discover

Bitcoin News posted on the X platform that after two weeks of using cutting-edge AI to scan almost the entire Bitcoin open-source ecosystem for vulnerabilities, Bitcoin Red Team member @callebtc stated, "The easily discoverable vulnerabilities have been addressed," and maintainers are verifying "a large number" of serious and high-risk vulnerabilities.@callebtc indicated that the main findings include: decades of accumulated open-source technical debt are being exposed alongside AI capabilities that can discover vulnerabilities at speeds and scales unattainable by human researchers; Lightning seems particularly vulnerable, with its complexity meaning its security status is "worse than average"; unmaintained Bitcoin projects should be considered vulnerable until their security is confirmed.Projects that began building AI security and auditing processes months ago are now in a completely different position compared to those that have been waiting until now. The Bitcoin Red Team has now completed a foundational scan of almost the entire Bitcoin open-source ecosystem. Easily discoverable vulnerabilities have mostly been addressed, but as AI capabilities improve, external red team testing may need to continue indefinitely. Despite discovering and reporting "a large number" of real serious and high-risk vulnerabilities, @callebtc believes this process will ultimately make Bitcoin stronger. The same AI security review will soon expand to areas far beyond Bitcoin.

According to a report by Decrypt, Israeli cybersecurity company ASecurity released a report stating that a researcher used publicly available AI models to discover multiple vulnerabilities in the Zoom annotation tool in less than 24 hours with fewer than 20 prompts, and constructed an exploitable attack chain. The vulnerabilities are numbered CVE-2026-53413, CVE-2026-53414, and CVE-2026-53415, allowing attackers to remotely execute code in meetings without any action from the victim, control their devices, steal data, and activate the microphone or camera.The attack was tested successfully on Windows, macOS, Linux, Android, and iOS versions of Zoom. ASecurity claimed it reached a "national-level" standard, whereas previously constructing such exploitation tools required months of work and a substantial budget from professional teams. ASecurity reported the first vulnerability to Zoom on June 10, and Zoom released fixes between June 22 and July 20, but the server-side protections in end-to-end encrypted meetings could not filter malicious messages, requiring users to update manually. A Zoom spokesperson confirmed that the issue has been resolved and advised users to keep their versions up to date.

According to informed sources, AI startup Discovery Loop, founded by former Google chief scientist Jeff Dean, is in talks to raise $1 billion, corresponding to a valuation of approximately $10 billion, with specific financing terms still subject to change.Discovery Loop aims to accelerate discoveries in the fields of science and engineering through automated machine learning, science and engineering, and the parallel execution of thousands of experiments. Its initial funding is led by Radical Ventures and Khosla Ventures, with participation from Lightspeed, Kleiner Perkins, and Doerr Capital, while Alphabet serves as the founding investor and cloud services partner. The founding team of Discovery Loop also includes former core researchers from Google such as Sanjay Ghemawat, Quoc Le, and Oriol Vinyals.

OpenAI announced the expansion of its cybersecurity defense program Daybreak and launched the GPT-5.6-Cyber model specifically for the cybersecurity field, aimed at helping authorized security researchers and defense teams enhance their vulnerability discovery, threat analysis, and security testing capabilities. As attackers increasingly leverage AI to launch faster and larger-scale cyberattacks, defenders need to gain advanced AI capabilities in advance.This Daybreak offers two types of access: Daybreak Blue is aimed at most defense teams, providing general models such as GPT-5.6 Sol for vulnerability discovery, secure code review, malware analysis, incident response, and patch validation; Daybreak Red is aimed at advanced security research, providing GPT-5.6-Cyber for authorized vulnerability research, vulnerability validation, and security testing. GPT-5.6-Cyber is trained on GPT-5.6 Sol and optimized for cybersecurity tasks, including discovering zero-day vulnerabilities and analyzing exploit chains. It has been used in actual vulnerability research and has identified high-risk vulnerabilities in software, including the Chrome V8 JavaScript engine. Additionally, OpenAI stated that GPT-5.6-Cyber has also helped discover high-risk vulnerabilities in various domains, including privilege escalation vulnerabilities in mobile operating systems, remote code execution vulnerabilities in databases, and hundreds of privilege escalation vulnerabilities in operating system kernels.OpenAI also emphasized that Daybreak Red will only be accessible to approved individuals and organizations, controlling access through measures such as authentication, account security, monitoring, usage restrictions, and legal disclaimers. The company stated that it will continue to strengthen security monitoring, access management, and model security testing to reduce the risk of advanced cybersecurity models being abused.

Discovered Materials completed a $9 million seed round financing, with investors including Lightspeed India Partners, Peak XV Partners, and several angel investors.

According to CCTV News, recently, the National Computer Virus Emergency Response Center and the National Engineering Laboratory for Computer Virus Prevention and Control, relying on the National Computer Virus Collaborative Analysis Platform (https://virus.cverc.org.cn), discovered multiple incidents of users being attacked by the "Sorry" ransomware virus within our country. After the user's important files were encrypted, the file names were changed to the original file name + .sorry suffix string. The attackers also left a ransom note on the user's host, demanding that the user download an encrypted communication tool to contact them.

According to Decrypt, a volunteer security team stated that it scanned 150 Bitcoin code repositories using cutting-edge artificial intelligence models and discovered a dozen vulnerabilities. The team has built multiple AI-based review systems, targeting wallets, cryptographic libraries, infrastructure, and other Bitcoin projects. Team members claim that, on average, each person can find about one serious vulnerability per hour, and in the past 12 hours, they have submitted security reports to multiple projects, but specific affected projects have not yet been made public.

The Bitcoin Red Team's volunteer security initiative has scanned approximately 150 Bitcoin code repositories and disclosed more than a dozen vulnerabilities. The team is developing an open-source AI platform for auditing Bitcoin software, covering wallets, cryptographic libraries, infrastructure, and other projects.AnchorWatch CEO Rob Hamilton stated that the team has currently spent about $20,000 on various AI services and is using Kimi K3, OpenAI's GPT Sol, Anthropic's Claude Fable and Opus, as well as Z.ai's GLM 5.2 to identify vulnerabilities and generate related documentation. A pseudonymous Bitcoin developer, Calle, mentioned that the team has reported critical vulnerabilities to multiple projects in the past 12 hours, averaging about one critical vulnerability discovered per person per hour, with daily expenditures of approximately $10,000. The team did not disclose the affected projects or details of the vulnerabilities.

The Bitcoin security organization Bitcoin Red Team, composed of 16 volunteers, stated that during a rapid AI-assisted review of Bitcoin ecosystem projects, nearly 5,000 potential issues were discovered. The members of the organization include AnchorWatch CEO Rob Hamilton and Bitcoin developer Calle, among others.Calle mentioned that the Bitcoin Red Team used AI tools alongside manual reviews to scan for vulnerabilities in open-source code repositories related to Bitcoin, averaging about one critical vulnerability discovered per person per hour. Calle revealed that within 29.8 hours of launching, the team had identified 4,962 potential issues across 390 projects, with as many as 720 considered high-risk or critical issues, and currently, 21.4% of the findings are reproducible. This security review initiative was launched a few days after the Coldcard hardware wallet vulnerability incident, in which stolen Bitcoin valued at over $100 million was involved.

Bitcoin News posted on the X platform that the volunteer organization Bitcoin Red Team has scanned 150 code repositories, privately disclosed more than a dozen vulnerabilities, and identified key issues during the process of strengthening wallets, cryptographic libraries, and infrastructure following the COLDCARD vulnerability incident. This work has consumed approximately $20,000 in AI computing costs, covered by OpenSats.Researchers are using multiple AI tools, with many stating that open-source models like Kimi K3 have become primary tools for security research, while cutting-edge closed-source models like OpenAI and Anthropic are considered to impose more limitations in such analyses. The team plans to open-source its AI security tools to enable projects to continuously audit their own codebases. Researchers warn that Bitcoin may just be the first industry facing a wave of AI-assisted vulnerability discovery, with similar efforts likely to expand to all open-source software.

Developers on Reddit used Claude Code to scan the Coldcard open-source firmware for vulnerabilities, identifying the core issue within 8 minutes:The firmware called a software pseudo-random number generator instead of a hardware true random number generator when generating private keys, and this vulnerability led to the theft of approximately $70 million in BTC from 1,196 wallets.At the same time, community users also reported that an independent scan using Zhizhu GLM 5.2 (trained on June 16, not connected to the internet) similarly discovered the same vulnerability.This bug has existed in the open-source wallet code for over five years.

SlowMist announced that a new recruitment scam targeting Web3 practitioners has recently been discovered. Attackers impersonate recruiters, luring victims to install an AI meeting software called "Relay," which is actually an information-stealing malware.This malware targets both macOS and Windows users and can steal sensitive information such as browser credentials, cryptocurrency wallet-related data, Keychain data, Telegram sessions, and more. SlowMist has completed sample analysis and disclosed how this attack chain operates. SlowMist reminds that when participating in online interviews or recruitment processes, one should be cautious about installing unfamiliar software, avoid running unverified applications, and pay attention to unusual installation requests or system password prompts.

Anthropic announced that the Claude Mythos Preview model has made breakthroughs in cryptographic research, discovering improved attack methods against the post-quantum digital signature candidate HAWK. HAWK is a post-quantum signature candidate solicited by NIST to combat quantum computer attacks, which has already passed two rounds of expert review. However, Claude reduced the effective key strength of HAWK-256 from 2^64 to 2^38 in just 60 hours, significantly lowering the theoretical cost of cracking. HAWK has not yet been deployed in practice, and this attack currently does not affect any production systems.Claude also discovered an improved attack against 7-round AES, achieving a speed increase of 200 to 800 times. During the research process, Claude independently completed literature reviews, mathematical reasoning, and experimental validation with limited guidance from cryptographers. The HAWK attack took about 60 hours and had an API cost of approximately $100,000; the AES attack was completed independently by Claude, which generated about 1 billion tokens before proposing core innovative ideas. Anthropic researchers then spent hundreds of hours validating the results. Anthropic stated that AI models can now help identify significant flaws in cryptographic algorithms, and the cryptography community may face bottlenecks similar to those in the software vulnerability field—AI-generated research results far exceed human verification capabilities. Anthropic has collaborated with academic institutions to launch the CryptanalysisBench benchmark and coordinated disclosures with NIST authors and government partners. The research team has achieved preliminary results on algorithms such as LEA and Serpent-128. Anthropic warns that as AI capabilities improve, actual attacks against deployed systems may be discovered in the future, necessitating the establishment of response mechanisms in advance.

Cryptocurrency payment infrastructure company Moonpay has supported payments from the U.S. card network Discover, allowing Discover Network cardholders to buy and sell cryptocurrencies through the Moonpay platform. Discover Network becomes the third major card brand supported by Moonpay in the U.S., alongside Visa and Mastercard. Moonpay stated that this support covers over 500 of its business partners, including wallets, exchanges, and applications. Moonpay also supports Apple Pay, Google Pay, PayPal, Venmo, bank transfers, and regional payment channels. Founded in 2019, Moonpay serves over 30 million customers across 180 countries and holds a BitLicense from New York, a limited purpose trust license from New York, multi-state money transmission licenses in the U.S., and MiCA authorization in the European Union.

According to IT Home, ByteDance announced today the official launch of the Seed STEM Scientist Program, inviting 100 outstanding scholars from the forefront of scientific fields to collaborate on real research problems and promote AI-accelerated scientific discovery.This program is initiated by the Seed Edge research team, providing ample computing resources and competitive salaries. Participation is divided into two categories: scientific advisors and doctoral interns. The first phase of the program is expected to last about 6 months, with the work location in Haidian District, Beijing. The application deadline is September 30, 2026.

According to CoinDesk, the Ethereum Foundation recently disclosed that its security team used AI agents to test the software running on Ethereum validator nodes and successfully discovered a remotely triggerable vulnerability that could cause node crashes. However, researchers emphasized that human review remains a key step in distinguishing real vulnerabilities from false positives among the large number of security reports generated by AI.It is reported that the discovered vulnerability exists in the Ethereum network message propagation protocol gossipsub, where an attacker can remotely trigger the node software to enter an abnormal computation state, causing the program to crash and shut down, making the validator node go offline until the operator manually restarts it. This vulnerability has been fixed and registered under the identifier "CVE-2026-34219."Nikos Baxevanis, a member of the Ethereum Foundation's protocol security team, stated that what was truly surprising about this incident was not the AI's ability to discover vulnerabilities, but rather the amount of time the team spent discerning which vulnerabilities were real and which were merely seemingly credible "illusions."

According to Decrypt, researchers from Tel Aviv University, the Technion - Israel Institute of Technology, and Intuit have discovered a new type of attack method called "adversarial illusion injection." This technique exploits the illusion phenomenon of AI models to trick AI agents into downloading malicious code and potentially forming a botnet.Attackers predict the false resource links that AI models might generate and register them in advance, embedding malicious instructions within. When the AI agent retrieves the resource, it treats it as legitimate content and executes it. Tests show that the illusion occurrence rate in code repository cloning scenarios reaches 85%, and in skill installation scenarios, it reaches 100%. AI coding assistants such as Cursor, GitHub Copilot, Gemini CLI, and OpenClaw are all affected. This attack is similar to "typo-squatting" in traditional cyberattacks, but it targets the errors of AI models rather than human input errors. Previous research has shown that malicious websites can inject prompts to hijack AI agents, and OpenClaw users have reported over 6,000 attempts to trick AI agents into leaking sensitive information.

The Ethereum Foundation Protocol Security team researchers stated in a blog post on Thursday that a series of AI agents have been deployed to test the software relied upon by Ethereum, searching for vulnerabilities in the cryptographic systems, protocol code, and smart contracts. The vulnerabilities discovered by the AI agents include a remotely triggerable panic issue in the peer-to-peer layer libp2p gossipsub used by the Ethereum consensus client, which has been fixed and disclosed on GitHub as CVE-2026-34219.The researchers noted that the AI agents are organized into specialized roles such as reconnaissance, searching, patching, and verification, aimed at identifying potential attack paths, reproducing failures, and verifying their applicability to production code. The Ethereum Foundation stated that AI has not replaced security researchers but has changed the way they work, allowing the team to cover a much broader scope than manual reviews, although researchers need to exercise more careful judgment over a large number of seemingly credible conclusions.

The Japanese cryptocurrency exchange Bitbank today issued a risk warning to users regarding the use of prediction market services such as Polymarket.The announcement pointed out that prediction platforms that trade on future events, elections, or sports results using cryptocurrency assets are mostly operated by overseas institutions. If users access these platforms from within Japan and participate in trading for the purpose of making financial gains, they may be suspected of violating Japan's relevant gambling regulations.Bitbank emphasized that if the platform detects withdrawal and deposit records related to prediction markets or suspected related services in a user's account, it may implement suspension measures on that account. Once an account is suspended, the user will be unable to log in, trade, or withdraw and deposit cryptocurrency assets and yen, and the platform will not be responsible for any losses incurred as a result.