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Source channel @githubtrending · Post #14659 · May 1

#cplusplus#arm#convolution#deep_learning#embedded_devices#llm#machine_learning#ml#mnn#transformer#vulkan#winograd_algorithm MNN is a lightweight and efficient deep learning framework that helps run AI models on mobile devices and other small devices. It supports many types of AI models and can handle tasks like image recognition and language processing quickly and locally on your device. This means you can use AI features without needing to send data to the cloud, which improves privacy and speed. MNN is used in many apps, including those from Alibaba, and supports various platforms like Android and iOS. It also helps reduce the size of AI models, making them faster and more efficient. https://github.com/alibaba/MNN

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Libreware

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

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⁭#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

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