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Divide, Consult, Conquer: Capability Laundering Through Aligned LLMs
Attack shows unaligned orchestrators can launder capabilities from aligned frontier LLMs via benign subtask consultation, raising Gemma-4-31B CBRN rubric score from 62.3 to 83.1.
The paper introduces capability laundering, where a weaker unaligned model decomposes a harmful task into benign-looking subproblems, queries a stronger aligned model on each, and recombines answers locally, bypassing per-interaction safety evaluations. Evaluation used GPT-5.5, Claude Opus 4.8, and Grok-4.3 as consultants to four local orchestrators on CyBench, BountyBench, and CBRN tasks. On CyBench, Gemma-4-31B recovered 8/14 candidate tasks with GPT-5.5 and 7/9 with Opus, while Muse-Glimmer-30B recovered none. Across an eight-step hypothetical bioweapon attack chain, consultation raised Gemma-4-31B's mean rubric score from 62.3 to 83.1, exposing a gap in defenses that only refuse complete harmful tasks.
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Rhysida Publishes Berlin Government Data After €2m Extortion Demand Refused
Rhysida published 5.7 TB of Berlin state government data, including sensitive CBRN emergency plans, after the state refused a €2m ransom demand.
The Rhysida ransomware gang leaked roughly 5.7 TB — about 1.4 million files — stolen from Berlin's state network after the government declined to pay 30 bitcoins (about €2m) by the September 4 deadline. The dump reportedly includes sensitive state emergency plans for terrorist attacks and CBRN disaster scenarios in a folder titled 'AG CBRN-Rahmenplanung', plus personnel files, absence lists, payroll data, and home addresses, potentially affecting tens of thousands of people. Berlin says there are no indications the state network remains compromised and will notify affected individuals on a risk-based basis after forensic analysis.
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Import AI 468: 23 RSI ideas; PostTrainBench+; and how trust and transparency interplay with AI racing
Import AI covers 23 IFP policy ideas for automated AI R&D risks and MIT/Columbia's game theory of AI racing slowdowns.
Think tank IFP published 23 policy recommendations across seven categories to help policymakers address risks from increasingly automated AI R&D. MIT and Columbia researchers released 'Racing to Ruin,' a game theory model showing that coordinated slowdowns between rival AI firms hinge on trust and transparency. The newsletter also links a short story on interacting with powerful AI systems.
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Berlin Ransomware Leak Exposes State Secrets
Rhysida ransomware leaked 5.79 TB of Berlin state government data on the dark web after the city refused a 30 Bitcoin ransom.
The Rhysida ransomware group published 5.79 TB (about 1.44 million files) of Berlin state administration data on its leak site on August 28, 2026, after the city-state refused a 30 Bitcoin ransom. The claimed dataset includes personal data on 12,076 individuals, over 5,000 personnel files, payroll records, plaintext credentials for systems like PAYONE and Z_ADMIN, Bundesrat committee protocols, and documents allegedly containing state secrets. Leaked material reportedly covers national defense emergency plans, federal secret communication channels, a CBRN threat planning folder, and vulnerability analyses of Berlin's water supply. Berlin's government has activated a central crisis unit to review the leaked data and notify affected citizens and businesses.
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Building AI to accelerate science and improve lives
Google highlights AI-for-science advances: AlphaGenome Atlas mapping 9 billion genetic variants, WeatherNext 3 weather model, and global health AI tools.
Google detailed AI advances across science and health, including AlphaGenome Atlas, which mapped all 9 billion possible single-letter genetic changes in the human genome and was made openly available. WeatherNext 3 delivers 50% more accurate precipitation forecasts a day or more ahead and is already in products. AlphaFold is used by 4 million researchers in 190 countries, TB chest X-ray screening has processed 25,000+ scans across six nations, and the diabetic retinopathy model has supported 1.15 million screenings. Google also released its AI & Economy ATLAS global usage insights.
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Introducing Gemini 3.8 Flash and 3.8 Flash Cyber
Google DeepMind releases Gemini 3.8 Flash and 3.8 Flash Cyber with improved reasoning, coding, and cybersecurity vulnerability detection and automated patching.
Google DeepMind introduced Gemini 3.8 Flash, its strongest reasoning and coding model, priced at $0.75 per million input and $3.75 per million output tokens, alongside Gemini 3.8 Flash Cyber, a cybersecurity-specialized variant offered to trusted defenders via the Fairwind Program. The Cyber variant shows frontier-level autonomous vulnerability discovery on CyberGym, exceeds 70% success on an internal benchmark spanning 20 programming languages, and scores 47.2% pass@1 on the CWE-Bench patching benchmark. Google reports it produced 2.6x more correct Chrome vulnerability patches than larger commercial models and found a critical foundational bug in under 2 hours.
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