted September 23 with Material Security.

On September 23, 2026, BleepingComputer will host a webinar with Material Security examining two real attacks that used malicious OAuth applications and social engineering to breach Google Workspace environments. Rather than stealing credentials, attackers persuaded users to authorize malicious apps, gaining access to data through the granted permissions. The session covers first-hour response decisions and which security controls provide the greatest value for fast-growing organizations.

BleepingComputer · 2d agoPhishing & fraud

Zoom Annotation Flaws Could Let a Meeting Participant Hijack Another Attendee's Client

A Security researchers disclosed three Zoom annotation flaws enabling zero-click client hijacking; Zoom shipped fixes in June and July with no exploitation reported.

Researchers at A Security found three flaws in Zoom's annotation feature: CVE-2026-53413 (CVSS 8.3, buffer over-write), CVE-2026-53414 (CVSS 6.5, buffer over-read), and CVE-2026-53415 (CVSS 8.3, use-after-free). A crafted drawing object sent over the wrong message channel can overwrite adjacent memory and hijack another attendee's client with no user interaction. Fixes shipped in Zoom Workplace 7.1.5/7.0.6, VDI Client 7.0.11/6.6.16, and Zoom Rooms/Meeting SDK 7.1.0+ during June and July. No exploitation has been reported and the flaws are absent from CISA's Known Exploited Vulnerabilities catalog.

Google Research Releases ToolGrad: Answer-First Framework Hits 99.8% Pass Rate for Tool-Use Data Generation

Google Research and partners introduce ToolGrad, a verified tool-chain-first data generation framework reaching 99.8% pass rate and boosting Gemma-3-12B to 83.1 on BFCL.

Researchers from Google, the University of Tokyo, RIKEN AIP, and Tohoku University released ToolGrad, which inverts query-first tool-use data generation by executing and verifying API chains before annotating them with user queries. On the ToolBench database of 16,000+ APIs, ToolGrad raised generation pass rate from 63.8% to 99.8% while increasing tool uses per sample from 2.1 to 3.4 and cutting tool-use steps from 34.3 to 20.0. Fine-tuning Gemma-3 at 1B, 4B, and 12B parameters on the 500-sample ToolGrad-500 dataset lifted ToolGrad-12B to 83.1 on the Berkeley Function Calling Leaderboard, near Gemini 2.5 Pro at 83.2 and ahead of GPT-5 at 74.4. Code is Apache-2.0, with the dataset, PyPI package, and models available on Hugging Face.

MarkTechPost · 5d agoAI research1

Codex bundles LibreOffice

OpenAI's Codex desktop app bundles 1.7GB of runtimes including full Python, Node.js, Poppler, git, and LibreOffice binaries.

Blogger Simon Willison found that the OpenAI Codex desktop app (since rebranded to ChatGPT) keeps about 1.7GB in a ~/.cache/codex-runtimes/codex-primary-runtime folder, including full Python and Node.js installations plus native binaries for Poppler, git, and the LibreOffice office suite. Bundled skills in the plugins directory instruct Codex on how to find and use these binaries. The observation highlights the heavyweight local runtime stack shipped with agentic coding tools.

Simon Willison · 14d agoAI tools & infra1

What Breaks Under Pruning in Smart Homes, and When? Evaluating LLM Degradation Across Architectures and Task Complexity

Pruning study across four LLM architectures finds dense models degrade sharply on smart-home tool calling while MoE models tolerate far more.

Researchers systematically study pruning-induced degradation in smart-home tool calling across four LLMs spanning dense Transformer, dense hybrid, and mixture-of-experts architectures, combining depth, width, hybrid, and expert pruning methods, and evaluate over 19,500 instances from three datasets after post-pruning supervised fine-tuning. Dense models show narrow safe pruning regions followed by sharp degradation, while MoE models tolerate substantially more pruning. Pruning degrades grounded specificity (operation, device, argument, value) before schema-level intent, and aggressive dense pruning can induce systematic over-refusal.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

DataGrout helps enterprises control AI usage, governance and LLM costs

SelectHub launched DataGrout, an LLM cost and governance platform combining dynamic context pruning, symbolic inference and MCP gating, claiming about 60% token reduction.

SelectHub launched DataGrout, an LLM inference optimization and AI governance platform combining dynamic context pruning, a symbolic inference layer, and an MCP gateway with per-call token and cost monitoring. Early tests claim roughly 60% token reduction on data-intensive ERP and CRM integration tasks without accuracy loss. The platform connects via its Conduit SDK, MCP or JSON-RPC, offers its own MCP servers for SaaS apps such as Salesforce, SAP and ServiceNow, and supports bring-your-own-key LLM access or gateways like Amazon Bedrock and Kong.

Help Net Security · Aug 13, 2026AI tools & infra1

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 · 12d agoAI research1

Show HN: Panel – A research workspace where the agent can build its own panes

Panel is an open-source research workspace where AI agents dynamically build their own panes, posted on Hacker News.

Panel, shared as a Show HN project on GitHub, is a research workspace in which the agent can construct its own panes rather than using a fixed interface. The post received 41 points and 8 comments on Hacker News. It targets agentic research workflows with a dynamically generated UI.

Try Google Pics: Easy image creation and editing in Google Workspace

Google rolls out Pics, a Nano Banana-based image creation and editing tool, to Workspace subscribers with integrations in Docs, Slides, and Drive.

Google Pics, built on the Nano Banana image generation model, is rolling out to Google AI Pro and Ultra subscribers and most Workspace business customers. Features include object segmentation, in-image text editing and translation, collaboration, and multiple generations per prompt. Integrations launched in Docs and Slides, with Drive support planned in the coming weeks.

Google · AI · 15d agoAI industry

Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization

ModerationBench shows foundation models can nearly triple Bluesky's moderation F1 (0.60 vs 0.22), with instruction- and example-driven guidance performing comparably.

Researchers built ModerationBench, a new benchmark of 4,000 manually annotated in-the-wild posts from Bluesky, to test whether foundation models can reliably operationalize content moderation policies. They systematically compare instruction-driven guidance (reasoning from policy precepts) with example-driven guidance (generalizing from precedents) for Vision-Language Models. Both paradigms achieve comparable peak effectiveness, and foundation models nearly triple the F1 of Bluesky's deployed moderation system on Random Posts (0.60 vs 0.22).

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

Who Should Grade My Work? Student Perspectives on Transparent AI-Assisted Writing Assessment in Higher Education

A Saudi university study finds students value ChatGPT writing feedback but treat human instructors as the final grading authority.

Thirteen male undergraduate computing students at a Saudi public university completed handwritten writing tasks that were scored by ChatGPT using a rubric-based prompt, then reflected after being told the score and feedback were AI-generated. Inductive thematic analysis identified four themes: perceived feedback usefulness, awareness of AI's contextual and pedagogical limitations, conditional trust, and reflection on the instructor's institutional role. Participants accepted GenAI feedback for surface-level revision but consistently positioned human instructors as the authority over grading decisions, distinguishing feedback utility from evaluative authority.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research

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.

Sure, Meta’s AI Muse works, but it sure creeps me out

Hands-on review finds Meta's Muse AI agent completes shopping and email tasks but surfaces personal Instagram API data beyond user-visible ad-topic settings.

Meta launched Muse, its first agentic AI productivity assistant, which performs tasks like shopping, email management, trip planning, media generation, and creating webpages or documents via a cloud-based virtual computer. The Verge's hands-on found it successfully deleted thousands of promotional emails and completed an Amazon purchase, but it also revealed detailed personal interests inferred from Instagram and Facebook account API data that is not visible in the apps' ad-topic settings. Meta says Muse only exchanges data needed for third-party integrations and does not share information with advertisers; the reviewer frames privacy unease as the main adoption hurdle.

The Verge · AIupdated · 5h agofirst · 6d agoAI industry 11 sources

Ask HN: How do you manage skills files?

A Hacker News thread debates whether agent skill files are worth managing, citing 2–4x output-token reductions on flagship models in one company's testing.

Commenters argue skills are stored prompts that help less-technical users compensate for weak prompting, while one participant reports company testing found skills reduce flagship-model output tokens by roughly 2–4x, a gap growing with newer models. Others note skills can bundle reusable scripts and inline commands for deterministic context building, and that harnesses now execute backticked commands before the agent sees the skill. Some argue improving model capability makes downloadable skills redundant.

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.

Meta bets on AI agent Muse to catch up in AI race

Meta launched Muse, a free personal AI agent in the US that autonomously shops, emails, and plans trips, powered by its in-house Muse Spark model.

Meta unveiled Muse, a consumer personal AI agent that handles tasks like online shopping, emailing, and trip planning, continues working in the background, and requests approval for purchases. It launches in the US on iOS, Android, and muse.ai, is free for most users with unspecified paid tiers, and runs on Meta's in-house Muse Spark model. Muse executes on a cloud virtual machine with a Sentinel agent policing outbound actions, and Meta promises an encrypted confidential VM later this year plus 1Password, Shop Pay, and Stripe Link support. The launch is positioned as the centerpiece of Meta's effort to catch up with OpenAI, Anthropic, and Google.

The Verge · AI · 7d agoAI industry 3 sources1

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

Grouped Value Attention stores grouped values and reconstructs content keys via a learned linear map, cutting KV-cache size about 45-47% versus GQA.

GVA stores only grouped values and reconstructs content keys with a learned linear map absorbed into the query at decode time, while a small shared decoupled RoPE channel preserves positional information via a separately cached positional key. At 350M parameters trained on 30B FineWeb-Edu tokens, the 16-dimensional positional variant scores 44.18 average accuracy across five tasks versus 44.36 for GQA and 43.88 for MLA. Custom decoding kernels are in development with an open-source release planned.

Hugging Face daily papers · 8d agoAI research