6 مستودعات
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.
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.
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.
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.
Battery Historian هي أداة تصور وتوصيف لتحليل استهلاك الطاقة ونفاد البطارية على أجهزة Android. تعمل كعارض لتقارير الأخطاء وموصّف لاستهلاك الطاقة يقوم بتحليل سجلات النظام لاستخراج إحصائيات البطارية وبيانات النواة إلى واجهة قائمة على الويب. تتخصص الأداة في ربط مصادر البيانات المتباينة على جدول زمني متزامن. تحدد الأنشطة المستنزفة للطاقة من خلال تتبع انتقالات wakelock في مساحة المستخدم والنواة، وربط مصادر استيقاظ النواة بالطوابع الزمنية في الوقت الفعلي، وتراكب سجلات مراقبة طاقة العتاد الخارجية على أحداث النظام. يوفر النظام قدرات للتحليل المقارن، مما يسمح بحساب الفروق بين تقارير أخطاء متعددة لقياس التغييرات في سلوك الطاقة. كما يجمع المقاييس على مستوى التطبيق وأحداث النظام لتحديد محفزات برمجية محددة تمنع الجهاز من الدخول في وضع السكون.
Logs kernel wakeup sources and activities to identify low-level system triggers for power consumption.
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.
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.