Attackers used “technical assessment” projects with repeatable naming conventions to blend in cloning and build workflows, retrieving loader scripts from remote infrastructure, and minimizing on-disk ...
UTSA: ~20% of AI-suggested packages don't exist. Slopsquatting could let attackers slip malicious libs into projects.
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
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