Search Results for "kernel-br"
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Showing 397 open source projects for "kernel-br"
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Lunatik
Lunatik is a framework for scripting the Linux kernel with Lua
Lunatik is a framework for scripting the Linux kernel with Lua. It is composed by the Lua interpreter modified to run in the kernel; a device driver (written in Lua =)) and a command line tool to load and run scripts and manage runtime environments from the user space; a C API to load and run scripts and manage runtime environments from the kernel; and Lua APIs for binding kernel facilities to Lua scripts. -
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gVisor
Application Kernel for Containers
...Its key runtime, runsc, integrates seamlessly with container ecosystems such as Docker and Kubernetes, making it easy to deploy sandboxed workloads using familiar tools. By intercepting and safely handling syscalls from applications, gVisor reduces the attack surface of the host kernel, mitigating risks associated with running untrusted or potentially malicious code in containerized environments. -
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Nitro Enclaves Command Line Interface
Tooling for Nitro Enclave management
This repository contains a collection of tools and commands used for managing the lifecycle of enclaves. The Nitro CLI needs to be installed on the parent instance, and it can be used to start, manage, and terminate enclaves. The Nitro Enclaves kernel driver is available in the upstream Linux kernel starting with the v5.10 kernel for x86_64 and starting with the v5.16 kernel for arm64. The codebase from the 'drivers/virt/nitro_enclaves' directory in this GitHub repository is similar to the one merged into the upstream Linux kernel. The enclaves do not have access to a physical disk, just a RAM filesystem. ... -
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TitanHide
Hiding kernel-driver for x86/x64
TitanHide is an open-source Windows kernel driver designed to conceal debugging activity from selected processes during software analysis. It operates at the kernel level by intercepting specific Windows system functions and modifying information returned to applications. This approach helps reverse engineers examine software that implements debugger detection and anti-debugging protections. -
Endpoint Management with Remote Control Built InSplashtop AEM handles patching, alerts, scripts, and inventory, and unattended remote control is included. When something needs hands-on work, you’re one click away instead of switching tools.
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LKMPG
The Linux Kernel Module Programming Guide
lkmpg is a modernized, open-source guide that teaches the fundamentals of writing Linux kernel modules through clear explanations and working examples. It covers the full lifecycle: building and loading modules, understanding kernel symbols, handling device files, and interacting with kernel subsystems. Readers learn about concurrency concerns (spinlocks, mutexes), memory allocation in kernel space, and safe patterns for error handling and cleanup. -
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eBPF
ebpf-go is a pure-Go library to read, modify and load eBPF programs
Package ebpf is a toolkit for working with eBPF programs. eBPF programs are small snippets of code which are executed directly in a VM in the Linux kernel, which makes them very fast and flexible. Many Linux subsystems now accept eBPF programs. This makes it possible to implement highly application-specific logic inside the kernel, without having to modify the actual kernel itself. This package is designed for long-running processes which want to use eBPF to implement part of their application logic. ... -
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pwru
eBPF-based Linux kernel networking debugger
pwru is an eBPF-based tool for tracing network packets in the Linux kernel with advanced filtering capabilities. It allows fine-grained introspection of kernel state to facilitate debugging network connectivity issues. -
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ProperTree
Cross platform GUI plist editor written in python
...Users can rearrange entries through drag-and-drop operations, search and replace content, and reverse changes with a comprehensive undo history. Its OpenCore Snapshot functionality automatically synchronizes configuration entries with installed ACPI tables, kernel extensions, drivers, and tools. It also checks kernel extension dependencies and identifies duplicate identifiers. Additional utilities provide data conversion, hexadecimal integer handling, and context-sensitive OpenCore and Clover configuration assistance. -
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Tile Kernels
A kernel library written in tilelang
Tile Kernels is a DeepSeek kernel library written with TileLang for high-performance AI and machine-learning workloads. It contains specialized kernels for areas such as mixture-of-experts routing, quantization, batched transpose operations, Engram gating, and Manifold HyperConnection components. The project includes both optimized kernel implementations and PyTorch reference versions for comparison and validation. -
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Copy Fail - CVE-2026-31431
epository that demonstrates and analyzes a Linux kernel vulnerability
Copy Fail - CVE-2026-31431 is a proof-of-concept repository that demonstrates and analyzes a specific Linux kernel vulnerability identified as CVE-2026-31431. The project provides experimental scripts and documentation to reproduce and study the exploit in controlled environments. It is designed for security researchers and engineers who want to understand the mechanics of the vulnerability. The repository includes tested configurations across multiple Linux distributions and kernel versions. ... -
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CUDA Python
Performance meets Productivity
...The project is designed to simplify GPU programming by offering Pythonic abstractions while still exposing the full power of CUDA for advanced users. It integrates tightly with the broader Python GPU ecosystem, including Numba for kernel compilation and CCCL for parallel primitives, allowing developers to write performant code without leaving Python. The toolkit also includes utilities for profiling, memory management, distributed computing, and numerical operations, making it suitable for scientific computing, AI, and data processing workloads. -
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JupyterLab LSP
Coding assistance for JupyterLab (code navigation + hover suggestions
...Use the context menu entry, or Alt + 🖱️ to jump to definitions/references (you can change it to Ctrl/⌘ in settings); use Alt + o to jump back. Place your cursor on a variable, function, etc and all the usages will be highlighted. When a kernel is available the suggestions from the kernel (such as keys of a dict and columns of a DataFrame) are merged with the suggestions from the Language Server (in notebook). If the kernel is too slow to respond promptly only the Language Server suggestions will be shown (default threshold: 0.6s). You can configure the completer to not attempt to fetch the kernel completions if the kernel is busy. -
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linux-wasm
WebAssembly (Wasm) arch support for the Linux kernel
linux-wasm is an experimental project that ports the Linux kernel to run directly as a WebAssembly module, enabling a full Linux environment to boot and operate entirely inside a web browser without virtualization or cloud infrastructure. Instead of emulating Linux through a virtual machine, this project compiles the actual kernel for a WebAssembly target, allowing it to execute natively within a Wasm runtime. -
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OCaml Jupyter
An OCaml kernel for Jupyter (IPython) notebook
An OCaml kernel for Jupyter Notebook. This provides an OCaml REPL with a great user interface such as markdown/HTML documentation, LaTeX formula by MathJax, and image embedding. OCaml Jupyter requires the libraries zlib, libffi, libgmp, libzmq 5+. -
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BCC (BPF Compiler Collection)
Tools for BPF-based Linux IO analysis, networking, monitoring, etc.
BCC is a toolkit that simplifies creating efficient kernel tracing, monitoring, and manipulation programs by leveraging extended Berkeley Packet Filters (eBPF). It includes a rich set of example tools and scripting interfaces in C, Python, and Lua. BCC makes BPF programs easier to write, with kernel instrumentation in C (and includes a C wrapper around LLVM), and front-ends in Python and lua. -
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NVIDIA Warp
A Python framework for accelerated simulation, data generation
NVIDIA Warp is a high-performance Python framework developed by NVIDIA for building and accelerating simulation, graphics, and physics-based workloads using GPU computing. It enables developers to write kernel-level code in Python that is automatically compiled into efficient CUDA kernels, combining ease of use with near-native performance. The framework is designed for applications such as robotics, reinforcement learning, physical simulation, and differentiable computing, where performance and flexibility are critical. Warp provides a set of primitives for working with arrays, geometry, and physics operations, allowing users to implement complex simulations without writing low-level CUDA code directly. ... -
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GoNB
GoNB, a Go Notebook Kernel for Jupyter
Go is a compiled language, but with very fast compilation, that allows one to use it in a REPL (Read-Eval-Print-Loop) fashion, by inserting a "Compile" step in the middle of the loop -- so it's a Read-Compile-Run-Print-Loop — while still feeling very interactive. GoNB leverages that compilation speed to implement a full-featured (at least it's getting there) Jupyter notebook kernel. As a side benefit it works with packages that use CGO — although it won't parse C code in the cells, so it can't be used as a C kernel. It already includes many goodies: cache between cell of results, contextual help and auto-complete (with gopls), compilation error context (by mousing over), bash command execution, images, html, etc. ... -
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gophernotes
The Go kernel for Jupyter notebooks and nteract
...The gophernotes logo was designed by the brilliant Marcus Olsson and was inspired by Renee French's original Go Gopher design. If you have the JUPYTER_PATH environmental variable set or if you are using an older version of Jupyter, you may need to copy this kernel config to another directory. -
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Cosmos
Cosmos is an operating system "construction kit"
...Cosmos (C# Open Source Managed Operating System) is an operating system development kit that uses Visual Studio as its development environment. Despite C# in the name any .NET-based language can be used including VB.NET, Fortran, Delphi Prism, IronPython, F# and more. Cosmos itself and the kernel routines are primarily written in C#, and thus the Cosmos name. Cosmos is not an operating system in the traditional sense, but instead, it is an "Operating System Development Kit". Cosmos lets you create operating systems just as Visual Studio and C# normally let you create applications. Most users can write and boot their own operating system in just a few minutes, all using Visual Studio. -
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LZ4
Extremely fast compression algorithm
...A high compression derivative, called LZ4_HC, is available, trading customizable CPU time for compression ratio. LZ4 library is provided as open-source software using a BSD license. This benchmark simulates simple "static content transfer" scenario such as OS Kernel compression or video game's static assets (text/images/tables/scripts/etc) which loading from Flash Memory / HDD / SSD. In this case, compression time is completely ignored. Because only content developers compress the data at once and usually they don't care about its computational cost. But they always care end user's experience a.k.a. ... -
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Armbian Linux Build Framework
Armbian Linux Build Framework
...Special config utilities are optional. A distributed image is compressed to its real data size which starts below 1G. Login is possible via serial, HDMI/VGA or SSH. Boot loader and kernel optimizations, memory caching, ZRAM swap, and video acceleration where applicable. Images are made fully automatized from sources. Releases are PGP signed and code is regularly inspected by the community. Long-term support, quick security fixes, documentation and community-based end-user support. Make sure you have a good & reliable SD card and a proper power supply. ... -
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Triton
Development repository for the Triton language and compiler
Triton is a programming language and compiler framework specifically designed for writing highly efficient custom deep learning operations, particularly for GPUs. It aims to bridge the gap between low-level GPU programming, such as CUDA, and higher-level abstractions by providing a more productive and flexible environment for developers. Triton enables users to write optimized kernels for machine learning workloads while maintaining readability and control over performance-critical aspects... -
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Perfetto
Production-grade client-side tracing, profiling, and analysis
...It’s designed around a low-overhead producer/consumer model: instrumented components (“producers”) write binary events into shared memory buffers and a collector (“service”) reliably streams them to storage. The data model spans kernel and userspace, so you can stitch together CPU scheduling, app lifecycles, binder/IPC hops, GPU work, power and thermal signals, file I/O, heap samples, and more into a single coherent timeline. Perfetto’s ecosystem includes a web-based UI that can load multi-GB traces directly in the browser and an offline “trace processor” that exposes the trace as a queryable SQL-like table schema for deep analysis and automation. ... -
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Privilege-Escalation
This cheasheet is aimed at the CTF Players and Beginners
...It is aimed at CTF players, penetration testers, and beginners studying post-exploitation techniques in controlled environments. The repository organizes material by common escalation vectors instead of presenting a single automated tool. Topics include sudo permissions, SUID binaries, kernel weaknesses, scheduled jobs, Linux capabilities, writable files, containers, databases, and network services. Individual guides connect these concepts to vulnerable lab machines and CTF examples. This structure helps learners recognize recurring misconfigurations and understand why they create security risk. The collection is primarily focused on Linux-oriented privilege escalation and educational security practice. -
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LiteBox
A security-focused library OS supporting kernel execution
...The design emphasizes interoperability across different integration layers, describing a separation between “North” shims (how apps or runtimes plug in) and “South” platforms (where the sandbox runs), which helps the system adapt to multiple deployment contexts. A key aspect of the project is that it targets both kernel-mode and user-mode scenarios, enabling experimentation with different trust and performance tradeoffs. The repository positions LiteBox as a foundation for building hardened execution environments where untrusted or semi-trusted components can run with reduced privileges and a minimized host interface.
