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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 new Brazilian bill proposes the establishment of a permanent financial sandbox to support blockchain and tokenization testing

According to Livecoins, Brazilian Federal Deputy Lincoln Portela proposed Bill No. 2.901/2026, which aims to establish a framework for a national fintech and digital finance platform, creating a permanent regulatory sandbox system for testing blockchain technology and asset tokenization, supervised by the Central Bank of Brazil.The bill requires regulatory requirements to be proportional to the size of the company, allowing small fintech startups to apply simplified standards, and prohibits the government from imposing bureaucratic measures or obligations that do not align with the digital nature of the cryptocurrency market. The sandbox testing scope includes financial flow tracking, artificial intelligence credit applications, and programmable payment practices.The bill also allows companies to share network infrastructure and institutional adaptation databases, but they must comply with data protection regulations. The cooperation mechanism aims to combat financial crimes in cryptocurrency transactions, promote customer identity verification, and enhance cybersecurity.The bill also proposes the establishment of a national system for digital financial integrity, coordinating network regulatory actions to combat criminal structures that use cryptocurrency to hide wealth. Fines for non-compliant companies can reach up to 20% of their annual profit or revenue. The bill will be discussed in various committees of the House of Representatives.

Ernst & Young launches Blockchain Privacy Sandbox, supporting the development of privacy smart contracts on EVM chains

EY announced the launch of the Blockchain Privacy Sandbox, a web-based development environment designed to help businesses and developers experiment with privacy-preserving smart contracts on public chains compatible with the Ethereum Virtual Machine. It is reported that this sandbox environment is based on the open-source technology Starlight, allowing developers to convert standard Solidity smart contracts into applications with privacy protection features while retaining the original contract logic, and providing exploratory, replicable, and modifiable sample projects to accelerate proof of concept development.Currently, the Blockchain Privacy Sandbox is mainly used for experimentation and validation, supporting businesses in assessing the feasibility of privacy smart contracts, testing functionalities, and validating application scenarios before officially integrating Starlight. EY stated that this tool lowers the technical barrier for conducting privacy experiments on public chains by providing an easy-to-use web environment. Starlight, as the underlying ZKP compiler, has been open-sourced, allowing developers to integrate privacy features through its GitHub repository. As businesses' demand for data privacy protection on public chains increases, the attention on zero-knowledge proof technology continues to rise. Relevant reports indicate that the global ZKP market is expected to reach approximately $7.6 billion by 2033.
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