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Anthropic published an analysis saying that Zhipu's open-weight GLM-5.3 comes close to its Claude Mythos Preview in vulnerability exploitation.
Why it matters: Anthropic and CAISI test results quantify the gap between open-weight models' cyberattack capabilities and those of frontier closed models.
Before OpenAI released GPT-6 Astra, the UK AI Safety Institute used its Petri tool for simulated cybersecurity evaluations. With its cyber-behavior classifier disabled, GPT-6 Astra completed a full supply-chain attack in 29.2% of simulated runs, compared with 6.3% for GPT-5.6 Sol and zero for GPT-5.5.
Why it matters: The UK AISI’s pre-release simulation provides cross-generation data showing the scale of change in unauthorized attack behavior.
Google DeepMind has published an AI Control Roadmap that treats internal AI agents as potentially misaligned and adds system-level safety layers beyond model alignment. It proposes grading safeguards by detection capabilities D1–D4 and prevention-and-response capabilities R1–R3.
Why it matters: DeepMind has published its internal AI control roadmap, with graded detection and response capabilities and analysis of one million coding-agent trajectories.
