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first_img The Internal Revenue Service (IRS) of the United States plans to reform the voluntary disclosure program, reduce tax penalties, and expedite processing

According to a report by Forbes on Friday, the Internal Revenue Service (IRS) is preparing to reform its voluntary disclosure program, planning to reduce penalties and expedite the processing of tax violation cases, including those involving cryptocurrency.Jarod Koopman, head of the IRS Criminal Investigation Division, stated that the agency aims to launch the revised program before December and to close cases within 120 days after taxpayers complete the required submission process. He noted that the new plan will not establish a separate disclosure channel for digital assets but will apply the same voluntary disclosure procedures to other forms of tax noncompliance. Koopman also mentioned that the penalties under the revised program will be significantly lower than current levels, although he did not provide specific amounts. The IRS is considering allowing taxpayers to settle debts through installment payments or settlement offers.According to Forbes, the current program often takes a year or longer to complete and primarily targets taxpayers who intentionally fail to comply with tax laws and may face criminal prosecution, rather than those who make reporting errors due to negligence. Meanwhile, legislative efforts are advancing another voluntary disclosure program aimed at cryptocurrency taxpayers. Section 502 of the Digital Asset Taxation Certainty Act will establish a correction process with clear penalty standards for past violations, and the bill was passed by the House Ways and Means Committee in September.

first_img Anthropic: Claude has completed large-scale formal verification of the open-source library

On October 22, the Frontier Red Team of the artificial intelligence company Anthropic released research stating that large language models can automatically write formal proofs on a larger scale. The team collaborated with Theorem to use Claude to prove safety properties on over 100 real open-source libraries at the RISC-V assembly level, claiming this is the first known instance of using AI for large-scale formal verification of production software at the assembly level. During the proof-writing process, vulnerabilities that had gone undetected for years were also discovered.The experiment converted existing compilable fuzz tests from Google OSS-Fuzz into specifications: under assumptions of single-threaded static binaries, fixed memory budgets, RISC-V CPUs, and Linux, for any input less than 64 MB, the program should exit normally without triggering memory safety errors or assertion failures. Within weeks, Claude proved the aforementioned properties for 239 entry points in 123 OSS-Fuzz libraries after patching the identified issues. The proofs targeted compiled RISC-V instructions, approximately 180 million lines of Rocq, and were checked by the Rocq kernel. The page states that this does not mean these libraries are free of vulnerabilities, as remaining issues may lie outside trusted components or the scope of the proofs.The page also mentions that the team had Claude formalize RFC 1950 and proved that the zlib implementation in the Linux kernel conforms to that specification at the x86 binary level; an interpreter written in Rust covering a large subset of Python showed a 99.95% consistency with CPython behavior across over 1.7 million randomly generated programs. In 36 small verification tasks, Opus 5.5 proved that about half required approximately 40% fewer tokens than Opus 5. The team also pointed out that the proofs targeted single-threaded, statically linked RISC-V binaries, and the proof checker cannot determine whether the specifications align with reality.

first_img Alibaba Cloud helps Jielue Xingchen build a computing power factory, creating 30,000 sandboxes in minutes

The official account of Alibaba Cloud stated that the large model company Step Star has globally released its flagship open-source model Step 5 Preview, positioned as a primary working model for real-world intelligent agent tasks, excelling in AI programming, software engineering, professional knowledge work, and financial scenarios. The model has a total of 600 billion parameters and 27 billion active parameters, utilizing sparse MoE, with a maximum context window of 1 million, capable of processing text, images, and videos. The article mentions that it recently ranked second globally in both weekly and daily call volume on OpenRouter. On the day of the release, Alibaba Cloud announced the completion of DAY0 adaptation, optimized for joint inference based on chips, super node instances, and models, with inference computing power provided by the Lingjun super node.Step Star has developed its own intelligent agent reinforcement learning training platform, with the sandbox platform managed by Alibaba Cloud. The solution is based on Alibaba Cloud's Agent Sandbox and Kubernetes container service, aimed at elastic computing power in training mode, claiming to create tens of thousands of sandboxes in a single minute, with a maximum concurrency of up to one million, compatible with E2B API, and providing native Kubernetes interfaces. Through multi-level image caching, intelligent pre-scheduling, and control link optimization, it achieves millisecond-level application and minute-level creation of 30,000 sandboxes, with the sandbox lifecycle uniformly managed by Alibaba Cloud's backend.In terms of storage, each Pod starts with 15GB of free temporary storage, automatically increasing by 30GB each time when usage exceeds 70%, up to a maximum of 300GB. For security, MicroVM-level isolation is adopted by default, covering computing, networking, storage, and permissions, with zero-trust access to cloud products and large model interfaces. The results provided in the article include: a 90% reduction in image startup time, model evaluation cycles compressed from weekly to daily, and an average savings of about 40% on EBS storage costs; relying on ACK One Fleet, it can support the stable operation of hundreds of thousands of sandboxes simultaneously.

Bithumb administrative lawsuit held for the first time: claims that transfers of less than 1 million Korean won have regulatory gaps

According to South Korean media Digital Asset, the Second Division of the Seoul Administrative Court held its first hearing on October 22 regarding the administrative lawsuit between Bithumb and the Financial Intelligence Unit of Korea (FIU). The FIU determined that between August 28, 2022, and April 3, 2025, Bithumb conducted 45,772 transactions with 18 unreported cryptocurrency operators, and based on this, imposed sanctions, including a partial suspension that restricts new customers from transferring cryptocurrency assets externally for six months.Bithumb stated in court that transactions of 1 million won or more are subject to the "travel rule," and unreported operators have been excluded from the list of optional exchanges, thus the number of violations for this amount range is zero. Transactions below 1 million won were not subject to the travel rule at that time, and the platform had no legal basis to require customers to provide information about the receiving exchange, nor did the regulatory authorities specify a blocking method. Bithumb also mentioned that after integrating the Chainalysis API, only about 2% of the addresses that could not be confirmed were later identified as unreported operators designated by the FIU. If all were blocked, the remaining 98% of normal transactions would be affected, and the platform could also face user claims.Bithumb also believes that the six-month sanction is excessive, effectively equivalent to prohibiting the platform from acquiring new customers. The company also questioned the FIU's criteria for identifying overseas operators and the reasonableness of the basis for the sanctions.

first_img Bitcoin Core adjusts vulnerability disclosure policy to address AI vulnerability exploitation

Bitcoin core developer Antoine Poinsot announced an adjustment to the security vulnerability disclosure policy in the Bitcoin development mailing list. He stated that in the past, vulnerabilities were often kept secret for a long time to allow users to complete upgrades before details were made public, but this also led to fixes not being backported to older versions, requiring users to wait for the next major release. Poinsot pointed out that large language models make some vulnerabilities very easy to rediscover, and the protection that continued delays in fixing can provide is now quite limited.According to the new policy, vulnerabilities deemed "easy to discover" will be fixed as soon as possible in all maintained major versions, with security announcements released simultaneously. This classification applies to vulnerabilities that can be discovered with minimal effort, such as through simple LLM prompts. Other vulnerabilities will still follow the disclosure timeline based on severity: low-severity vulnerabilities will be disclosed two weeks after the major release containing the fix; medium to high-severity vulnerabilities will be disclosed two weeks after the last affected version reaches its end of life (usually one year after the fix is released in a new major version). Critical vulnerabilities are not covered by the standard policy and may require ad hoc procedures.Bitcoin ecosystem security researcher Luke de Wolf stated that he previously disagreed with Poinsot's security strategy but believes this update is a good adjustment. In August of this year, the volunteer-based Bitcoin Red Team reported nearly 5,000 potential issues across 390 projects, with only about one-fifth being reproducible at that time. In the same month, Core Lightning developers urged operators to upgrade or take nodes offline after receiving multiple AI-generated vulnerability reports, while keeping technical details confidential for two weeks.
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