Anthropic Finds 22 Firefox Vulnerabilities Using Claude Opus 4.6 AI Model
嗯,用户让我帮忙总结一篇文章的内容,控制在100字以内,而且不需要特定的开头。首先,我需要快速阅读并理解文章的主要内容。 文章主要讲的是Anthropic公司与Mozilla合作,在Firefox浏览器中发现了22个新的安全漏洞。其中14个是高危的,7个中危,1个低危。这些漏洞已经在Firefox 148版本中修复了大部分,剩下的会在未来的版本中解决。 Anthropic使用他们的Claude Opus 4.6大型语言模型来检测这些漏洞,特别是发现了用后释放(use-after-free)的bug。模型在短时间内扫描了近6000个C++文件,并提交了112份报告。虽然AI在开发 exploits 方面的成功率不高,但显示出AI在安全检测中的潜力。 此外,Mozilla提到这种AI辅助的方法发现了其他90个漏洞,大多数已经修复。这表明结合传统工程方法和新分析工具能有效提升安全性。 总结的时候要抓住关键点:发现漏洞的数量、分类、修复情况、AI的作用以及成功案例。同时要注意字数限制,确保简洁明了。 </think> Anthropic与Mozilla合作发现Firefox浏览器22个安全漏洞,其中14个高危、7个中危、1个低危,并已修复大部分。利用Claude Opus 4.6模型扫描近6000个C++文件,检测到多个严重问题并生成112份报告。尽管AI在开发 exploits 方面成功率有限,但显示其在安全检测中的潜力。 2026-3-7 11:21:0 Author: thehackernews.com(查看原文) 阅读量:16 收藏

Browser Security / Artificial Intelligence

Anthropic on Friday said it discovered 22 new security vulnerabilities in the Firefox web browser as part of a security partnership with Mozilla.

Of these, 14 have been classified as high, seven have been classified as moderate, and one has been rated low in severity. The issues were addressed in Firefox 148, released late last month. The vulnerabilities were identified over a two-week period in January 2026.

The artificial intelligence (AI) company said the number of high-severity bugs identified by its Claude Opus 4.6 large language model (LLM) represents "almost a fifth" of all high-severity vulnerabilities that were patched in Firefox in 2025.

Anthropic said the LLM detected a use-after-free bug in the browser's JavaScript after "just" 20 minutes of exploration, which was then validated by a human researcher in a virtualized environment to rule out the possibility of a false positive.

"By the end of this effort, we had scanned nearly 6,000 C++ files and submitted a total of 112 unique reports, including the high- and moderate-severity vulnerabilities mentioned above," the company said. "Most issues have been fixed in Firefox 148, with the remainder to be fixed in upcoming releases."

The AI upstart said it also fed its Claude model access to the entire list of vulnerabilities submitted to Mozilla and tasked the AI tool with developing a practical exploit for them.

Despite carrying out the test several hundred times and spending about $4,000 in API credits, the company said Claude Opus 4.6 was able to turn the security defect into an exploit only in two cases.

This behavior, the company added, signaled two important aspects: the cost of identifying vulnerabilities is cheaper than creating an exploit for them, and the model is better at finding issues than at exploiting them.

"However, the fact that Claude could succeed at automatically developing a crude browser exploit, even if only in a few cases, is concerning," Anthropic emphasized, adding the exploits only worked within the confines of its testing environment, which has had some security features like sandboxing intentionally stripped off.

A crucial component incorporated into the process is a task verifier to determine if the exploit actually works, giving the tool real-time feedback as it explores the codebase in question and allowing it to iterate its results until a successful exploit is devised.

One such exploit Claude wrote was for CVE-2026-2796 (CVSS score: 9.8), which has been described as a just-in-time (JIT) miscompilation in the JavaScript WebAssembly component.

The disclosure comes weeks after the company released Claude Code Security in a limited research preview as a way to fix vulnerabilities using an AI agent.

"We can't guarantee that all agent-generated patches that pass these tests are good enough to merge immediately," Anthropic said. "But task verifiers give us increased confidence that the produced patch will fix the specific vulnerability while preserving program functionality—and therefore achieve what's considered to be the minimum requirement for a plausible patch."

Mozilla, in a coordinated announcement, said the AI-assisted approach has discovered 90 other bugs, most of which have been fixed. These consisted of assertion failures that overlapped with issues traditionally found through fuzzing and distinct classes of logic errors that the fuzzers failed to catch.

"The scale of findings reflects the power of combining rigorous engineering with new analysis tools for continuous improvement," the browser maker said. "We view this as clear evidence that large-scale, AI-assisted analysis is a powerful new addition to security engineers' toolbox."

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文章来源: https://thehackernews.com/2026/03/anthropic-finds-22-firefox.html
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