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6 个仓库

Awesome GitHub RepositoriesKernel Task Inspection

Tools for extracting detailed state and metadata from active kernel tasks.

Distinct from Kernel Debuggers: Focuses on inspecting the state of kernel tasks, distinct from general kernel debugging or construction.

Explore 6 awesome GitHub repositories matching operating systems & systems programming · Kernel Task Inspection. Refine with filters or upvote what's useful.

Awesome Kernel Task Inspection GitHub Repositories

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  • pwndbg/pwndbgpwndbg 的头像

    pwndbg/pwndbg

    10,051在 GitHub 上查看↗

    pwndbg is a GDB plugin and binary analysis framework designed for reverse engineering, exploit development, and low-level program analysis. It extends the core functionality of the debugger to provide advanced memory inspection and automation tools. The project distinguishes itself with specialized capabilities for heap analysis across glibc, jemalloc, and musl, as well as a comprehensive kernel debugging toolkit for inspecting Linux kernel tasks and slab allocators. It includes an integrated ROP gadget searcher for constructing exploit chains and an LLM-powered debugging assistant that provi

    Enables inspection of kernel-level execution via system emulation to identify security vulnerabilities.

    Pythonbinary-ninjacapture-the-flagctf
    在 GitHub 上查看↗10,051
  • falcosecurity/falcofalcosecurity 的头像

    falcosecurity/falco

    8,670在 GitHub 上查看↗

    Falco is an eBPF runtime security monitor and cloud native detection engine that identifies abnormal behavior and security threats across hosts and containers. It functions as a Linux kernel event auditor, capturing system calls and kernel events in real-time to detect malicious activity. The system distinguishes itself through a rule-based threat detection model that evaluates system activity against a library of community-maintained rules and custom security definitions. It enriches raw kernel events with container and Kubernetes metadata to provide observability into isolated environments

    Dumping of raw events from kernel drivers to a local interface for debugging and verification of data collection.

    C++cloud-nativecncfcncf-project
    在 GitHub 上查看↗8,670
  • tensorflow/rusttensorflow 的头像

    tensorflow/rust

    5,480在 GitHub 上查看↗

    This project provides Rust bindings for the TensorFlow C API, serving as a tensor computation interface and machine learning library. It enables the construction and execution of machine learning models and neural networks by bridging a systems language to high-performance backends. The framework supports GPU-accelerated computing to increase the speed of model training and inference by offloading mathematical operations to graphics processing units. It offers both graph-based computation for defining static network architectures and an eager execution mode for immediate operation calls durin

    Allows retrieval of metadata and definition buffers for all operations and kernels available in the environment.

    Rust
    在 GitHub 上查看↗5,480
  • google/battery-historiangoogle 的头像

    google/battery-historian

    5,401在 GitHub 上查看↗

    Battery Historian 是一款用于分析 Android 设备功耗和电池损耗的可视化和分析工具。它作为一个错误报告查看器和功耗分析器,解析系统日志以将电池统计数据和内核数据提取到基于 Web 的界面中。 该工具专门用于在同步的时间轴上关联不同的数据源。它通过追踪用户空间和内核唤醒锁(wakelock)转换、将内核唤醒源映射到实时时间戳,并将外部硬件功耗监控日志叠加到系统事件上来识别耗电活动。 该系统提供了比较分析功能,允许计算多个错误报告之间的增量以衡量功耗行为的变化。它进一步聚合了应用程序级指标和系统事件,以查明导致设备无法进入睡眠模式的具体软件触发因素。

    Logs kernel wakeup sources and activities to identify low-level system triggers for power consumption.

    Go
    在 GitHub 上查看↗5,401
  • hyperdbg/hyperdbgHyperDbg 的头像

    HyperDbg/HyperDbg

    3,885在 GitHub 上查看↗

    HyperDbg is a hardware-assisted kernel-mode debugging platform that leverages virtualization to monitor and control system execution. By utilizing hypervisor-level primitives, it enables deep system analysis and instrumentation without relying on standard operating system debugging interfaces. The framework provides a comprehensive environment for inspecting both kernel and user-mode processes, allowing for granular control over execution flow and system state. The project distinguishes itself through a transparent debugging layer designed to remain invisible to the target environment. It emp

    Analyzes kernel-mode processes using a hypervisor to monitor memory and instruction flow without standard OS interfaces.

    Cbinary-analysisdebugdebugger
    在 GitHub 上查看↗3,885
  • cilium/pwrucilium 的头像

    cilium/pwru

    3,777在 GitHub 上查看↗

    pwru is a tooling implementation for tracing, filtering, and debugging network packet movements and transformations within the Linux kernel. It functions as an eBPF network packet tracer and debugger used to analyze kernel state and identify where network packets are dropped or redirected. The project provides specialized capabilities for monitoring the packet lifecycle, including tracking packets through NAT transformations and tunnel decapsulation. It includes an eBPF traffic filter that reduces noise by restricting traced packets based on namespaces, interfaces, and kernel function names.

    Extracts detailed packet metadata and L4 tuples from active kernel tasks and data structures.

    C
    在 GitHub 上查看↗3,777
  1. Home
  2. Operating Systems & Systems Programming
  3. Kernel Task Inspection

探索子标签

  • Kernel Event Stream Inspection1 个子标签Tools for dumping and analyzing raw event streams directly from kernel drivers for verification. **Distinct from Kernel Task Inspection:** Distinct from Kernel Task Inspection: focuses on the continuous stream of captured events rather than the static state of a kernel task.
  • Kernel Execution Analysis2 个子标签Tools for analyzing the execution flow and behavior of kernel-level processes. **Distinct from Kernel Task Inspection:** Distinct from Kernel Task Inspection: focuses on the execution flow and vulnerability identification rather than just static state extraction.
  • ML Kernel Metadata InspectionRetrieval of metadata and definition buffers for machine learning operations and kernels. **Distinct from Kernel Task Inspection:** Distinct from Kernel Task Inspection which focuses on OS process state; this focuses on ML operation metadata.