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Ukrainian lawyer's second career as a Conti coder earns him 4 years behind bars

Ukrainian lawyer turned Conti malware coder sentenced to four years in US prison, ordered to forfeit $25,042 in Bitcoin.

Oleksii Oleksiyovych Lytvynenko, 44, a trained lawyer who joined Conti under the handle "henry", pleaded guilty in June to conspiracy to commit wire fraud and was sentenced to four years. He coded a malware loader, researched targets using Google and ZoomInfo, and possessed data stolen from eight US victims who reported over $1.5 million in losses. Investigators found Cobalt Strike running and a Rocket.Chat session over Tor on his laptop when Gardaí arrested him in County Cork, Ireland in July 2023; he was extradited to the US in October 2025. Conti attacked over 1,000 victims across 47 US states and 31 countries, with payouts exceeding $150 million by January 2022.

The Register · Securityupdated Sep 11, 16:07 UTC · 5d agofirst Sep 11, 12:15 UTC · 5d agoPolicy & legal 7 sources

nex-agi/Nex-N2.5-Pro — new model trending #30 on Hugging Face

Nex-AGI launches Nex-N2.5 agentic model family (mini/Pro/Max), with Max built on a 1.6-trillion-parameter MoE foundation.

Nex-AGI introduced Nex-N2.5, a next-generation family of agentic models in three sizes (mini, Pro, Max) focused on long-horizon agentic tasks including computer use, web browsing, and autonomous program execution. Nex-N2.5-Max is built on a 1.6-trillion-parameter text-only Mixture-of-Experts foundation, marking the company's first complete post-training effort at trillion-parameter scale. Weights will be released open-source on Hugging Face and ModelScope, with hosted access via OpenRouter. Benchmark comparisons against Claude Opus 5, GPT-5.6 Sol, Kimi-K3, GLM-5.3, DeepSeek-V4-Pro-0813, and Qwen3.8-Max show competitive scores on Terminal-Bench 2.1 and SWE-Bench Pro, though weights were listed as "coming soon" at publication.

Hugging Face trending modelsSep 8, 11:01 UTC · 8d agoModel release1

[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

DeepSeek released V4.1-Flash, an open-weight 763B-parameter model with a novel causal encoder-decoder architecture, 1M context, vision input, and MIT license.

DeepSeek launched V4.1-Flash, an open-weight MIT-licensed model using a novel causal encoder-decoder architecture with 763B total parameters and asymmetric active parameters: 8B for prefill and 16B for decode. It supports 1M-token context and text+image input, priced at $0.30 per 1M input and $1.20 per 1M output tokens with a 50% off-peak discount. Artificial Analysis scored it 40 on its Intelligence Index, above DeepSeek V4 Pro 0813, and Vals ranked it the #1 open-weight model ahead of Kimi K3. Baseten shipped day-0 support and Ollama began rolling it out to paid subscribers.

Latent SpaceSep 12, 05:56 UTC · 4d agoModel release 4 sources1