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google/syzkaller

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6,232 स्टार्स·1,425 फोर्क्स·Go·Apache-2.0·11 व्यूज़

Syzkaller

Syzkaller is an unsupervised, coverage-guided kernel fuzzer that automatically generates and mutates system call sequences to find bugs in operating system kernels. It operates without human intervention, using a closed feedback loop of input generation, execution, crash detection, and corpus refinement to continuously explore kernel code paths.

The fuzzer distinguishes itself by supporting multiple operating system kernels, including Linux, FreeBSD, and Windows, through per-platform syscall harnesses that abstract system call interfaces behind a common driver. It uses declarative descriptions of syscall arguments, structures, and constraints to produce valid and semantically meaningful inputs for each target OS, while parallel VM-based execution distributes workloads across isolated kernel instances to maximize throughput.

Syzkaller maintains a persistent corpus of interesting inputs, using coverage metrics to rank and evolve them for deeper kernel exploration. Crash reports are collected, deduplicated by stack trace or other signatures, and grouped into related bugs for efficient developer review. The project provides documentation and installation guidance for setting up fuzzing campaigns across supported platforms.

Features

  • Unsupervised Kernel Fuzzers - Syzkaller fuzzes operating system kernels by automatically generating and mutating system call sequences to find bugs without human supervision.
  • Coverage-Guided Fuzzers - A fuzzer that uses code coverage feedback to steer input generation toward unexplored kernel paths.
  • Coverage-Guided Fuzzing - Syzkaller guides fuzzing by using code coverage signals to steer input generation toward unexplored kernel paths and increase bug yield.
  • Multi-OS Kernel Fuzzers - A fuzzer that supports Linux, FreeBSD, Windows, and other OS kernels with per-platform harnesses.
  • Multi-OS Kernel Fuzzers - Running the same fuzzing engine across Linux, FreeBSD, Windows, and other OS kernels with per-platform harnesses.
  • Kernel-Specific Syscall Harnesses - Abstracts system call interfaces and kernel-specific harnesses behind a common driver, enabling the same fuzzer to target Linux, FreeBSD, and Windows.
  • Unsupervised Fuzzing Loops - Automatically runs a closed feedback cycle of input generation, execution, crash detection, and corpus refinement without human intervention.
  • Coverage-Guided Mutation - Generates and mutates sequences of system calls, using kernel code coverage feedback to prioritise inputs that reach new execution paths.
  • Coverage-Ranked Input Prioritization - Maintains a persistent corpus of interesting inputs, using coverage metrics to rank and evolve them for deeper kernel exploration.
  • Declarative System Call Descriptions - Uses declarative descriptions of syscall arguments, structures, and constraints to generate valid and semantically meaningful inputs for each target OS.
  • Parallel VM-Based Execution - Distributes fuzzing workloads across multiple virtual machines, each running isolated kernel instances to maximise throughput and avoid state interference.
  • Multi-OS Kernel Fuzzers - Syzkaller runs the same fuzzing engine across Linux, FreeBSD, Windows, and other OS kernels with per-platform harnesses.
  • Crash Deduplication and Triaging - Collects crash reports, deduplicates them by stack trace or other signatures, and groups related bugs for efficient developer review.
  • Fuzzing Frameworks - Distributed, coverage-guided fuzzer for Linux kernel syscalls.
  • Fuzzing Tools - Kernel-level fuzzer for discovering vulnerabilities in operating systems.
  • Kernel Fuzzers - Unsupervised coverage-guided kernel fuzzer.
  • Kernel Fuzzing Tools - Unsupervised coverage-guided fuzzer for multiple operating system kernels.
  • Security Tools - Unsupervised, coverage-guided kernel fuzzer.

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google/syzkaller क्या करता है?

Syzkaller is an unsupervised, coverage-guided kernel fuzzer that automatically generates and mutates system call sequences to find bugs in operating system kernels. It operates without human intervention, using a closed feedback loop of input generation, execution, crash detection, and corpus refinement to continuously explore kernel code paths.

google/syzkaller की मुख्य विशेषताएं क्या हैं?

google/syzkaller की मुख्य विशेषताएं हैं: Unsupervised Kernel Fuzzers, Coverage-Guided Fuzzers, Coverage-Guided Fuzzing, Multi-OS Kernel Fuzzers, Kernel-Specific Syscall Harnesses, Unsupervised Fuzzing Loops, Coverage-Guided Mutation, Coverage-Ranked Input Prioritization।

google/syzkaller के कुछ ओपन-सोर्स विकल्प क्या हैं?

google/syzkaller के ओपन-सोर्स विकल्पों में शामिल हैं: dvyukov/go-fuzz — go-fuzz is a coverage-guided randomized testing tool for identifying crashes and logic bugs in Go code. It consists of… google/clusterfuzz — ClusterFuzz is an automated platform that runs coverage-guided fuzzers at scale to find security and stability bugs in… google/afl — AFL is a coverage-guided fuzzer and security vulnerability scanner used to identify software bugs and memory… aflplusplus/aflplusplus — AFL++ is a coverage-guided fuzzing framework that discovers crashes and hangs in software by mutating inputs while… google/fuzzing — This project is a comprehensive software fuzzing knowledge base and technical guide designed for discovering software… sslab-gatech/janus — Janus: a state-of-the-art file system fuzzer on Linux.

Syzkaller के ओपन-सोर्स विकल्प

समान ओपन-सोर्स प्रोजेक्ट्स, जो Syzkaller के साथ साझा की गई सुविधाओं के आधार पर रैंक किए गए हैं।
  • dvyukov/go-fuzzdvyukov का अवतार

    dvyukov/go-fuzz

    4,853GitHub पर देखें↗

    go-fuzz is a coverage-guided randomized testing tool for identifying crashes and logic bugs in Go code. It consists of a fuzzer that evolves random inputs based on code execution paths, an instrumentation tool that produces binaries for tracking coverage, and a seed corpus manager. The tool utilizes compile-time binary instrumentation to monitor branch coverage and employs a feedback-driven mutation loop to prioritize inputs that reach new sections of the codebase. It includes capabilities for comparative differential testing to identify logic errors by executing different implementations of

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  • google/clusterfuzzgoogle का अवतार

    google/clusterfuzz

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    ClusterFuzz is an automated platform that runs coverage-guided fuzzers at scale to find security and stability bugs in software. It orchestrates libFuzzer and AFL++ across distributed clusters of worker bots, collecting coverage feedback to guide input mutation and discover crashes. The platform provides a web-based dashboard for configuring fuzzing jobs, monitoring progress, and inspecting crash reports, with role-based access control to restrict sensitive features. The system automates the full fuzzing lifecycle, from build pipeline integration and corpus management to crash triage and bug

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  • google/aflgoogle का अवतार

    google/AFL

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    AFL is a coverage-guided fuzzer and security vulnerability scanner used to identify software bugs and memory corruption by feeding programs mutated data. It functions as a binary instrumentation tool and a test case minimizer to locate crashes and isolate the smallest set of bytes causing a fault. The project distinguishes itself through its ability to operate as a parallel fuzzing orchestrator, distributing workloads across multiple CPU cores or networked machines. It utilizes dictionary-based mutation for complex file formats and performs input sensitivity analysis to identify critical sect

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  • aflplusplus/aflplusplusAFLplusplus का अवतार

    AFLplusplus/AFLplusplus

    6,605GitHub पर देखें↗

    AFL++ is a coverage-guided fuzzing framework that discovers crashes and hangs in software by mutating inputs while tracking which code paths are exercised. It functions as both a fuzzing engine and a campaign manager, supporting targets with or without source code through compile-time instrumentation, dynamic binary instrumentation, and emulation. The framework includes tools for crash triage and analysis, test case minimization, and campaign deployment across local or distributed environments. The framework distinguishes itself through its breadth of instrumentation backends, allowing users

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