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14 stories in the last 3d

DomainAll Cyber AIWindow24h 3d 7d 30d AllIn the wild Important only Show duplicates

CategoryAll Vulnerability 117 Advisory 65 AI safety & security 64 AI industry 61 AI research 57 Exploit / PoC 48 Industry 39 Research 32 Policy & legal 28 Tools 26 Malware 25 Data breach 24 Threat actor 20 AI tools & infra 14

SeverityAll critical 39 high 125 medium 121 low 41 info 323

Meta now lets AI agents handle the boring parts of WhatsApp Business setup

Meta launched a WhatsApp Business Tools MCP server that lets AI agents like Claude or Cursor set up and manage WhatsApp Business messaging accounts.

Meta announced a WhatsApp Business Tools MCP server, a Model Context Protocol server that connects AI coding agents such as Claude, Cursor, Codex, or ChatGPT directly to the WhatsApp Business Platform. The agents can handle account creation, phone number verification, Cloud API registration, Terms of Service checks, messaging template creation/editing, and webhook testing. Meta's companion Social Technologies MCP can also discover API endpoints, search documentation, and troubleshoot errors. The launch extends Meta's existing MCP servers for ad management and app configuration monitoring.

TechCrunch · AI20:12 UTC · 1h agoAI tools & infra

Your Agent Aced the Task. Will It Do It Again?

IBM Research Hugging Face post examines whether LLM agents that succeed at a task once will reliably succeed again.

Hugging Face published an IBM Research blog post titled 'Your Agent Aced the Task. Will It Do It Again?' with URL slug 'altk-evolve-consistency'. No article text was provided, but it appears to address agent consistency and reliability evaluation across repeated task runs. This is relevant to developers building or evaluating LLM agent systems.

Hugging Face Blog16:00 UTC · 5h agoAI tools & infra

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.

Hacker News · AI13:58 UTC · 7h agoAI tools & infra HN 41↑ · 8 comments

Show HN: Ordewell – turn one goal into an ordered plan of coding-agent tasks

Ordewell is an open-source tool that decomposes a single goal into an ordered plan of coding-agent tasks, posted on Hacker News.

Ordewell, shared as a Show HN project on GitHub, converts one high-level goal into an ordered plan of tasks for coding agents to execute. The post received 40 points and 29 comments on Hacker News. It focuses on task planning and orchestration for autonomous coding agents.

Hacker News · AI13:31 UTC · 7h agoAI tools & infra HN 40↑ · 29 comments

Akuity gives AI agents operational context to safely ship software

Akuity launches Agentic Control Plane and MCP Server to govern AI agent actions inside production software delivery pipelines.

Akuity introduced an Agentic Control Plane and MCP Server that lets AI agents such as Claude, Codex, and Cursor access deployment and cluster context under existing identity, permission, and audit controls. MLB reported the product identified over 100 degraded applications within hours. Akuity positions it against open-source MCP servers granting raw access with no identity inheritance or policy layer.

Help Net Security08:37 UTC · 12h agoAI tools & infra

Traefik Labs brings independent verification to AI agent governance

Traefik Labs announces Sovereign Trust Plane in Traefik Hub, adding verifiable delegation, policy enforcement, and tamper-evident audit records for AI agent traffic.

Traefik Labs announced the Sovereign Trust Plane for Traefik Hub, generally available by September 30, 2026, providing delegated access, policy enforcement, and tamper-evident records for AI agent, tool, and API traffic. It implements the IETF ID-JAG draft with Okta Cross App Access and Janssen, enforces decisions through OpenID AuthZEN with OpenFGA and Cerbos, and commits cryptographic log fingerprints to transparency checkpoints verified by independently administered witnesses. The gateway also extends enforcement to MCP tool calls and the MCP server's backend API connection.

Help Net Security08:20 UTC · 13h agoAI tools & infra1

Agent-net Open Sources Webagent: A Go Harness That Turns Any Website into a Guarded AI Agent

Agent-net open-sourced Webagent, a Go harness turning websites into AI agents with code-enforced guardrails wrapping every tool call.

Agent-net released Webagent under Apache 2.0, a Go framework where a business fills in a declarative JSON spec, picks one provider for each of nine pluggable slots (retrieval, memory, guardrail, channel, secrets, presenter, model, action, observability), and runs webagent serve. Every tool the agent holds is wrapped by action.Guard so the chosen guardrail executes before any action runs and the model cannot bypass it. Live capabilities include OpenRouter/gateway LLM brains, MCP tools over Streamable HTTP, and Slack, WhatsApp, and HTTP channels; browser actions, OAuth-gated MCP, OTel export, and AgentNet identity/billing are not yet built. The project is v0 with a deferred-hardening list and cites arXiv 2511.19477 on an 85% versus 50% task-success gap attributed to architecture over model capability.

MarkTechPost04:03 UTC · 17h agoAI tools & infra1

Show HN: Sunk Cost – How long until a local LLM rig pays for itself?

Show HN tool 'Sunk Cost' calculates when a local LLM rig breaks even versus falling API prices, factoring electricity cost and inference speed.

A Hacker News Show HN project called Sunk Cost models the payback period of buying local LLM hardware instead of paying API prices. Users can adjust assumptions like electricity cost ($/kWh) and API speed (tokens/second), and the model assumes API prices keep falling. Where local speed is unmeasured, it is estimated from memory bandwidth divided by bytes read per token, and labelled as an estimate.

Hacker News · security01:37 UTC · 19h agoAI tools & infra HN 30↑ · 31 comments

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 · securitySep 14, 16:07 UTC · 1d agoAI tools & infra HN 21↑ · 7 comments

NVIDIA Open-Sources OSMO: One YAML Orchestrates Physical AI Training, Simulation, and Robot Testing

NVIDIA open-sourced OSMO, a Kubernetes-native YAML orchestrator running physical-AI training, simulation, and robot testing across mixed GPU tiers.

OSMO (Apache-2.0, latest release 6.3.1) lets teams describe training, simulation, and hardware-in-the-loop pipelines in a single YAML and routes tasks across datacenter GPUs (GB200), workstation RTX hardware, and edge devices like Jetson AGX Thor. It ships Helm charts and containers on NGC, uses the KAI Scheduler with NVLink topology-aware placement, and includes RBAC, OAuth2, and TLS termination. NVIDIA says it is battle-tested on GR00T, Isaac Lab, Isaac Sim, and Isaac ROS, and integrates with Claude Code, OpenAI Codex, and Cursor agents.

MarkTechPostSep 14, 08:04 UTC · 1d agoAI tools & infra

OpenArch – PyTorch implementations of modern LLM architectures

OpenArch provides PyTorch reference implementations of modern LLM architectures for developers and researchers.

OpenArch is a GitHub project offering PyTorch implementations of modern large language model architectures. The repository attracted 43 points and 7 comments on Hacker News. It targets developers and researchers who want readable, runnable versions of current LLM architectures.

Hacker News · AISep 14, 07:55 UTC · 1d agoAI tools & infra HN 43↑ · 7 comments

CUDA for AMD on Windows

GitHub project 'CUDA for AMD on Windows' trends on Hacker News, aiming to run CUDA workloads on AMD GPUs under Windows.

A GitHub repository named CUDA-for-AMD-Windows drew 45 points and 5 comments on Hacker News. The project targets making NVIDIA's CUDA software stack work on AMD GPUs under Windows, which matters to developers running GPU compute or inference on non-NVIDIA hardware. No security impact is described.

Hacker News · AISep 13, 14:25 UTC · 2d agoAI tools & infra HN 45↑ · 5 comments1

AWS Introduces Pizza Bot: An Open Source Inbox for Background AI Agents

AWS open-sourced Pizza Bot, a self-hosted inbox app for background AI agents with approval gating and multi-provider model support.

AWS released Pizza Bot under Apache 2.0 after earlier versions served over 2,000 Amazon employees for meeting prep, email drafting, and research. The app provides macOS, Windows, and Linux desktop builds plus browser and terminal clients talking to a Hono API server, with LangGraph/DeepAgents checkpoints preserving thread state and approval pauses. It supports Amazon Bedrock, Anthropic, Google Gemini, OpenAI, OpenRouter, and Ollama, exposes external tools via MCP servers, and lets skill authors gate actions behind approve/edit/reject flows.

MarkTechPostSep 13, 08:10 UTC · 2d agoAI tools & infra

Implementation of Machine Learning Workflows with NVIDIA cuML, RAPIDS, GPU Benchmarking, Explainability, Clustering, and Model Inference

Hands-on tutorial implements NVIDIA cuML and RAPIDS to GPU-accelerate scikit-learn-style ML workflows with benchmarking, clustering, and inference.

The tutorial demonstrates NVIDIA cuML as a GPU-accelerated machine learning framework, using cuml.accel to speed up unmodified scikit-learn scripts with zero code changes and the native cuML API for CuPy/cuDF interoperability. It benchmarks CPU versus GPU implementations of PCA, K-Means, nearest-neighbor search, logistic regression, random forests, and DBSCAN on datasets up to 200,000 samples with 64 features. It also builds GPU pipelines with UMAP, t-SNE, and HDBSCAN, validates GPU-generated SHAP explanations, uses the FIL library for forest inference, and covers model serialization and GPU/CPU portability.

MarkTechPostSep 13, 01:42 UTC · 2d agoAI tools & infra