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Anthropic Mythos AI So Powerful It Found A Serious Bug In Apple Software

Anthropic’s Mythos has been making headlines since the day it was launched. The AI tool can analyse and find hidden critical software flaws in the software. The AI system has reportedly found major security weaknesses in Apple’s macOS system, raising concerns about the AI-led cyberattacks. As per The Wall Street Journal, researchers from Palo Alto discovered the flaws after testing the AI tool and later shared their findings directly with Apple. This issue became alarming because AI was able to combine several bugs and potentially gain deep access to Mac computers.

How Mythos Managed To Break Through macOS Security
Experts believe that Mythos did not depend on a single software error. Rather, it carried out what experts describe as a ‘chained attack.’ This tool reportedly detected two different minor flaws hidden inside macOS and linked them together to create a much larger security breach. By combining bugs, the AI model was able to interfere with the computer’s memory and highlight protected areas of the device.

AI And Humans Worked Together

Despite the breakthrough, researchers clarified that Mythos did not act completely on its own. The test involved collaboration between the AI system and experienced cybersecurity professionals.
Experts explained that the AI was extremely effective at scanning huge amounts of code and spotting hidden weaknesses quickly. However, human experts were still needed to guide the process and carry out the final stages of the attack simulation.
The findings have added to growing fears that AI-powered hacking tools could become a major cybersecurity threat in the near future. Recently, Google also claimed it had stopped an AI-supported hacking attempt.

Apple Reviewing The Findings

Apple has confirmed that it is reviewing the information shared by the researchers. In a statement quoted by The Wall Street Journal, the company said security remains one of its top priorities and that it takes reports about possible vulnerabilities seriously.

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