The OWASP Top 10 for Large Language Model Applications is a standard awareness document for developers and web application security, providing practical, actionable, and concise security guidance for applications utilizing Large Language Model (LLM) technologies. The project aims to make application security visible and bridge the gap between general application security principles and the specific challenges posed by LLMs. It offers a comprehensive guide to navigate potential security risks in LLM applications, serving as a reference for both new and experienced developers and security professionals.

Fast-DLLM is a diffusion-based Large Language Model (LLM) inference acceleration framework that supports efficient inference for models like Dream and LLaDA. It offers fast inference support, multiple optimization strategies, code generation, evaluation capabilities, and an interactive chat interface. Key features include Key-Value Cache for Block-Wise Decoding, Confidence-Aware Parallel Decoding, and overall performance improvements. The project structure includes directories for Dream and LLaDA model-related code, with installation and usage instructions provided for using the LLaDA and Dream models.

Inspect AI is a framework developed by the UK AI Safety Institute for evaluating large language models. It offers various built-in components for prompt engineering, tool usage, multi-turn dialog, and model graded evaluations. Users can extend Inspect by adding new elicitation and scoring techniques through additional Python packages. The tool aims to provide a comprehensive solution for assessing the performance and safety of language models.

This repository provides a comprehensive collection of methodologies, tools, and step-by-step instructions for successful training of large language models (LLMs) and multi-modal models. It is a technical resource suitable for LLM/VLM training engineers and operators, containing numerous scripts and copy-n-paste commands to facilitate quick problem-solving. The repository is an ongoing compilation of the author's experiences training BLOOM-176B and IDEFICS-80B models, and currently focuses on the development and training of Retrieval Augmented Generation (RAG) models at Contextual.AI. The content is organized into six parts: Insights, Hardware, Orchestration, Training, Development, and Miscellaneous. It includes key comparison tables for high-end accelerators and networks, as well as shortcuts to frequently needed tools and guides. The repository is open to contributions and discussions, and is licensed under Attribution-ShareAlike 4.0 International.

CREDIT is an open software platform for training and deploying AI atmospheric prediction models. It offers fast models with flexible configuration options for input data and neural network architecture. The user-friendly interface enables quick setup and iteration. Developed by the MILES group and NSF National Center for Atmospheric Research, CREDIT combines advanced AI/ML with atmospheric science expertise. It provides a stable release with various models, training, and deployment options, with ongoing development. Detailed documentation is available for installation, training, deployment, config file interpretation, and API usage.

The Chinese LLM Benchmark is a continuous evaluation list of large models in CLiB, covering a wide range of commercial and open-source models from various companies and research institutions. It supports multidimensional evaluation of capabilities including classification, information extraction, reading comprehension, data analysis, Chinese encoding efficiency, and Chinese instruction compliance. The benchmark not only provides capability score rankings but also offers the original output results of all models for interested individuals to score and rank themselves.

paperless-gpt is a tool designed to generate accurate and meaningful document titles and tags for paperless-ngx using Large Language Models (LLMs). It supports multiple LLM providers, including OpenAI and Ollama. With paperless-gpt, you can streamline your document management by automatically suggesting appropriate titles and tags based on the content of your scanned documents. The tool offers features like multiple LLM support, customizable prompts, easy integration with paperless-ngx, user-friendly interface for reviewing and applying suggestions, dockerized deployment, automatic document processing, and an experimental OCR feature.

This repository extends the LLVM framework to generate code for use with AMD/Xilinx AI Engine processors. AI Engine processors are in-order, exposed-pipeline VLIW processors focused on application acceleration for AI, Machine Learning, and DSP applications. The repository adds LLVM support for specific features like non-power of 2 pointers, operand latencies, resource conflicts, negative operand latencies, slot assignment, relocations, code alignment restrictions, and register allocation. It includes support for Clang, LLD, binutils, Compiler-RT, and LLVM-LIBC.

The LLM Hosting Container repository provides Dockerfile and associated resources for building and hosting containers for large language models, specifically the HuggingFace Text Generation Inference (TGI) container. This tool allows users to easily deploy and manage large language models in a containerized environment, enabling efficient inference and deployment of language-based applications.

KTransformers is a flexible Python-centric framework designed to enhance the user's experience with advanced kernel optimizations and placement/parallelism strategies for Transformers. It provides a Transformers-compatible interface, RESTful APIs compliant with OpenAI and Ollama, and a simplified ChatGPT-like web UI. The framework aims to serve as a platform for experimenting with innovative LLM inference optimizations, focusing on local deployments constrained by limited resources and supporting heterogeneous computing opportunities like GPU/CPU offloading of quantized models.

OpenManus-RL is an open-source initiative focused on enhancing reasoning and decision-making capabilities of large language models (LLMs) through advanced reinforcement learning (RL)-based agent tuning. The project explores novel algorithmic structures, diverse reasoning paradigms, sophisticated reward strategies, and extensive benchmark environments. It aims to push the boundaries of agent reasoning and tool integration by integrating insights from leading RL tuning frameworks and continuously updating progress in a dynamic, live-streaming fashion.

Spec Workflow MCP is a Model Context Protocol (MCP) server that offers structured spec-driven development workflow tools for AI-assisted software development. It includes a real-time web dashboard and a VSCode extension for monitoring and managing project progress directly in the development environment. The tool supports sequential spec creation, real-time monitoring of specs and tasks, document management, archive system, task progress tracking, approval workflow, bug reporting, template system, and works on Windows, macOS, and Linux.

This repository contains a Geographic Information System (GIS) tool for performing Minimum Cumulative Path (MCP) analysis. The tool allows users to calculate the optimal path that minimizes cumulative cost between multiple locations on a map. It is particularly useful for urban planning, transportation route optimization, and environmental impact assessment. The tool supports various cost functions such as distance, travel time, and resource consumption, providing flexibility for different applications. Users can visualize the results on interactive maps and export the analysis outputs for further processing. The tool is implemented in Python and leverages popular GIS libraries such as GeoPandas and NetworkX for efficient spatial analysis.

Enterprise h2oGPTe - GenAI RAG is a repository containing code examples, notebooks, and benchmarks for the enterprise version of h2oGPTe, a powerful AI tool for generating text based on the RAG (Retrieval-Augmented Generation) architecture. The repository provides resources for leveraging h2oGPTe in enterprise settings, including implementation guides, performance evaluations, and best practices. Users can explore various applications of h2oGPTe in natural language processing tasks, such as text generation, content creation, and conversational AI.

This repository contains a collection of tools and scripts for generating code at the repository level. It provides a set of utilities to automate the process of creating and managing code across multiple files and directories. The tools included in this repository aim to improve code generation efficiency and maintainability by streamlining the development workflow. With a focus on enhancing productivity and reducing manual effort, this collection offers a variety of code generation options and customization features to suit different project requirements.

VLMEvalKit is an open-source evaluation toolkit of large vision-language models (LVLMs). It enables one-command evaluation of LVLMs on various benchmarks, without the heavy workload of data preparation under multiple repositories. In VLMEvalKit, we adopt generation-based evaluation for all LVLMs, and provide the evaluation results obtained with both exact matching and LLM-based answer extraction.

AI Services is a WordPress plugin that provides a centralized infrastructure for integrating AI capabilities into WordPress websites. It allows other plugins to utilize AI services via a common API, making it easier for developers to incorporate AI features without the need to implement separate API layers. The plugin supports various AI services such as Anthropic, Google, and OpenAI, enabling users to choose their preferred service. It simplifies the process of configuring AI APIs and unlocks AI capabilities for smaller plugins or features. The plugin is still in early stages, with ongoing enhancements and improvements planned to streamline API usage and enhance user experience.

The OWASP Top 10 for Large Language Model Applications is a standard awareness document for developers and web application security, providing practical, actionable, and concise security guidance for applications utilizing Large Language Model (LLM) technologies. The project aims to make application security visible and bridge the gap between general application security principles and the specific challenges posed by LLMs. It offers a comprehensive guide to navigate potential security risks in LLM applications, serving as a reference for both new and experienced developers and security professionals.

BESSER is a low-modeling low-code open-source platform funded by an FNR Pearl grant. It is built on B-UML, a Python-based interpretation of a 'Universal Modeling Language'. Users can specify their software application using B-UML and generate executable code for various applications like Django models or SQLAlchemy-compatible database structures. BESSER is available on PyPi and can be installed with pip. It supports popular Python IDEs and encourages contributions from the community.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

OWASP CycloneDX is a full-stack Bill of Materials (BOM) standard that provides advanced supply chain capabilities for cyber risk reduction. The specification supports various types of Bill of Materials including Software, Hardware, Machine Learning, Cryptography, Manufacturing, and Operations. It also includes support for Vulnerability Disclosure Reports, Vulnerability Exploitability eXchange, and CycloneDX Attestations. CycloneDX helps organizations accurately inventory all components used in software development to identify risks, enhance transparency, and enable rapid impact analysis. The project is managed by the CycloneDX Core Working Group under the OWASP Foundation and is supported by the global information security community.

The FuzzyAI Fuzzer is a powerful tool for automated LLM fuzzing, designed to help developers and security researchers identify jailbreaks and mitigate potential security vulnerabilities in their LLM APIs. It supports various fuzzing techniques, provides input generation capabilities, can be easily integrated into existing workflows, and offers an extensible architecture for customization and extension. The tool includes attacks like ArtPrompt, Taxonomy-based paraphrasing, Many-shot jailbreaking, Genetic algorithm, Hallucinations, DAN (Do Anything Now), WordGame, Crescendo, ActorAttack, Back To The Past, Please, Thought Experiment, and Default. It supports models from providers like Anthropic, OpenAI, Gemini, Azure, Bedrock, AI21, and Ollama, with the ability to add support for newer models. The tool also supports various cloud APIs and datasets for testing and experimentation.

CISO Assistant is a tool that helps organizations manage their cybersecurity posture and compliance. It provides a centralized platform for managing security controls, threats, and risks. CISO Assistant also includes a library of pre-built frameworks and tools to help organizations quickly and easily implement best practices.

Purple Llama is an umbrella project that aims to provide tools and evaluations to support responsible development and usage of generative AI models. It encompasses components for cybersecurity and input/output safeguards, with plans to expand in the future. The project emphasizes a collaborative approach, borrowing the concept of purple teaming from cybersecurity, to address potential risks and challenges posed by generative AI. Components within Purple Llama are licensed permissively to foster community collaboration and standardize the development of trust and safety tools for generative AI.

VPNFast is a lightweight and fast VPN service provider that offers secure and private internet access. With VPNFast, users can protect their online privacy, bypass geo-restrictions, and secure their internet connection from hackers and snoopers. The service provides high-speed servers in multiple locations worldwide, ensuring a reliable and seamless VPN experience for users. VPNFast is easy to use, with a user-friendly interface and simple setup process. Whether you're browsing the web, streaming content, or accessing sensitive information, VPNFast helps you stay safe and anonymous online.

Taranis AI is an advanced Open-Source Intelligence (OSINT) tool that leverages Artificial Intelligence to revolutionize information gathering and situational analysis. It navigates through diverse data sources like websites to collect unstructured news articles, utilizing Natural Language Processing and Artificial Intelligence to enhance content quality. Analysts then refine these AI-augmented articles into structured reports that serve as the foundation for deliverables such as PDF files, which are ultimately published.

Nightshade Antidote is an image forensics tool used to analyze digital images for signs of manipulation or forgery. It implements several common techniques used in image forensics including metadata analysis, copy-move forgery detection, frequency domain analysis, and JPEG compression artifacts analysis. The tool takes an input image, performs analysis using the above techniques, and outputs a report summarizing the findings.

This repository is a comprehensive collection of cybersecurity-related references, scripts, tools, code, and other resources. It is carefully curated and maintained by Omar Santos. The repository serves as a supplemental material provider to several books, video courses, and live training created by Omar Santos. It encompasses over 10,000 references that are instrumental for both offensive and defensive security professionals in honing their skills.

AIMr is an AI aimbot tool written in Python that leverages modern technologies to achieve an undetected system with a pleasing appearance. It works on any game that uses human-shaped models. To optimize its performance, users should build OpenCV with CUDA. For Valorant, additional perks in the Discord and an Arduino Leonardo R3 are required.

Admyral is an open-source Cybersecurity Automation & Investigation Assistant that provides a unified console for investigations and incident handling, workflow automation creation, automatic alert investigation, and next step suggestions for analysts. It aims to tackle alert fatigue and automate security workflows effectively by offering features like workflow actions, AI actions, case management, alert handling, and more. Admyral combines security automation and case management to streamline incident response processes and improve overall security posture. The tool is open-source, transparent, and community-driven, allowing users to self-host, contribute, and collaborate on integrations and features.