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3 takeaways from the Ultralytics AI Python library hack [Video]

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AI Behavioral Targeting

The Ultralytics AI library hack points to critical vulnerabilities in the Python ecosystem—but not where you might think. Here’s what developers need to know.

Credit: Who is Danny – Shutterstock.com

When attackers compromised Ultralytics YOLO, a popular real-time object detection machine-learning package for Python, most assumed the Python Package Index, or PyPI, must be the point of failure. That made sense because the tampered software artifact was first found on PyPI. Moreover, the Python software repository has become a major attack vector for one of the software world’s most popular languages.

But it turned out the compromised PyPI package was just a symptom and the real exploit lay elsewhere—a sophisticated and daring compromise of a common GitHub build mechanism. Now that the dust has started to settle, it’s a good time to consider the three big takeaways from the Ultralytics AI library hack.

Python’s own supply chain wasn’t the point of compromise

Most developers are rightly aware of PyPI as a compromise …

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