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“White-Haired Stock God” Serenity: Chinese VC Funds Are Accelerating Their Flow into Physical AI and World Model Tracks
: "White-Haired Stock God" Serenity posted on platform X, stating that based on the capital flow direction in China's private VC market, institutions are currently pouring into fields related to Physical AI and World Models on a large scale.Data shows the approximate capital distribution as follows: Large Models/LLMs at about $23.56 billion, AI Infrastructure and Technology Layer at about $15.74 billion, Embodied Intelligence/Physical AI at about $13.36 billion, AIGC Applications at about $8.79 billion, and Autonomous Driving plus other top 20 sub-sectors totaling about $3.82 billion (note: metrics may not be directly comparable).Serenity pointed out that early-stage pure foundational model financing is largely closed, with capital more concentrated in existing leading companies and the World Model direction. He expects this trend to also appear in the US, potentially concentrating further towards leading companies like Anthropic and OpenAI. Regarding AIGC applications, Serenity believes this track's commercialization is already relatively mature, but an absolute winner has yet to emerge, exhibiting a fragmented competitive landscape in both China and the US markets.Overall, Serenity concluded that current AI investments continue to flow into infrastructure and the semiconductor supply chain. Meanwhile, capital is rapidly rotating towards Physical AI and Embodied Intelligence, but the World Model track still lacks direct investment targets.
Claw Intelligence closes $3 million seed funding round, with participation from Castrum Istanbul and others
According to official announcements, Web3 intelligence-layer project Claw Intelligence has raised $3 million in seed funding. Investors include Castrum Istanbul, Titans Ventures, Super Labs, and Genesis Capital. Claw Intelligence is simplifying user interaction with the Web3 ecosystem and underlying computing resources through its unified intelligence layer, lowering operational barriers. The platform leverages an encryption-native Model Context Protocol (MCP) service to transform fragmented data endpoints into conversational workflows. New features include a secure, isolated large language model (LLM)-powered code execution sandbox that safely runs code directly within the chat interface—enabling real-time computation, data processing, and script prototyping; and LLM-driven cross-device/multi-computer control, allowing users to centrally manage multiple devices and servers via natural-language commands.
Covenant AI Announces Exit from Bittensor Network, Claims Its Decentralization Promise Is Hollow
Sam Dare, founder of Covenant AI, announced that Covenant AI has officially exited the Bittensor network. Previously, Covenant AI completed the largest decentralized LLM pretraining project in history—Covenant-72B (a 72-billion-parameter model developed by over 70 independent contributors)—which drew attention from NVIDIA’s CEO and was cited by an Anthropic co-founder. In its statement, Covenant AI accused the Bittensor network of long concentrating actual control in the hands of co-founder Jacob Steeves (“Const”), rendering the so-called “three-signature multisig governance” merely a theatrical performance of decentralization, with real power never truly distributed. Recently, Jacob Steeves unilaterally imposed punitive measures against Covenant AI, including: suspending its subnet earnings, revoking its community channel moderation privileges, unilaterally deprecating its subnet infrastructure, and exerting economic pressure via large-scale token dumping during the ongoing conflict between the two parties. Covenant AI stated it cannot continue fundraising, recruiting talent, or soliciting community resources on a network where the promise of “decentralization” can be unilaterally revoked by a single individual. Its research outcomes, team, and models will depart alongside the team, and a new project—including related progress—will be publicly announced shortly.
Bitcoin Core Adjusts Security Disclosure Rules, Requires Vulnerabilities to Be Fixed Promptly
Odaily reports: Bitcoin Core developers have merged a security policy adjustment. For vulnerabilities that can be easily discovered or rediscovered through simple large language model (LLM) prompts, the previous long-term confidential disclosure mechanism will no longer be used. The new rules allow developers to mark such issues as "easy to find" during vulnerability classification, then backport fixes to all still-supported versions and release them as soon as possible through minor version updates, along with a security advisory and some vulnerability details.Previously, Bitcoin Core scheduled disclosure based on vulnerability severity, with medium- and high-risk vulnerabilities usually only made public after the affected versions stopped being maintained. This adjustment stems from AI tools lowering the threshold for vulnerability discovery: in July this year, a Bitcoin Red Team composed of 16 developers used AI models to scan about 390 Bitcoin-related projects and recorded 4,962 findings in one day, of which 85 were listed as critical issues. Developers noted that continuing to extend the confidentiality period for such vulnerabilities can no longer effectively prevent attacks and instead delays the release of fixed versions; however, the new rules also mean that fixes may lack longer testing time. Currently, no vulnerability has been officially marked as falling into the "easy to find" category under the new rules. (CoinDesk)
Bitcoin Core Updates Vulnerability Disclosure Policy, Easily Discoverable Vulnerabilities Will Be Fixed Promptly and Announced Simultaneously
According to Cointelegraph, Bitcoin Core developer Antoine Poinsot stated on Thursday on the bitcoin-dev mailing list that large language models (LLMs) have made certain software vulnerabilities extremely easy to rediscover. Maintaining long-term secrecy is already of limited value and instead delays the release of patched versions, prompting the team to update its vulnerability disclosure policy. The new policy dictates that "easily discoverable" vulnerabilities, which can be identified with minimal cost such as through simple LLM prompts, will be patched as soon as possible across all supported major versions, alongside the simultaneous release of security advisories. Other vulnerabilities will continue to be disclosed based on severity: low-severity vulnerabilities will be disclosed two weeks after the release of the major version containing the fix; medium-to-high-severity vulnerabilities will be disclosed two weeks after the end-of-life (EOL) of the last affected version, typically around one year after the patch release; critical vulnerabilities will be handled through a dedicated process.
Florida sues OpenAI and Sam Altman, accusing them of constituting "public nuisance"
According to Forbes, the state of Florida has filed a lawsuit against OpenAI and its CEO Sam Altman, alleging that its generative AI and large language models (LLMs) pose a threat to public health and safety, constituting a "public nuisance" in the legal sense. The state likened AI chatbots to polluting factories, arguing that they cause psychological harm to the public, provide uncertified advice, and disrupt public order. Florida is seeking substantial monetary damages and injunctive relief.
Japan’s Financial Services Agency Establishes New Crypto Assets and Stablecoins Division, Toshiaki Adomi Appointed as First Director
Odaily News: The Japan Financial Services Agency (FSA) has announced personnel appointments. As part of its organizational restructuring, the agency has established a new "Crypto Assets and Stablecoins Division" dedicated to overseeing crypto assets and stablecoins, with Toshiaki Adomi appointed as its first Director. Adomi graduated from the Faculty of Law at Osaka University in 2002 before joining the FSA. He subsequently earned an MBA from the University of Birmingham in the UK and an LLM from the London School of Economics and Political Science, holding positions in banking supervision and policy coordination. From July 2025, he served as a Counselor at the General Policy Bureau, and until August 1, 2026, held the role of Senior Counselor for Postal Savings and Insurance Supervision.
Research: AI Code Review Can Reduce Review Time, But Quality Risks Cannot Be Ignored
According to the research summary published by Rohan Paul, a large-scale study covering 207 GitHub projects and 1.02 million pull requests shows that introducing AI agent review can reduce code review time by 2.5 to 4.5 days/KLOC, but at the cost of declining review quality—in reviews involving AI, 78%~94% of PRs exhibit "review smells", higher than the 69%~76% in pure human reviews. The study points out that repeatedly assigning the same AI reviewer identity is the main reason leading to the decline in review diversity. Notably, projects that introduced LLM review extensively in the early stage did not achieve significant efficiency improvements.
Coinbase CEO: Coinbase will support pre-IPO perpetual contracts, stock options, and tokenized stocks
Brian Armstrong posted on the X platform, stating that Coinbase now includes pre-IPO perpetual contracts, stock options, and will soon support tokenized stocks. Coinbase has also redesigned Coinbase Advanced and has begun integrating global liquidity between US and international users, as well as between Coinbase and Deribit users. CoinbaseDev is providing stablecoin payment capabilities for enterprises, launching fully managed accounts based on its compliance technology stack, and introducing a new developer tools dashboard. On the Base side, Coinbase announced the launch of private transactions and a web-based Base App. Coinbase is also becoming the financial account for AI, supporting wallets for AI agents, providing AI-driven financial advice, and connecting Coinbase accounts to users' commonly used LLMs.
Research: Stablecoin De-Pegging May Have a "Critical Threshold," Severe Narrative Shocks Can Trigger Panic Selling
The Institute of Financial Technology at Renmin University of China published a translated overview of stablecoin research from the Journal of International Money and Finance. The related research employs large language model (LLM) agents to analyze stablecoin de-pegging risks, indicating that de-pegging exhibits distinct nonlinear and threshold characteristics. Arbitrage mechanisms can absorb a certain degree of informational pressure, but once narrative severity reaches a "critical threshold," the system may rapidly enter a sustained de-pegging state.
“White-Haired Stock God” Serenity: Chinese VC Funds Are Accelerating Their Flow into Physical AI and World Model Tracks
: "White-Haired Stock God" Serenity posted on platform X, stating that based on the capital flow direction in China's private VC market, institutions are currently pouring into fields related to Physical AI and World Models on a large scale.Data shows the approximate capital distribution as follows: Large Models/LLMs at about $23.56 billion, AI Infrastructure and Technology Layer at about $15.74 billion, Embodied Intelligence/Physical AI at about $13.36 billion, AIGC Applications at about $8.79 billion, and Autonomous Driving plus other top 20 sub-sectors totaling about $3.82 billion (note: metrics may not be directly comparable).Serenity pointed out that early-stage pure foundational model financing is largely closed, with capital more concentrated in existing leading companies and the World Model direction. He expects this trend to also appear in the US, potentially concentrating further towards leading companies like Anthropic and OpenAI. Regarding AIGC applications, Serenity believes this track's commercialization is already relatively mature, but an absolute winner has yet to emerge, exhibiting a fragmented competitive landscape in both China and the US markets.Overall, Serenity concluded that current AI investments continue to flow into infrastructure and the semiconductor supply chain. Meanwhile, capital is rapidly rotating towards Physical AI and Embodied Intelligence, but the World Model track still lacks direct investment targets.
BNB Agent Studio is Now Live on BNB Chain Mainnet
BNB Chain has announced the official mainnet launch of its AI Agent development platform, BNB Agent Studio.Developers can now use a single prompt in AI coding tools like Cursor and Claude Code to complete Agent wallet creation, on-chain identity registration (ERC-8004), and deployment, without needing to separately set up wallets, identities, payments, custody, or LLM integration.Once deployed, Agents can use the x402 protocol to automatically deduct fees from users' pre-funded wallets to cover LLM usage, and they can be discovered and invoked by other Agents via the ERC-8183 task interface. The entire process runs on the AWS Bedrock AgentCore.The platform is also launching a limited-time free trial, where users can experience the full deployment process on the BSC testnet using their GitHub account.
Gate Research Institute: Multi-Agent LLM Trading Framework Significantly Outperforms Buy & Hold Strategy in BTC Backtesting
Odaily Odaily News: A recent report released by Gate Research Institute, titled "Research and Backtesting Analysis of BTC Trading Framework Based on Multi-Agent LLM," points out that compared to a single LLM directly generating trading signals, the Multi-Agent LLM architecture more closely mirrors the research and investment process of real financial institutions. By leveraging collaboration and debate among analysts, researchers, traders, and risk control teams, it enhances the transparency and risk control capabilities of trading decisions. The research, based on the TradingAgents framework, constructs an AI trading system applicable to the crypto scenario for the BTC market, introducing multiple agent roles such as technical analysis, news analysis, sentiment analysis, and macro/on-chain analysis.Using BTC/USDT 1-hour data, the study conducted historical backtesting of the TradingAgents-BTC strategy. The results show that the strategy achieved a total return of +20.25% during the testing period, significantly outperforming the Buy & Hold strategy's -7.89% over the same period. Furthermore, its maximum drawdown was controlled at -17.41%, lower than the Buy & Hold's -27.06%. The research suggests that during periods of consolidation and decline, the multi-agent framework can reduce some risk exposure through Sell/Underweight and Flat states, and re-enter long positions during market rebounds, thereby improving overall risk-adjusted returns.The report indicates that the Multi-Agent LLM framework shows certain application potential in crypto trading scenarios. However, the current backtesting period covers only about three months, and 1-hour level trading may still be affected by transaction fees, slippage, and signal latency. Future work requires further validation of the strategy's stability and generalization capabilities over longer historical periods, different market conditions, and across a wider range of asset classes.
Covenant AI Announces Exit from Bittensor Network, Claims Its Decentralization Promise Is Hollow
Sam Dare, founder of Covenant AI, announced that Covenant AI has officially exited the Bittensor network. Previously, Covenant AI completed the largest decentralized LLM pretraining project in history—Covenant-72B (a 72-billion-parameter model developed by over 70 independent contributors)—which drew attention from NVIDIA’s CEO and was cited by an Anthropic co-founder. In its statement, Covenant AI accused the Bittensor network of long concentrating actual control in the hands of co-founder Jacob Steeves (“Const”), rendering the so-called “three-signature multisig governance” merely a theatrical performance of decentralization, with real power never truly distributed. Recently, Jacob Steeves unilaterally imposed punitive measures against Covenant AI, including: suspending its subnet earnings, revoking its community channel moderation privileges, unilaterally deprecating its subnet infrastructure, and exerting economic pressure via large-scale token dumping during the ongoing conflict between the two parties. Covenant AI stated it cannot continue fundraising, recruiting talent, or soliciting community resources on a network where the promise of “decentralization” can be unilaterally revoked by a single individual. Its research outcomes, team, and models will depart alongside the team, and a new project—including related progress—will be publicly announced shortly.
OKX Star: We detect and respond to various cyberattacks every month
Odaily reports: OKX Star posted on X, stating: "OKX detects and responds to various cyberattacks every month, including advanced persistent threat (APT) attacks targeting the crypto industry. More than a year ago, OKX launched LLM-based automated penetration testing. Regarding the security incidents recently encountered by our peers, we will certainly learn lessons seriously, comprehensively strengthen self-inspections, continuously improve our security system, and always remain humble and vigilant."
Bitcoin Core Adjusts Security Disclosure Rules, Requires Vulnerabilities to Be Fixed Promptly
Odaily reports: Bitcoin Core developers have merged a security policy adjustment. For vulnerabilities that can be easily discovered or rediscovered through simple large language model (LLM) prompts, the previous long-term confidential disclosure mechanism will no longer be used. The new rules allow developers to mark such issues as "easy to find" during vulnerability classification, then backport fixes to all still-supported versions and release them as soon as possible through minor version updates, along with a security advisory and some vulnerability details.Previously, Bitcoin Core scheduled disclosure based on vulnerability severity, with medium- and high-risk vulnerabilities usually only made public after the affected versions stopped being maintained. This adjustment stems from AI tools lowering the threshold for vulnerability discovery: in July this year, a Bitcoin Red Team composed of 16 developers used AI models to scan about 390 Bitcoin-related projects and recorded 4,962 findings in one day, of which 85 were listed as critical issues. Developers noted that continuing to extend the confidentiality period for such vulnerabilities can no longer effectively prevent attacks and instead delays the release of fixed versions; however, the new rules also mean that fixes may lack longer testing time. Currently, no vulnerability has been officially marked as falling into the "easy to find" category under the new rules. (CoinDesk)
Bitcoin Core Updates Vulnerability Disclosure Policy, Easily Discoverable Vulnerabilities Will Be Fixed Promptly and Announced Simultaneously
According to Cointelegraph, Bitcoin Core developer Antoine Poinsot stated on Thursday on the bitcoin-dev mailing list that large language models (LLMs) have made certain software vulnerabilities extremely easy to rediscover. Maintaining long-term secrecy is already of limited value and instead delays the release of patched versions, prompting the team to update its vulnerability disclosure policy. The new policy dictates that "easily discoverable" vulnerabilities, which can be identified with minimal cost such as through simple LLM prompts, will be patched as soon as possible across all supported major versions, alongside the simultaneous release of security advisories. Other vulnerabilities will continue to be disclosed based on severity: low-severity vulnerabilities will be disclosed two weeks after the release of the major version containing the fix; medium-to-high-severity vulnerabilities will be disclosed two weeks after the end-of-life (EOL) of the last affected version, typically around one year after the patch release; critical vulnerabilities will be handled through a dedicated process.
Security agency: Hackers used LLM combined with AI penetration tools to attack South Korean financial institutions, leaking data of approximately 68,000 people
security firm CrowdStrike released an intelligence report stating that an unidentified hacker, between late September and early October, combined large language models (LLMs) with the domestic open-source AI penetration testing tool ARTEX to launch targeted cyberattacks against multiple South Korean financial institutions and steal data.After analyzing the hacker's exposed open directory, it was found that they employed a dual-server architecture centered on a Hong Kong IP, and used models including Claude Code, GLM-5.3, Grok 4.6, and DeepSeek v4.1-flash accessed through an API proxy to orchestrate the attack process. The hacker also asked Claude how to monetize the leaked South Korean data in Telegram groups. According to estimates by South Korean media, at least seven South Korean financial institutions were attacked, including KB Kookmin Bank, Shinhan Bank, and Hana Bank, with personal data of approximately 68,000 people leaked, involving sensitive information such as annual income and loan limits.
北韩黑客组织金速基构建本地 LLM 环境，AI 攻击能力全面升级
攻击手法方面，该组织已转向利用生成型 AI 制作高度仿真的虚拟资产与金融领域文档，用于精准鱼叉式钓鱼攻击，目标涵盖加密货币钱包信息、Gmail 账户及网站注册记录等敏感数据。Genians 安全中心负责人文钟铉警告，随着 AI 技术发展，社会工程攻击将持续精细化，建议企业部署以行为检测为核心的 EDR 威胁猎捕体系加以应对。
One week after the NVIDIA-led AI Safety Alliance OSAA was established, it has already gathered over 120 companies.
According to TechCrunch, the Open Safety AI Alliance (OSAA), led by Nvidia, has exceeded 120 member companies just one week after its establishment, including tech and financial giants such as Adobe, BlackRock, Cisco, Intel, Microsoft, and Visa. During the Black Hat Cybersecurity Conference held in Las Vegas this week, the alliance established a working group named "Shared AI Findings Exchange" (SAFE) and has submitted multiple proposals open for public comment, managed by the Linux Foundation. The proposals cover confidential reporting mechanisms for AI cybersecurity incidents, alert processes for affected parties, and no-fault attribution analysis frameworks. Meanwhile, member companies are also actively contributing open-source technologies: Nvidia open-sourced the LLM vulnerability scanning tool Garak, Amazon contributed the agent building tool Strands Agents and authorization language Cedar, and Okta and Red Hat are advancing agent identity authentication and governance technologies respectively. Notably, Anthropic, OpenAI, and Google have not yet joined the alliance, although OpenAI and Google previously co-signed the open letter that spurred the creation of the alliance.
Bitcoin Core Adjusts Security Disclosure Rules, Requires Vulnerabilities to Be Fixed Promptly
Odaily reports: Bitcoin Core developers have merged a security policy adjustment. For vulnerabilities that can be easily discovered or rediscovered through simple large language model (LLM) prompts, the previous long-term confidential disclosure mechanism will no longer be used. The new rules allow developers to mark such issues as "easy to find" during vulnerability classification, then backport fixes to all still-supported versions and release them as soon as possible through minor version updates, along with a security advisory and some vulnerability details.Previously, Bitcoin Core scheduled disclosure based on vulnerability severity, with medium- and high-risk vulnerabilities usually only made public after the affected versions stopped being maintained. This adjustment stems from AI tools lowering the threshold for vulnerability discovery: in July this year, a Bitcoin Red Team composed of 16 developers used AI models to scan about 390 Bitcoin-related projects and recorded 4,962 findings in one day, of which 85 were listed as critical issues. Developers noted that continuing to extend the confidentiality period for such vulnerabilities can no longer effectively prevent attacks and instead delays the release of fixed versions; however, the new rules also mean that fixes may lack longer testing time. Currently, no vulnerability has been officially marked as falling into the "easy to find" category under the new rules. (CoinDesk)
Bitcoin Core Updates Vulnerability Disclosure Policy, Easily Discoverable Vulnerabilities Will Be Fixed Promptly and Announced Simultaneously
According to Cointelegraph, Bitcoin Core developer Antoine Poinsot stated on Thursday on the bitcoin-dev mailing list that large language models (LLMs) have made certain software vulnerabilities extremely easy to rediscover. Maintaining long-term secrecy is already of limited value and instead delays the release of patched versions, prompting the team to update its vulnerability disclosure policy. The new policy dictates that "easily discoverable" vulnerabilities, which can be identified with minimal cost such as through simple LLM prompts, will be patched as soon as possible across all supported major versions, alongside the simultaneous release of security advisories. Other vulnerabilities will continue to be disclosed based on severity: low-severity vulnerabilities will be disclosed two weeks after the release of the major version containing the fix; medium-to-high-severity vulnerabilities will be disclosed two weeks after the end-of-life (EOL) of the last affected version, typically around one year after the patch release; critical vulnerabilities will be handled through a dedicated process.
Vitalik: Building a Tor-based "paranoid mode" wrapper for the agent tool pi
Odaily reports: Vitalik posted on X platform stating that he has integrated Wrapped zkAPI, Tor, additional cover traffic, and local LLM prompt rewriting into an OpenAI-compatible daemon, and built a "paranoid mode" wrapper for the agent tool pi. Each conversation is assigned an independent Tor circuit, requests include random cover traffic, zkAPI avoids identity leakage through a payment mechanism, and all prompts are rewritten locally; his agent tool runs in a bwrap sandbox with torsocks layered on top, and all operations go through Tor. This solution already has relatively high usability but increases latency; Vitalik stated that Tor is not an ideal privacy solution in this scenario, and more specialized mix networks may require higher bandwidth overhead and built-in constant cover traffic. Lower mainnet deposit and withdrawal gas costs for zkAPI are coming soon.
Security agency: Hackers used LLM combined with AI penetration tools to attack South Korean financial institutions, leaking data of approximately 68,000 people
security firm CrowdStrike released an intelligence report stating that an unidentified hacker, between late September and early October, combined large language models (LLMs) with the domestic open-source AI penetration testing tool ARTEX to launch targeted cyberattacks against multiple South Korean financial institutions and steal data.After analyzing the hacker's exposed open directory, it was found that they employed a dual-server architecture centered on a Hong Kong IP, and used models including Claude Code, GLM-5.3, Grok 4.6, and DeepSeek v4.1-flash accessed through an API proxy to orchestrate the attack process. The hacker also asked Claude how to monetize the leaked South Korean data in Telegram groups. According to estimates by South Korean media, at least seven South Korean financial institutions were attacked, including KB Kookmin Bank, Shinhan Bank, and Hana Bank, with personal data of approximately 68,000 people leaked, involving sensitive information such as annual income and loan limits.
X-Agent Releases Latest Whitepaper: Taking AI from "Content Generation" to "Execution and Transactions"
Odaily News: AI Agent onchain operating system (AI Agent Onchain OS) X-Agent has released its latest whitepaper, systematically introducing its product architecture, MCP ecosystem, business model, and the use cases of $XAGT.The whitepaper points out that the next phase of the AI industry is not just about generating text, images, or code, but about enabling Agents to understand user intent, invoke tools, execute tasks, and complete transactions. Centered around the philosophy of "Speak to Build, Share to Connect," X-Agent allows users to create AI Agents with context, memory, skills, API, and wallet connectivity capabilities through natural language, without writing any code.In terms of business model, X-Agent aims to connect the full chain of Agent creation, MCP capability integration, distribution, payment, and monetization. Developers can package APIs, data, and professional services into MCP capabilities and earn revenue through pay-per-call, subscriptions, or transaction commissions.$XAGT is planned to be used for computing costs of secure runtime environments, LLM and API calls, Agent transaction settlement, MCP service payments, Premium Agent template purchases, and developer deployment. In the future, it will also expand to service staking, multi-Agent settlement, and ecosystem governance scenarios.According to the project team, X-Agent currently has over 1 million registered users, has completed over 1.1 million autonomous tasks cumulatively, and has consumed over 84 billion LLM Tokens. In the future, the project will also advance Super-Agent, enterprise sandbox, decentralized Agent Store, and multi-Agent collaboration systems.
Research: Stablecoin De-Pegging May Have a "Critical Threshold," Severe Narrative Shocks Can Trigger Panic Selling
The Institute of Financial Technology at Renmin University of China published a translated overview of stablecoin research from the Journal of International Money and Finance. The related research employs large language model (LLM) agents to analyze stablecoin de-pegging risks, indicating that de-pegging exhibits distinct nonlinear and threshold characteristics. Arbitrage mechanisms can absorb a certain degree of informational pressure, but once narrative severity reaches a "critical threshold," the system may rapidly enter a sustained de-pegging state.
Related news
OKX Star: We detect and respond to various cyberattacks every month
Odaily reports: OKX Star posted on X, stating: "OKX detects and responds to various cyberattacks every month, including advanced persistent threat (APT) attacks targeting the crypto industry. More than a year ago, OKX launched LLM-based automated penetration testing. Regarding the security incidents recently encountered by our peers, we will certainly learn lessons seriously, comprehensively strengthen self-inspections, continuously improve our security system, and always remain humble and vigilant."
Deepgram Acquires Voice AI Infrastructure Developer Daily; Its Open-Source Framework Pipecat Will Remain Open
According to TechCrunch, voice AI company Deepgram has acquired Daily, the developer of the open-source voice AI infrastructure framework Pipecat. Both parties did not disclose the transaction amount and have committed to maintaining Pipecat as an open-source and vendor-neutral platform. Pipecat manages audio and video streams, integrating speech-to-text (STT), large language models (LLM), and text-to-speech (TTS) to minimize real-time interaction latency.
Bitcoin Core Adjusts Security Disclosure Rules, Requires Vulnerabilities to Be Fixed Promptly
Odaily reports: Bitcoin Core developers have merged a security policy adjustment. For vulnerabilities that can be easily discovered or rediscovered through simple large language model (LLM) prompts, the previous long-term confidential disclosure mechanism will no longer be used. The new rules allow developers to mark such issues as "easy to find" during vulnerability classification, then backport fixes to all still-supported versions and release them as soon as possible through minor version updates, along with a security advisory and some vulnerability details.Previously, Bitcoin Core scheduled disclosure based on vulnerability severity, with medium- and high-risk vulnerabilities usually only made public after the affected versions stopped being maintained. This adjustment stems from AI tools lowering the threshold for vulnerability discovery: in July this year, a Bitcoin Red Team composed of 16 developers used AI models to scan about 390 Bitcoin-related projects and recorded 4,962 findings in one day, of which 85 were listed as critical issues. Developers noted that continuing to extend the confidentiality period for such vulnerabilities can no longer effectively prevent attacks and instead delays the release of fixed versions; however, the new rules also mean that fixes may lack longer testing time. Currently, no vulnerability has been officially marked as falling into the "easy to find" category under the new rules. (CoinDesk)
Bitcoin Core Updates Vulnerability Disclosure Policy, Easily Discoverable Vulnerabilities Will Be Fixed Promptly and Announced Simultaneously
According to Cointelegraph, Bitcoin Core developer Antoine Poinsot stated on Thursday on the bitcoin-dev mailing list that large language models (LLMs) have made certain software vulnerabilities extremely easy to rediscover. Maintaining long-term secrecy is already of limited value and instead delays the release of patched versions, prompting the team to update its vulnerability disclosure policy. The new policy dictates that "easily discoverable" vulnerabilities, which can be identified with minimal cost such as through simple LLM prompts, will be patched as soon as possible across all supported major versions, alongside the simultaneous release of security advisories. Other vulnerabilities will continue to be disclosed based on severity: low-severity vulnerabilities will be disclosed two weeks after the release of the major version containing the fix; medium-to-high-severity vulnerabilities will be disclosed two weeks after the end-of-life (EOL) of the last affected version, typically around one year after the patch release; critical vulnerabilities will be handled through a dedicated process.
Vitalik: Building a Tor-based "paranoid mode" wrapper for the agent tool pi
Odaily reports: Vitalik posted on X platform stating that he has integrated Wrapped zkAPI, Tor, additional cover traffic, and local LLM prompt rewriting into an OpenAI-compatible daemon, and built a "paranoid mode" wrapper for the agent tool pi. Each conversation is assigned an independent Tor circuit, requests include random cover traffic, zkAPI avoids identity leakage through a payment mechanism, and all prompts are rewritten locally; his agent tool runs in a bwrap sandbox with torsocks layered on top, and all operations go through Tor. This solution already has relatively high usability but increases latency; Vitalik stated that Tor is not an ideal privacy solution in this scenario, and more specialized mix networks may require higher bandwidth overhead and built-in constant cover traffic. Lower mainnet deposit and withdrawal gas costs for zkAPI are coming soon.
Security agency: Hackers used LLM combined with AI penetration tools to attack South Korean financial institutions, leaking data of approximately 68,000 people
security firm CrowdStrike released an intelligence report stating that an unidentified hacker, between late September and early October, combined large language models (LLMs) with the domestic open-source AI penetration testing tool ARTEX to launch targeted cyberattacks against multiple South Korean financial institutions and steal data.After analyzing the hacker's exposed open directory, it was found that they employed a dual-server architecture centered on a Hong Kong IP, and used models including Claude Code, GLM-5.3, Grok 4.6, and DeepSeek v4.1-flash accessed through an API proxy to orchestrate the attack process. The hacker also asked Claude how to monetize the leaked South Korean data in Telegram groups. According to estimates by South Korean media, at least seven South Korean financial institutions were attacked, including KB Kookmin Bank, Shinhan Bank, and Hana Bank, with personal data of approximately 68,000 people leaked, involving sensitive information such as annual income and loan limits.