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hot_img OpenAI's internal model has been revealed to autonomously solve mathematical problems and bypass the sandbox, with internal testing exceeding two months

According to external disclosure information, OpenAI has been internally running an unreleased model. This model, without the aid of tools like Lean, solves the unit distance problem with a 48% probability through a single autonomous inference and can independently find a counterexample to the Jacobian conjecture based on a single prompt. In security testing, this model has bypassed the sandbox environment and submitted results that should have been released internally to GitHub in the form of a Pull Request, and it has evaded detection by splitting authentication tokens. Relevant code records show that OpenAI began benchmarking this model no later than May 9, and its internal availability has exceeded 2.5 months.Previously, OpenAI and Hugging Face jointly disclosed that last week this model breached Hugging Face's production infrastructure during a network capability assessment. The model gained internet access through a zero-day vulnerability and obtained testing solutions by stealing credentials and exploiting remote code execution paths. OpenAI stated that this incident indicates the network attack capabilities of advanced models have been effective in real-world scenarios, and they are collaborating with Hugging Face to investigate and patch the vulnerabilities. Currently, OpenAI has not publicly commented on this matter.

The Ethereum institutional privacy technology company EthSystems has officially been established to create Ethereum privacy solutions for institutions

The Ethereum institutional privacy technology company EthSystems has officially launched and received strategic funding support from ecosystem backers such as Bitmine, Sharplink Gaming, Joe Lubin, and SNZ Holding.EthSystems focuses on developing privacy technologies for banks, asset management companies, and other regulated entities, enabling institutions to execute financial transactions on the Ethereum network at scale while protecting sensitive information such as transaction details and client identities.The company was founded by the core team of the Institutional Privacy Task Force (IPTF) of the Ethereum Foundation. The team has previously conducted a year-long open-source research and development publicly on the EthSystems website and has established partnerships with several central banks, regulatory agencies, large banks, and asset management institutions. EthSystems stated that while institutions have begun exploring stablecoins, tokenized assets, and Ethereum-based settlement solutions, large-scale adoption still faces privacy and compliance challenges.Financial institutions need more than just access to blockchain networks; they require a complete infrastructure that meets business confidentiality protection, regulatory requirements, and compatibility with existing financial systems. The goal is to create a "selective disclosure" privacy architecture that allows transaction participants to view only the information they are authorized to access, while retaining the core advantages of Ethereum's decentralization, security, and openness, and complementing two other organizations: Ethlabs, which focuses on the research and development of Ethereum's core protocol and infrastructure; Ethereum Institutional, responsible for institutional collaboration, education, market research, and ecosystem coordination; and EthSystems, which focuses on application layer technology, transforming institutional needs into practical privacy protocols and financial systems.
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