Search Results for "android pentesting framework"
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Showing 17 open source projects for "android pentesting framework"
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Scene Framework
Android Single Activity Framework compatible with Fragment
Scene appears to be a ByteDance-hosted project — though at first glance its name is generic, implying it may relate to “scenes,” “rendering,” “storyboarding,” or perhaps “event handling.” Given ByteDance’s broad portfolio, Scene could be an internal or external library for structuring application “scenes” (UI, media, game, or module-level) or orchestrating workflows in a modular fashion. The repository may aim to help developers manage complex state, transitions, or UI/navigation flows in... -
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Golang Telegram Bot
Telegram Bot API Go framework
Telegram Bot API Go framework. -
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whisper.cpp
Port of OpenAI's Whisper model in C/C++
whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples.... -
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Open-AutoGLM
An open phone agent model & framework
Open-AutoGLM is an open-source framework and model designed to empower autonomous mobile intelligent assistants by enabling AI agents to understand and interact with phone screens in a multimodal manner, blending vision and language capability to control real devices. It aims to create an “AI phone agent” that can perceive on-screen content, reason about user goals, and execute sequences of taps, swipes, and text input via automated device control interfaces like ADB, enabling hands-off... -
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firerpa LAMDA
The most powerful Android RPA agent framework
lamda is an Android RPA agent framework that provides visual remote desktop control and automation at scale, geared toward testing, automation validation, and device management. It exposes a clean UI to monitor and interact with connected devices and includes tooling to script actions reliably across apps and OS versions. The project emphasizes low-friction setup and powerful control primitives so teams can move from interactive validation to repeatable automation. -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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Open Vision Agents by Stream
Build Vision Agents quickly with any model or video provider
Open Vision Agents by Stream is an open source framework from Stream for building real time, multimodal AI agents that watch, listen, and respond to live video streams. It focuses on combining video understanding models, such as YOLO and Roboflow based detectors, with real time large language models like OpenAI Realtime and Gemini Live to create interactive experiences. The framework uses Stream’s ultra low latency edge network so agents can join sessions quickly and maintain very low audio and video latency while processing frames and generating responses. ... -
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nndeploy
An Easy-to-Use and High-Performance AI Deployment Framework
nndeploy is an open-source framework designed to simplify the deployment of artificial intelligence models across multiple hardware platforms and devices. The framework focuses on making it easier to transform trained AI models into production-ready applications that can run efficiently on desktops, mobile devices, servers, and edge computing hardware. Developers can use visual workflows to design and configure AI processing pipelines by connecting modular nodes that represent different... -
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CGraph
A general, three-party dependency-free, cross-platform
CGraph is a high-performance, cross-platform Directed Acyclic Graph (DAG) framework implemented in pure C++ with no third-party dependencies, designed for building complex task pipelines and parallel execution workflows. It allows developers to model computational processes as graph structures, where nodes represent tasks and edges define dependencies, enabling efficient scheduling and execution. The framework includes a pipeline system that supports sequential and parallel execution,... -
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AiToEarn
Let's use AI to Earn
AiToEarn is an open-source, AI-powered platform designed to help creators, brands, and businesses automate the entire content marketing lifecycle, from ideation and production to distribution and monetization. It aims to be a unified solution where users can generate content, tailor it for multiple platforms, and publish it across social networks with minimal manual effort. The project supports matrix publishing to major global platforms like TikTok, YouTube, Instagram, Facebook, Pinterest,... -
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MegEngine
Easy-to-use deep learning framework with 3 key features
MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. ... -
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AskUI Vision Agent
Enable AI to control your desktop, mobile and HMI devices
AskUI’s Vision Agent is an automation framework that allows you—and AI agents—to control real desktops, mobile devices, and HMI systems by perceiving the UI and performing actions like clicking, typing, scrolling, and drag-and-drop. It is designed for multi-platform compatibility and supports multiple AI models so you can tailor perception and decision-making to your workload. The repository presents a feature overview, sample media, and frequent release notes, which show ongoing... -
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mllm
Fast Multimodal LLM on Mobile Devices
mllm is an open-source inference engine designed to run multimodal large language models efficiently on mobile devices and edge computing environments. The framework focuses on delivering high-performance AI inference in resource-constrained systems such as smartphones, embedded hardware, and lightweight computing platforms. Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies... -
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MLC LLM
Universal LLM Deployment Engine with ML Compilation
...The system supports deployment on environments including Linux, macOS, Windows, iOS, Android, and web browsers while utilizing different acceleration technologies such as CUDA, Vulkan, Metal, and WebGPU. It also provides OpenAI-compatible APIs that allow developers to integrate locally deployed models into existing AI applications without major code changes. -
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pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new... -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning... -
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libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
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