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Source channel @githubtrending · Post #15601 · Apr 5

#yara#awesome_list#blueteam#blueteam_tools#cti#detection#detection_engineering#dfir#hacktools#incident_response#ioc#iocs#ir#ransomware#redteam#rmm#security#siem#soc#threat_hunting#threat_intelligence You can access comprehensive security detection lists and threat hunting resources that help identify malicious activity across your infrastructure. These curated collections include indicators like suspicious file hashes, domain names, IP addresses, and behavioral patterns organized by threat type—from ransomware and phishing to command-and-control servers and vulnerable drivers. By integrating these lists into your security tools like SIEM platforms and endpoint detection systems, you gain immediate visibility into known threats while learning detection methodologies through guides and YARA rules. This accelerates your ability to hunt for compromises, validate security controls, and stay current with emerging attack techniques without building detection logic from scratch. https://github.com/mthcht/awesome-lists

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@githubtrending · Post #15271 · 11/05/2025, 12:30 PM

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite