- Anthropic Claude Opus 4.6 reveals 22 security vulnerabilities in Firefox
- Mozilla confirmed 14 high severity vulnerabilities fixed in Firefox 148
- AI model demonstrated accelerated, human-like vulnerability detection
Anthropic says it found nearly two dozen vulnerabilities in the latest version of Mozilla’s Firefox browser, including a few that could have caused serious damage.
In a new blog post, Anthropic said it partnered with Mozilla researchers and, within weeks, analyzed nearly 6,000 C++ files using Claude Opus 4.6.
Opus 4.6 is the latest version of Anthropic’s most powerful extended language model (LLM), released in early February 2026, and has been touted as a must-have tool in any cyber defender’s arsenal, claiming it is “notably better” at finding high-severity vulnerabilities.
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Major success
After analyzing popular open source repositories and discovering more than 500 vulnerabilities, Anthropic set its sights on Firefox, primarily because it is “both complex and one of the most tested and secure open source projects in the world.” In other words, he really wanted to prove something by finding a product that was generally considered bulky and safe.
The team conducted the experiment for two weeks, and during this period Opus 4.6 managed to find 22 vulnerabilities. Mozilla rated 14 of them as serious. In total, Anthropic submitted a total of 112 unique reports, most of which were processed in Firefox 148. The rest will be fixed in future releases, it was noted.
Anthropic considers this a major success, saying that Opus 4.6 discovered in two weeks about a fifth of the number of high-severity vulnerabilities that Mozilla patched in the year 2025.
“AI makes it possible to detect serious security vulnerabilities at greatly accelerated speeds,” they said. Earlier, Anthropic said Opus 4.6 stood out for how it detected vulnerabilities “out of the box, without task-specific tools, custom scaffolding, or specialized prompts.” »
He also added that unlike fuzzing, which is a standard vulnerability finding technique, Opus works by reasoning about code “like a human researcher would,” meaning it looked at past patches to find similar bugs that haven’t been fixed, spotting patterns that tend to cause problems, and understood the logic “well enough to know exactly what input would break it.”
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