# Jackalope

Binary, coverage-guided fuzzer for Windows, macOS, Linux and Android

Repository: https://github.com/googleprojectzero/Jackalope
Canonical: https://ross.abutalabs.com/products/jackalope
Language: C++
License: Apache-2.0
License Family: permissive
Last push: 2026-08-25T12:40:01+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 2087, "days_push": 8, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1380, forks 157 (observed 2026-08-28T04:04:33.877129+00:00)

## What it is
Jackalope is a customizable, coverage-guided fuzzer for black-box binaries built on the TinyInst instrumentation library by Google Project Zero. It supports distributed fuzzing across machines, custom mutators including a grammar-based mutation engine, and runs on Windows, macOS, Linux, and Android.

## Use cases
- fuzz a closed-source Windows binary for memory corruption bugs
- fuzz macOS applications without source code
- run a distributed fuzzing campaign across multiple machines
- write custom mutators for a proprietary file format
- grammar-based fuzzing of a parser accepting structured input
- fuzz an Android native library
- fuzz a Linux target built with SanitizerCoverage

## When to choose
- you need to fuzz black-box binaries on Windows or macOS where few alternatives exist
- you want a fuzzer that is easy to customize with custom mutators, instrumentation, or sample delivery
- you need to parallelize fuzzing across threads or multiple machines
- you are doing vulnerability research on closed-source targets

## When to avoid
- you have source code and just want a mature off-the-shelf fuzzer like AFL++ or libFuzzer
- you need advanced built-in mutation strategies out of the box
- you want a low-effort setup without writing or configuring custom components for unusual targets

## Facets
- artifact type: library
- maturity: active
- function: fuzzing, security, penetration-testing, vulnerability-scanning
- domain: security, developer-tools, testing
- platform: windows, cpp
- tags: coverage-guided-fuzzing, binary-fuzzer, tinyinst, black-box-fuzzing, grammar-based-mutation, distributed-fuzzing, vulnerability-research, macos, linux, android

## Member repositories
- googleprojectzero/Jackalope (main) score 77
- googleprojectzero/TinyInst (sdk) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:33.877129+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:40:13.265066+00:00, confidence not recorded.
  - readme: https://github.com/googleprojectzero/Jackalope (fetched 2026-08-28T04:04:33.877129+00:00, sha 2424d6c71275)
- Data as of 2026-08-30T08:39:29.467469+00:00.