Search Results for "artificial intelligence pentesting" - Page 61
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Showing 3035 open source projects for "artificial intelligence pentesting"
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Robyn
Experimental, AI/ML-powered and open sourced Marketing Mix Modeling
Robyn is an open-source, AI/ML-powered Marketing Mix Modeling (MMM) toolkit developed by Meta Marketing Science under the “facebookexperimental” GitHub umbrella. Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of... -
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Step1X-3D
High-Fidelity and Controllable Generation of Textured 3D Assets
Step1X-3D is an open-source framework for generating high-fidelity textured 3D assets from scratch — both their geometry and surface textures — using modern generative AI techniques. It combines a hybrid architecture: a geometry generation stage using a VAE-DiT model to output a watertight 3D representation (e.g. TSDF surface), and a texture synthesis stage that conditions on geometry and optionally reference input (or prompts) to produce view-consistent textures using a diffusion-based... -
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Step-Audio 2
Multi-modal large language model designed for audio understanding
Step-Audio2 is an advanced, end-to-end multimodal large language model designed for high-fidelity audio understanding and natural speech conversation: unlike many pipelines that separate speech recognition, processing, and synthesis, Step-Audio2 processes raw audio, reasons about semantic and paralinguistic content (like emotion, speaker characteristics, non-verbal cues), and can generate contextually appropriate responses — including potentially generating or transforming audio output. It... -
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VideoChat
Real-time voice interactive digital human
VideoChat is a real-time voice-interactive “digital human” system that combines automatic speech recognition, large language models, text-to-speech, and talking-head generation into a single conversational pipeline. It supports both pure end-to-end voice solutions based on multimodal large language models (GLM-4-Voice feeding directly into talking-head generation) and a more traditional cascaded pipeline using ASR → LLM → TTS → talking head. It is built as a Gradio Python demo, exposing a... -
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MiniMax-MCP
Official MiniMax Model Context Protocol (MCP) server
MiniMax-MCP is the official Model Context Protocol (MCP) server for accessing MiniMax’s multimodal generative APIs from MCP-compatible clients. It acts as a bridge between tools like Claude Desktop, Cursor, Windsurf, OpenAI Agents, and the MiniMax platform, exposing capabilities such as text-to-speech, voice cloning, image generation, text-to-image, video generation, image-to-video, text-to-video, and music generation. The server is written in Python and distributed under the MIT license,... -
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files-to-prompt
Concatenate a directory full of files into a single prompt
files-to-prompt is a Python command-line tool that takes one or more files or entire directories and concatenates their contents into a single, LLM-friendly prompt. It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It... -
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mlforecast
Scalable machine learning for time series forecasting
mlforecast is a time-series forecasting framework built around machine-learning models, designed to make forecasting both efficient and scalable. It lets you apply any regressor that follows the typical scikit-learn API, for example, gradient-boosted trees or linear models, to time-series data by automating much of the messy feature engineering and data preparation. Instead of writing custom code to build lagged features, rolling statistics, and date-based predictors, mlforecast generates... -
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HunterX AI-Assisted Offensive Security Engine Discover. Validate. Prove. Report. HunterX is not merely a vulnerability scanner. It is an open-source, AI-assisted offensive security engine for planning and running authorized security-assessment missions. It combines reconnaissance, security-tool orchestration, AI-assisted reasoning, hypothesis-driven investigation, vulnerability validation, evidence collection, proof / PoC engineering, replay / reproducibility, correlation, impact...
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reverse-SynthID
Reverse engineering Gemini's SynthID detection
Reverse-SynthID is a research-focused project that analyzes and reverse-engineers Google’s SynthID watermarking system used in AI-generated images. It leverages signal processing and spectral analysis techniques to identify hidden watermark patterns without access to proprietary encoding methods. The project introduces a multi-resolution “SpectralCodebook” that maps watermark characteristics across different image sizes. Using this approach, it can detect SynthID watermarks with high... -
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NLP
Open source NLP guide with models, methods, and real use cases
NLP is an open source introductory resource for natural language processing, presented as a continuously updated book hosted on GitHub. It explains how machines process and understand human language, combining theory with practical examples. Its covers core NLP concepts such as text representation, feature extraction, and model evaluation, alongside hands-on implementations using tools like Word2Vec, TF-IDF, and FastText. It also introduces topic modeling with LDA, keyword extraction... -
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autoMate
AI tool for automating desktop tasks via natural language input
autoMate is an AI-powered local automation tool designed to enable users to control and automate their computers using natural language instructions instead of traditional scripting or rule-based systems. It combines large language models with computer vision techniques to interpret user intent and understand on-screen content, allowing it to interact with graphical interfaces similarly to a human user. autoMate follows an observe-decide-act workflow, where it analyzes the screen, plans... -
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Text Embeddings Inference
High-performance inference server for text embeddings models API layer
Text Embeddings Inference is a high-performance server designed to serve text embedding models efficiently in production environments. It focuses on delivering fast and scalable embedding generation by leveraging optimized inference techniques and modern hardware acceleration. It is built to support transformer-based embedding models, making it suitable for tasks such as semantic search, clustering, and retrieval-augmented systems. It provides an API interface that allows developers to... -
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DeepWiki Open
AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories
DeepWiki Open is an open-source, AI-powered wiki generator that automatically creates fully navigable, richly structured wiki documentation for GitHub, GitLab, or Bitbucket repositories by combining code analysis, vector embeddings, retrieval-augmented generation (RAG), and visualization tools. Users can enter a repository URL and the system will clone the project, build semantic embeddings of its codebase, extract architecture and relationships, generate human-readable documentation, and... -
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Magika
Fast and accurate AI powered file content types detection
Magika is an AI-powered file-type detector that uses a compact deep-learning model to classify binary and textual files with high accuracy and very low latency. The model is engineered to be only a few megabytes and to run quickly even on CPU-only systems, making it practical for desktop apps, servers, and security pipelines. Magika ships as a command-line tool and a library, providing drop-in detection that improves on traditional “magic number” and heuristic approaches, especially for... -
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GR00T Whole-Body Control (WBC)
Welcome to GR00T Whole-Body Control (WBC)
GR00T Whole-Body Control is NVIDIA’s unified platform for training, evaluating, and deploying advanced humanoid robot controllers. It includes the decoupled controller used with GR00T N1.5 and N1.6, combining reinforcement learning for the lower body with inverse kinematics for the upper body. The GEAR-SONIC system learns a broad set of natural motor skills from large-scale human motion data through a unified tracking policy. Released Unitree G1 checkpoints support motion references,... -
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LoLLMs WEBUI
Local AI WebUI for running and managing large language models offlineA
lollms-webui is a locally hosted web interface designed to run and manage large language models without relying on external services. It provides users with a centralized environment to interact with multiple AI models, making it suitable for experimentation, development, and personal use. lollms-webui emphasizes offline capability, allowing users to maintain privacy and control over their data while still accessing advanced AI features. It integrates model management tools that help users... -
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Conversational Health Agents (CHA)
A Personalized LLM-powered Agent Frameworks
CHA, or Conversational Health Agents, is an open-source framework designed to build intelligent healthcare assistants powered by large language models and external data sources. The system enables developers to create personalized AI agents that can interact with users through natural language while performing multi-step reasoning and task execution. It integrates orchestration capabilities that allow the agent to gather information from APIs, knowledge bases, and external services in order... -
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nanochat
The best ChatGPT that $100 can buy
nanochat is a from-scratch, end-to-end “mini ChatGPT” that shows the entire path from raw text to a chatty web app in one small, dependency-lean codebase. The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. Its north star is approachability and... -
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nanoGPT
The simplest, fastest repository for training/finetuning models
NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare... -
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AI Infra
Understanding of AI Infra: Quantitative Analysis and System Design
AI Infra Book is an open-source technical book and companion repository focused on the infrastructure behind modern large language models. It approaches inference and training through quantitative analysis of hardware limits, data movement, model architecture, and distributed systems. The book contains twelve chapters supported by formulas, diagrams, experiments, and case studies. Companion tools help readers reproduce resource calculations and inspect the assumptions behind system-design... -
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MSA: Memory Sparse Attention
Trainable latent-memory framework for 100M-token contexts
MSA, or Memory Sparse Attention, is a research framework for scaling language-model memory to extremely long contexts. It replaces full attention over all tokens with sparse selection of compressed latent memory states. Document-wise rotary position encoding and top-k routing keep training and inference close to linear complexity. A tiered KV-cache design stores routing keys on GPU while larger content states can remain on CPU. Its Memory Parallel engine distributes scoring and transfers... -
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NeMo Automodel
Pytorch Distributed native training library for LLMs/VLMs
NeMo AutoModel is NVIDIA's open-source PyTorch Distributed training library for scaling LLM, VLM, diffusion, and retrieval-model training. Its DTensor-native SPMD approach lets the same training code scale from one GPU to large multi-node clusters by changing configuration. Hugging Face integration provides broad model compatibility without requiring format conversion. YAML recipes and CLI overrides keep experiments concise while preserving reproducibility. The library supports composable... -
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Human Writing
Make the Chinese written by AI read like a specific person speaking
Human Writing is an AI writing skill designed to make Chinese prose sound like it was written by a specific person rather than a generic language model. Before drafting, it checks whether enough factual or fictional material exists to support meaningful writing. For nonfiction, it emphasizes verified facts, numbers, quotations, and lived details, while fiction must still contain purposeful actions and causal progression. Each paragraph is expected to add new information instead of repeating... -
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Semantica
Graph-Native Infrastructure for Context and Accountable AI Systems
Semantica is an open-source graph-native infrastructure layer for building explainable and auditable AI systems. It ingests fragmented data, extracts meaningful entities and relationships, and transforms them into context and knowledge graphs. Deterministic reasoning, ontology management, provenance tracking, and decision records help explain how conclusions were reached. The platform can complement existing LLMs, vector databases, and agent frameworks rather than replacing them. It supports... -
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Gpt-Agreement-Payment
End-to-end protocol replay toolkit for ChatGPT Plus/Team/Pro sub
Gpt-Agreement-Payment is a research-oriented automation toolkit focused on subscription payment flows, protocol replay behavior, and anti-fraud mechanism analysis. It documents and implements controlled workflows around account setup, payment routing, runtime state storage, and operational monitoring. The project includes both command-line and web UI modes, with Docker and manual deployment options. It stores runtime output and logs in a local SQLite-backed structure for review and...
