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Source channel @githubtrending · Post #14627 · Apr 24

#jupyter_notebook DINOv2 is a powerful AI model from Meta AI that learns to understand images without needing labeled data, using self-supervised learning. It was trained on 142 million images and creates strong visual features that work well for many tasks like image classification, depth estimation, and segmentation without extra fine-tuning. You can use its pretrained models easily with simple classifiers, saving time and effort. DINOv2 is efficient, scalable, and performs better than many other models, making it great for building versatile computer vision applications quickly and accurately. It’s open-source and ready to use with PyTorch. https://github.com/facebookresearch/dinov2

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Libreware

@libreware · Post #1262 · 03/28/2024, 03:59 PM

#Bluetooth#vulnerability allows unauthorized user to record & play audio on Bluetooth speaker via #BlueSpy Prevention section explains how you can check if your Bluetooth LE speakers/headsets are vulnerable to this attack using nRF Connect app https://www.mobile-hacker.com/2024/03/22/bluetooth-vulnerability-allows-unauthorized-user-to-record-and-play-audio-on-bluetooth-speakers/ #BlueDucky automates exploitation of Bluetooth pairing vulnerability that leads to 0-click code execution ▪️automatically scans for devices ▪️store MAC addresses of devices that are no longer visible but have enabled Bluetooth ▪️uses Rubber Ducky payloads https://www.mobile-hacker.com/2024/03/26/blueducky-automates-exploitation-of-bluetooth-pairing-vulnerability-that-leads-to-0-click-code-execution/ Demonstration of using BlueDucky to exploit 0-click Bluetooth vulnerability of unpatched Android smartphone (CVE-2023-45866) Exploit was triggered by Raspberry Pi 4 and then by Android running NetHunter https://youtu.be/GOGW7U1f2RA @androidMalware