比特币“红队”表示,人工智能正在核心项目中发现数百个关键漏洞。
Bitcoin 'Red Team' Says AI Is Finding 100s Of Critical Exploits Across Core Projects

原始链接: https://www.zerohedge.com/crypto/bitcoin-red-team-says-ai-finding-100s-critical-exploits-across-core-projects

由 AnchorWatch 首席执行官 Rob Hamilton 领导的一项志愿者安全计划,正在利用前沿人工智能模型主动识别比特币生态系统中的漏洞。通过部署 OpenAI 的 GPT、Anthropic 的 Claude 等模型,“比特币红队”已扫描了数百个代码库,旨在潜在漏洞被利用前将其发现。 其成果显著:在运行不到 30 小时的时间里,该计划在 390 个项目中标记了近 5,000 个潜在问题,其中超过 700 个被归类为高危或严重级别。尽管运营成本高昂——每天高达约 10,000 美元,但团队认为这项投入对于保护比特币核心基础设施至关重要。 这一计划凸显了加密货币行业中一个更广泛的趋势:人工智能正日益成为一把“双刃剑”。研究人员利用先进模型修复缺陷的同时,恶意攻击者也在以空前的速度利用人工智能发现漏洞。目前,团队尚未披露受影响的具体项目,而是专注于负责任的漏洞披露与修复工作。

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原文

Authored by Jason Nelson via Decrypto.co,

A volunteer security initiative says it used frontier AI models to scan 150 Bitcoin repositories and found more than a dozen vulnerabilities as developers increasingly use artificial intelligence to audit blockchains.

In a post on X earlier this week, AnchorWatch CEO Rob Hamilton said the group has spent about $20,000 on AI services while building a "Bitcoin red team" platform.

“We have been working around the clock, with ~$20,000 of spend up to this point across different services,” he wrote.

“Funding is secured, I appreciate all the gestures for donations but it is not necessary. The bill is taken care of.”

red team refers to cybersecurity professionals who test software from an attacker's perspective, probing for vulnerabilities before they can be exploited.

According to Hamilton, the Bitcoin red team uses Kimi K3 alongside OpenAI’s GPT Sol, Anthropic’s Claude Fable and Opus models, and Z.ai’s GLM 5.2 to identify vulnerabilities and generate supporting documentation.

“We also have been connected with OpenAI for some help so I could manage getting the Cyber Harness running as well,” he wrote.

“It's a much more expensive scan, but well worth it for load-bearing portions of the Bitcoin ecosystem and has already yielded good results.”

Pseudonymous Bitcoin developer Calle said the initiative has built multiple AI-powered review systems targeting wallets, cryptographic libraries, infrastructure, and other Bitcoin projects.

"We're averaging on the order of one critical exploit per hour per person,” Calle wrote on X.

We've reported critical vulnerabilities to several projects in the last 12 hours. Thankfully, this is a very expensive exercise. We're burning through $10,000 per day."

According to Calle, in the first 29.8 hours of its operation, its team has found 4,962 potential issues across 390 projects.

As many as 720 of them are considered high- or critical-level issues.

So far, 21.4% of findings have been able to be reproduced. 

The team did not disclose which projects were affected or provide details of the vulnerabilities.

The announcement comes as AI is playing a growing role in finding security flaws across the crypto industry.

Earlier this year, researchers using Anthropic's Claude Opus 4.8 uncovered a four-year-old flaw in Zcash that could have allowed attackers to create unlimited counterfeit ZEC. In August, Coinkite said it believes attackers used AI to identify the Coldcard wallet vulnerability, while Bitcoin bridge Boltz suspended its swap service after saying attackers were using AI to identify vulnerabilities faster than its team could patch them.

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