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Conti Hacker Who Built Malware and Attacked Victims Gets Four-Year Sentence

Ukrainian lawyer and Conti malware developer Oleksii Lytvynenko was sentenced to four years in U.S. prison for wire fraud conspiracy tied to Conti ransomware.

Lytvynenko, 44, admitted coding a loader for Conti and holding stolen data from eight U.S. and four overseas victims; prosecutors linked his actions to attacks on at least 12 companies. Conti infected more than 1,000 organizations across 47 U.S. states and 31 countries between 2020 and 2022, with victim payouts exceeding $150 million. Arrested in County Cork in July 2023 with Cobalt Strike running and an active Rocket.Chat session over Tor, forensic evidence showed his ransomware activity continued after Conti's 2022 collapse.

Security Affairs · 4d agoPolicy & legal

Ukrainian Conti Ransomware Developer Sentenced to 4 Years in US Prison

A US court sentenced Ukrainian Oleksii Lytvynenko to four years in prison for developing malware loaders and handling stolen data for the Conti ransomware operation.

Oleksii Oleksiyovych Lytvynenko, 44, was arrested in Ireland in 2023, extradited to the US in late 2025, and pleaded guilty to wire fraud in June 2026. He admitted joining the Conti gang in September 2021 and helping develop a malware loader, and investigators found victim data in his possession suggesting participation in actual attacks. The Conti operation is estimated to have received at least $150 million in ransoms from victims in more than 30 countries. The sentencing follows recent terms for Karakurt negotiator Deniss Zolotarjovs (8.5 years) and the Ransom Cartel administrator (16 years).

SecurityWeekupdated · 5d agofirst · 5d agoPolicy & legal 7 sources1

What's Scarier Than Agents Taking over Internet? CEO Cartel Trying Take over AI

Opinion essay argues Dario Amodei's proposals for embedded evaluators and frontier AI coordination would require antitrust waivers and entrench a large-lab cartel.

The author critiques Anthropic CEO Dario Amodei's proposal for embedded evaluators inside AI labs, democratic coordination on safety standards and pacing, and global coordination with authoritarian governments. He argues such coordination requires loosening antitrust law, burdening startups while shielding incumbents like Anthropic, OpenAI, and xAI, and doubts verifiable global pacing given enormous defection incentives. The piece links lab motivations to data center subsidy pushback, competition from open-source and low-cost Chinese models, and upcoming IPO financial disclosures.