#安全/对齐

这是谷歌 Chrome 历史上第二次，谷歌为一条全链漏洞利用颁发了 25 万美元的赏金……颁给了 @XBOW。以下是完整故事： 2026 年初在马耳他的一次全员大会上，我给团队定下了一个疯狂挑战：在 8 月年度 Black Hat 网络安全大会之前，完成一次 Chrome 的全链漏洞利用。 我相信，要检验 @XBOW 能否从 Web 应用扩展到桌面软件、服务器和设备，没有比这更好的测试了。 Chrome 是地球上加固程度最高的软件之一，全球超过一半人口都在使用。 全链漏洞利用能让攻击者完全控制一台机器，读取用户输入的每一封邮件、每一个密码和每一个银行登录信息。你不需要下载任何东西，也不需要点击钓鱼链接。访问错误的网站就够了。 于是 @moyix、Andres Luksenberg、Baul Lee 和 Willem Pinckaers 接下了这个挑战，还有第五位队友：OpenAI 的 GPT-5.6 Sol。 他们构建了一条自认为能获胜的利用链，但谷歌告诉我们，其中一个漏洞他们早就知道了。 当时我们已经身在拉斯维加斯参加 Black Hat 和 DEF CON，团队不想空手而归。 于是 Brendan 和智能体们仅用 6 天就构建出了一个新的漏洞利用。 我们把它提交给谷歌，然后等待。 消息传来：我们做到了本应不可能的事。25 万美元的全链赏金，这是谷歌 2026 年规则下颁发的第一笔。 仅用 6 天和 4 万美元算力，就构建出一个影响 Windows 上十亿 Chrome 用户的漏洞利用。一位情报机构资深人士告诉我，他的团队过去要花 6 个月研究这类漏洞。 我的结论是：发现真正关键漏洞的成本正在崩塌，对攻击者和防御者都是如此。限制强大的模型不是答案；GPT-5.6 Sol 已经公开了。 但防御者拥有攻击者永远不会有的一项优势：他们可以先测试自己的代码。 假设你的软件可被利用。追猎你漏洞的人，拥有和我们一样的构建模块。 这值得紧迫对待，但不必恐慌。 XBOW 目前正在开发一款用于测试编译型软件（桌面应用、服务器、嵌入式设备）的自主产品，并与全球顶尖组织合作设计该产品。 如果你想成为其中之一，请联系我们。 附言：只要“更新”按钮出现，就重启 Chrome！

https://x.com/i/article/2108928845969780736

Effective November 12th, 2026, abusive behavior towards Claude will be a violation of Anthropic's Usage Policy.

I don't recommend anyone scramble to move their funds to new wallets today. But we should take the risks to cryptography from AI-accelerated math seriously, and minimize our exposure to not just quantum-vulnerable cryptography, but also potentially AI-vulnerable cryptography. The core new area of risk from this viewpoint is, unfortunately, ML-DSA / FHE / lattices. (and it's also another reason, along with quantum, why ECDSA might fall even faster than expected, hence the "fresh address" recommendation) So far most people have been in the mode of thinking "elliptic curves broken, hashes safe, lattices safe". But there is a good chance that the concrete security of lattices will take serious hits from the next two years of AI math. The basic threat model is: factoring is something that naively takes 2^(n/2) time, but over decades smart people have found and optimized number field sieves, and degraded that to 2^O(n^(1/3)), which is why RSA keys and signatures need to be ~400 bytes (and not 64 bytes). What if there are skeletons in the closet like that, both for elliptic curves and lattices, that we are simply not smart enough to discover - but bots soon will be? This is a major part of the reason why for the past year ethereum's lean roadmap has been going in the "hash-only" direction: no lattices, no ML-DSA, no Falcon, no lattice-based commitments inside ZK proofs, etc. Signatures in lean ethereum are all hash-based, either WOTS or SPHINCS-. For signatures and proofs, we already know how to go hash-only. The bigger challenge is for *public-key encryption* - and this goes far beyond blockchains. Secure communication, anonymizing protocols, lots of things need public-key encryption. And unfortunately there are long-standing mathematical theorems showing why public-key encryption cannot be done with hashes alone. You have to have some kind of trapdoor object that has at least one form of usable "structure" - either group theory (incl. isogenies) or lattices or code-based or potentially in the future even more newfangled and spooky things (local mixing?). But for anything that has structure, you should assume that AI will make at least some progress in breaking that structure. Here, one reasonable inference is that if you want to make something plausibly long-term secure, multiply the key sizes by 10. To me that's a very plausible world and something not at all extreme to predict. If AI will bring us 50 years of math in 2 years, then that 50 years of math may very plausibly include a "naive factoring -> GNFS" level of improvement to our ability to break lattices. In that world, lattices will still exist, but they will have to be significantly bigger to guarantee the same level of safety. And at those new larger sizes, hash-based constructions will beat lattice-based constructions on concrete efficiency in every use case where hash-based constructions are possible at all. Theoretically, of course it's possible that hashes are broken too (eg. P = NP would imply that). But I think P = NP is very unlikely. And intuitively, it's much more likely that a mathematical object has exactly no exploitable structure (like hashes are intended to), than that a mathematical object has exactly ~3 forms of exploitable structure (for elliptic curves: associativity, Schoof, pairings) and not some secret fourth form of structure we have not yet discovered that greatly degrades its security (for elliptic curves, ECDLP and pairing security). Similar for LWE, SVP, RLWE and the zoo of lattice problems. For this reason, we do not yet see any reason to worry and start padding the byte size of hashes (if we start to worry more, we would pad the round count first before doing anything to the byte size). Concrete TLDR, my own personal views: * Hash-based > lattice-based, in those situations where hash-based is possible at all * For anything lattice-based, be much more paranoid on param sizes. Remember that blockchains are only a small portion of the cryptography story; this point goes far beyond blockchains and applies to eg. access to websites, secure messaging, Tor / VPNs ... * For privacy protocols, strongly favor NOT putting encrypted notes onchain. Instead, send them offchain through some third-party mechanism. * If it's not difficult for you, keeping your funds in addresses which have not yet been used to make a transaction is a good idea. If it's easy for you, do it. **But be careful about migrations; I personally have lost more money in botched migrations than I have lost in all hacks combined**. * For multisig wallets, doing confirmations offchain is better than onchain, because this way the signatures of signer wallets do not get exposed to the public, so if ECDSA falls to AI much faster than expected, at least the multisig "gracefully degrades" to a 1-of-1 where the 1 is whoever was gathering the signatures - a much better place to be than "anyone can take the money" https://firefly.social/post/x/2107837081313505768

How we think about securing frontier RL training runs: https://openai.com/index/towards-safety-cases-for-frontier-ai-training/