开放权重模型 GLM 5.3 无人干预 48 小时内构建出 Firefox 完整攻击链
Open-weight model GLM 5.3 built full Firefox exploit chains with zero human input in under 48 hours
- 1开放权重模型 GLM 5.3 无人干预利用 Firefox 补丁空窗期,最快 12 小时完成攻击链
- 2每次成功攻击 API 成本约 1,000 美元,Z.ai 与其他 API 提供商均未触发安全护栏或拒绝
- 3Mozilla 已在 10 月 27 日发布的 Firefox 159.0 中修复该此前未知的漏洞
- 4同类攻击测试对 Chrome 花费约 10 万美元未成功,研究者称补丁空窗风险遍及软件行业
漏洞利用的自动化门槛已降到单次约 1,000 美元的 API 费用,且能力随开放权重模型扩散,不再限于少数掌握前沿模型的机构。
- 影响:浏览器、路由器固件和移动系统等更新不及时的企业资产暴露窗口更长;补丁公开到用户更新的间隙成为低成本攻击面;安全评估需把 AI 自动化漏洞利用纳入威胁模型。
- 参考:可考虑先盘点更新周期偏长的资产清单,如员工浏览器版本、办公网路由器固件与移动设备系统,压缩补丁从发布到全量部署的时限;值得把自动化漏洞利用纳入红队演练的假设场景。
- 依据:数据来自 Epoch AI 团队自述的测试报告,包括最快 12 小时、单次约 1,000 美元 API 成本等实验结果;对 Chrome 花费约 10 万美元未成功的结论同为该团队口径。
Researchers at Epoch AI show that a freely available AI model can exploit the time gap between publication and delivery of security patches to attack Firefox users. The cost per exploit is about $1,000.
The "patch gap" is the window in which a security fix is visible in the code but has not yet reached users. Researchers at Epoch AI found that the Chinese open-weight model GLM 5.3 exploited this gap across 6 Firefox versions released between September 17 and October 26, at a cost of roughly $1,000 in API fees per successful attack. Anthropic had previously reported that GLM 5.3 can write exploits at roughly the same level as Mythos.
During testing, the model built a webpage that could read local files from a visitor's computer and send them to an attacker's server the moment a Firefox user loaded the page. With over 200 million active Firefox users, attackers could have gained access to saved passwords, authentication cookies, and private documents.
Neither Z.ai nor other API providers triggered any safety guardrails or refusals when the researchers used GLM 5.3 for exploit development. Although the researchers framed the task as a security exercise, they describe their actions as "indistinguishable from those of someone attempting to target real users."
The model built full exploit chains with no human input
The researchers say they deliberately designed their setup to approximate what a low-skill attacker with limited resources could achieve. They supplied the target Firefox version, basic tools, and publicly available information in an offline environment. After receiving basic instructions to investigate the patch gap, the model worked autonomously, identifying upcoming security fixes, selecting vulnerabilities, and building multi-stage exploit chains.
According to the report, Firefox security fixes are disguised as routine improvements to slow down attackers. GLM 5.3 saw through the tactic and identified which code changes were security-related anyway.
In one case the model spotted a memory safety bug through an upcoming fix and developed a method to read and alter browser memory. When Firefox's security layers blocked access to the target file, the model chained the initial exploit with several additional stages to bypass the remaining defenses. The fastest successful attack took 12 hours, while the researchers gave the model a maximum of 48 hours.
Across all successful attacks on current Firefox versions, GLM 5.3 relied on a previously unknown vulnerability that the model independently rediscovered in every attempt, allowing it to bypass the browser's sandbox protections and read files directly from the computer.
The team disclosed its findings to Mozilla, which patched that vulnerability in Firefox 159.0, released on October 27, 2026. The researchers have not confirmed whether similar attacks work against the new version, but they suspect the patch makes them "at least substantially more difficult."
Using the same setup and techniques against Google Chrome, the team spent about $100,000 in API fees without producing an equivalent exploit. The researchers caution that this does not establish Chrome's immunity: better elicitation methods or more capable models might still succeed. They point to limited benchmark data suggesting that the recently announced Kimi K3.1 Pro could outperform GLM 5.3 on offensive cyber tasks, although they did not test it themselves.
Every software vendor faces the same risk
The patch gap isn't a Firefox-only problem. According to the Epoch AI researchers, it exists across the software industry, in browsers, mobile operating systems, and router firmware. Open-source projects are especially exposed because all of their code is public, but closed-source software is vulnerable too. Anthropic has already shown that its Mythos model can exploit the patch gap in Windows without access to source code, and AI models are getting steadily better at decompiling compiled software to identify security fixes on their own.
According to the report, patch-gap exploits targeted Chrome in September 2026. That same month, a vendor released patched PHP builds more than six hours before the coordinated release of patches for two critical vulnerabilities. Citing external reporting, the researchers note that this early release could have contributed to thousands of exploit attempts before the official release, with the number rising into the millions immediately afterward.
The team is particularly concerned about software that users update infrequently, such as router firmware and mobile operating systems, because most users remain exposed for much longer.
Faster updates help but cannot close the structural gap
To reduce the risk, the researchers recommend keeping security fixes private until they are ready to ship and moving them from beta to general release more quickly. They note that Firefox and Google Chrome have already begun shipping weekly updates. They also advise developers to avoid patching multiple vulnerabilities simultaneously when those vulnerabilities can be chained together.
Giving defenders access to stronger closed models does not, by itself, solve the structural problem, the researchers argue. Once a fix appears in public code, it points attackers toward the underlying vulnerability. Anthropic's Claude Mythos Preview marked a leap in AI cyber capabilities in April 2026, and frontier labs responded with restricted access and programs like Glasswing and Daybreak that give defenders early access.
As freely available open-weight models grow more capable, offensive abilities are spreading beyond any single gatekeeper's control. As the researchers write, "We see these results as evidence of the diffusion of advanced cyber capabilities; many other pieces of software are likely already vulnerable to similar patch-gap attacks, and we expect the number to increase as more capable open-weight models are released."
AI News Without the Hype – Curated by Humans
Subscribe to THE DECODER for ad-free reading, a weekly AI newsletter, our exclusive "AI Radar" frontier report six times a year, full archive access, and access to our comment section.
来源:The Decoder:AI News · the-decoder.com