- Anthropic Claude Opus 4.6 Reveals 22 Firefox Security Flaws
- Mozilla confirmed 14 critical 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 harm.
In a new blog post, Anthropic said it teamed up with Mozilla researchers and over the course of a few weeks scanned nearly 6,000 C++ files using Claude Opus 4.6.
Opus 4.6 is the latest version of Anthropic’s most powerful large language model (LLM), which was released in early February 2026, and has been heralded as a must-have tool in every cyber defender’s arsenal, claiming it is “significantly better” at finding high-severity vulnerabilities.
The article continues below
Great success
After analyzing popular open source repositories and finding more than 500 bugs, Anthropic targeted Firefox, mostly because it is “both complex and one of the most well-tested and secure open source projects in the world.” In other words, it would really prove a point by finding a product that is generally considered great and safe.
The team ran the experiment for two weeks, and in that time frame, Opus 4.6 managed to find 22 vulnerabilities. Mozilla marked 14 of them as high. In total, Anthropic submitted a total of 112 unique reports, most of which were addressed in Firefox 148. The rest will be fixed in future releases, it said.
Anthropic calls this a huge success, saying that in two weeks, Opus 4.6 revealed about a fifth as many serious vulnerabilities as Mozilla fixed in all of 2025.
“AI makes it possible to detect serious security vulnerabilities at greatly accelerated speeds,” they said. Previously, Anthropic said that Opus 4.6 stood out for the way it found vulnerabilities “out of the box without task-specific tools, custom scaffolding or specialized prompts.”
It also added that unlike fuzzing, which is a standard vulnerability-hunting technique, Opus works by reasoning about the code “like a human researcher would,” meaning it looked at previous fixes to find similar bugs that weren’t fixed, discovered patterns that tend to cause problems, and understood the logic “well enough to know exactly what input would break it.”
The best antivirus for all budgets
Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews and opinions in your feeds. Be sure to click the Follow button!
And of course you can too follow TechRadar on TikTok for news, reviews, video unboxings, and get regular updates from us on WhatsApp also.
