Search: “IEEE”

7 items in the last 7d

MIT researchers published HardFlow, a method enforcing hard safety constraints on flow-matching generative models' final outputs without retraining.

MIT researchers led by Zeyang Li and Navid Azizan developed HardFlow, a trajectory-optimization method that enforces strict, non-negotiable constraints on flow-matching generative models by checking rule satisfaction only at the final generation step. Published in IEEE TPAMI, it outperformed six rival projection and guidance methods on four simulated benchmarks including D3IL robotic manipulation, Maze2D, physical process control, and image editing. All results are simulation-only, with no independent reproduction yet reported.

Hacker News · securitySep 14, 16:18 UTC · 2d agoAI research HN 24↑ · 25 comments

APT36 Uses USB-Spreading Malware to Reach Air-Gapped Government Networks

Zscaler attributes the RapidRust campaign by Pakistan-linked APT36 to USB-propagating Rust malware targeting air-gapped government networks in India and Afghanistan.

Zscaler identified in August 2026 a campaign tracked as RapidRust in which APT36 uses infected removable drives to reach air-gapped government environments in India and Afghanistan. RUSTYMOVE, a Rust USB-spreading utility, copies a fake-PDF shortcut and the RUSTYSHADE backdoor to removable media; RUSTYSHADE uses attacker-controlled private GitHub repositories for C2, running shell commands, capturing screenshots and webcam images, while PSNATCH and BASHNATCH steal files. Operators enumerated users, shares, and remote administrative shares to expand beyond initial victims, with payloads staged on lookalike domains mimicking Indian media outlets and Backblaze B2 storage.

Cyber Security News10:17 UTC · 2h agoThreat actor in the wild 3 sources

APT36 Targets Indian Government and Defense Organizations With New Rust Malware Arsenal

Pakistan-linked APT36 deployed a Rust malware suite, including RUSTYSHADE and USB-spreading RUSTYMOVE, against Indian and Afghan government and defense targets.

Zscaler ThreatLabz tracks the August 2026 activity as Operation RapidRust, introducing the Rust-based RUSTYSHADE backdoor, the RUSTYMOVE removable-media propagation utility, and PSNATCH and BASHNATCH file stealers for Windows and Linux. RUSTYSHADE uses private GitHub repositories as C2 with AES-256-GCM-encrypted traffic, supporting shell commands, screenshots, webcam capture, and encrypted exfiltration, while PSNATCH collects Office documents, archives, images, and databases from user folders and drives D: through H:. Typosquat domains spoofing ThePrint and India Today staged payloads with Backblaze storage, and persistence used scheduled tasks impersonating OneDrive and Microsoft Edge updates.

GBHackersupdated 10:17 UTC · 2h agofirst 09:42 UTC · 3h agoThreat actor in the wild 3 sources

Operation RapidRust: APT36 Deploys RUSTYSHADE, RUSTYMOVE, PSNATCH, and BASHNATCH

Zscaler details Operation RapidRust: APT36 deploys four new tools including RUSTYSHADE, a Rust backdoor using private GitHub repos for encrypted C2.

Zscaler ThreatLabz documents Operation RapidRust, a campaign by Pakistan-aligned APT36 deploying four new tools: RUSTYSHADE, a 64-bit Rust Windows backdoor that uses attacker-controlled private GitHub repositories with a hardcoded PAT and AES-256-GCM-encrypted messages for C2; RUSTYMOVE; PSNATCH, a PowerShell file stealer that scans Office documents, archives, media, and databases modified in the last 120 days and exfiltrates up to 5 GB per run to per-machine GitHub repositories; and BASHNATCH. The backdoor was dropped via PowerShell from attacker-controlled Backblaze B2 storage and supports screenshots, webcam capture, file listing, downloads, and shell command execution.

Zscaler ThreatLabzupdated 10:17 UTC · 2h agofirst Sep 16, 15:13 UTC · 21h agoThreat actor in the wild 3 sources

Exclusive: Paying for frontier AI models buys 4-month head start at 5x the cost

Mozilla report finds the capability gap between best open-weights (largely Chinese) and closed frontier AI models narrowed to 4.4 months at ~5x lower cost.

Mozilla's State of Open Source AI report (September 15) says the gap between closed frontier models and best open-weights models has closed to 4.4 months. Moonshot AI's Kimi K3 scores three points behind Anthropic's Fable 5 on the Artificial Analysis Intelligence Index at 30% of the cost, and Z.ai's GLM 5.2 scored within a point of Claude Opus 4.7 on Terminal-Bench 2.1. Eight of the top 10 OpenRouter models by August 2026 token volume provide open weights, though a Linux Foundation paper found open models earned only 4% of revenue. The report recommends open models as the default for routine workloads, reserving closed models for 8-12 hour expert tasks.

Ars Technica · AISep 15, 12:00 UTC · 2d agoAI industry1

I spent $4,000 on a robot dog from China

Hands-on review finds the $4,017 Unitree Go2 Pro robot dog affordable but impractical, as Unitree reaches a $34 billion valuation after its IPO.

Ars Technica reviewed the Unitree Go2 Pro quadruped, purchased for $4,017, finding it astonishingly cheap but of limited practical use; it collapsed from battery drain and heat (84°C internal temperature) on an uphill walk at 87°F. Unitree democratized quadruped research, sells humanoid robots from $13,500, and debuted on the Shanghai stock exchange on August 19 with shares rising over fivefold on day one, valuing the company at $34 billion. Its robots now face legal restrictions in the United States, and it competes with Boston Dynamics, whose Spot starts around $75,000.

Ars Technica · AISep 12, 11:00 UTC · 5d agoAI industry

Retrospectively Reverse-Engineering Apple's Neural Engine

A developer reverse-engineers Apple's M1 Neural Engine architecture, mapping compute cores, MAC datapaths, and schedulers to explain the NPU's decline as transformers displaced CNN workloads.

A developer who previously maintained a reverse-engineered Linux driver for Apple's Neural Engine (ANE) published a retrospective deep dive mapping the M1 ANE's full internal architecture: compute, datapath, scheduler, memory, and execution model. The M1 ANE has 16 compute cores with 128 FP16 (or 256 INT8) MAC lanes each, totaling 2048 parallel MAC lanes, using 32-bit Q16.16 fixed-point accumulation with FP16 readout and an accumulator that saturates at 2^15. The author argues the ANE's dataflow was architected around the predictable reuse patterns of 2017-era CNN workloads (dating to the A11 Bionic), which autoregressive transformer decode broke, limiting its usefulness for general ML. With Apple's M5 folding ANE cores into GPU cores to tout LLM performance, the post frames this as the beginning of the end for the standalone NPU.

Hacker News · AISep 12, 07:54 UTC · 5d agoAI research HN 54↑ · 7 comments2