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Source channel @githubtrending · Post #14877 · Jun 28

#python#bounty#bugbounty#bypass#cheatsheet#enumeration#hacking#hacktoberfest#methodology#payload#payloads#penetration_testing#pentest#privilege_escalation#redteam#security#vulnerability#web_application Payloads All The Things is a comprehensive collection of useful payloads and bypass techniques for web application security testing and penetration testing. It offers detailed documentation for each vulnerability, including how to exploit it and ready-to-use payloads, plus files for tools like Burp Intruder. You can contribute your own payloads or improvements, making it a collaborative resource. It also links to related projects for internal network and hardware pentesting, and provides learning resources like books and videos. Using this resource helps you efficiently find and test security weaknesses in web applications, improving your pentesting effectiveness and knowledge. https://github.com/swisskyrepo/PayloadsAllTheThings

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@githubtrending · Post #15295 · 11/11/2025, 05:00 PM

#python#ai#faiss#gpt_oss#langchain#llama_index#llm#localstorage#offline_first#ollama#privacy#python#rag#retrieval_augmented_generation#vector_database#vector_search#vectors LEANN is a tiny, powerful vector database that lets you turn your laptop into a personal AI assistant capable of searching millions of documents using 97% less storage than traditional systems without losing accuracy. It works by storing a compact graph and computing embeddings only when needed, saving huge space and keeping your data private on your device. You can search your files, emails, browser history, chat logs, live data from platforms like Slack and Twitter, and even codebases—all locally without cloud costs. This means fast, private, and efficient AI-powered search and retrieval on your own laptop. https://github.com/yichuan-w/LEANN

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@githubtrending · Post #15168 · 09/25/2025, 12:30 PM

#python#ai#context#embedded#faiss#knowledge_base#knowledge_graph#llm#machine_learning#memory#nlp#offline_first#opencv#python#rag#retrieval_augmented_generation#semantic_search#vector_database#video_processing Memvid lets you store millions of text pieces inside a single MP4 video file using QR codes, making your data 50-100 times smaller than usual databases. You can search this video instantly in under 100 milliseconds without needing servers or internet after setup. It works offline, is easy to use with simple Python code, and supports PDFs and chat with your data. The upcoming version 2 will add features like continuous memory updates, shareable capsules, fast local caching, and better video compression, making your AI memory smarter, faster, and more flexible. This means you get a powerful, portable, and efficient way to manage and search huge knowledge bases quickly and easily. https://github.com/Olow304/memvid