https://github.com/mozillasecurity/corpus-replicator

A corpus generation tool
https://github.com/mozillasecurity/corpus-replicator

corpus fuzzing media test

Last synced: about 1 year ago
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A corpus generation tool

• Host: GitHub
• URL: https://github.com/mozillasecurity/corpus-replicator
• Owner: MozillaSecurity
• License: mpl-2.0
• Created: 2023-06-13T23:32:39.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2025-03-26T17:11:24.000Z (over 1 year ago)
• Last Synced: 2025-05-07T08:14:18.210Z (about 1 year ago)
• Topics: corpus, fuzzing, media, test
• Language: Python
• Homepage:
• Size: 42 KB
• Stars: 22
• Watchers: 6
• Forks: 3
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md
  • Code of conduct: CODE_OF_CONDUCT.md
  • Codeowners: .github/CODEOWNERS

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README

          
Corpus Replicator

=================

[![Task Status](https://community-tc.services.mozilla.com/api/github/v1/repository/MozillaSecurity/corpus-replicator/main/badge.svg)](https://community-tc.services.mozilla.com/api/github/v1/repository/MozillaSecurity/corpus-replicator/main/latest)

[![Matrix](https://img.shields.io/badge/chat-%23fuzzing-green?logo=matrix)](https://matrix.to/#/#fuzzing:mozilla.org)

[![PyPI](https://img.shields.io/pypi/v/corpus-replicator)](https://pypi.org/project/corpus-replicator)

Corpus Replicator is a corpus generation tool that enables the creation of multiple

unique output files based on templates. The primary intended use case is the

creation of a seed corpus that can be used by fuzzers. Support for additional output

formats can be added via the creation of `Recipes`. If a desired format is unsupported,

support can be added via the creation of a `CorpusGenerator`.

The goal is to create an efficient corpus that maximizes code coverage and minimizes

file size. Small unique files that execute quickly are preferred.

Currently four media types can be generated `animation`, `audio`, `image` and

`video`.

Requirements

------------

Corpus Replicator relies on [FFmpeg](https://ffmpeg.org/).

Installation

------------

```

pip install corpus-replicator

```

Example

-------

This is an example `recipe` file.

```yaml

# "base" contains required entries and default flags

base:

  codec: "h264"       # name of the codec

  container: "mp4"    # container/file extension

  library: "libx264"  # name of library

  medium: "video"     # supported medium

  tool: "ffmpeg"      # name of supported tool

  default_flags:

    encoder:          # "encoder" flag group

      ["-c:v", "libx264"]

    resolution:       # "resolution" flag group

      ["-s", "320x240"]

# variations allow flags to be added and overwritten

# one file will be generated for each entry in a flag group

variation:

  resolution:         # flag group - overwrites default flag group in "base"

  - ["-s", "640x480"]

  - ["-s", "32x18"]

  - ["-s", "64x64"]

  monochrome:         # flag group - adds new flag group

  - ["-vf", "hue=s=0"]

```

Running the recipe will generate a corpus:

```

$ corpus-replicator example.yml video -t test

Generating templates...

1 recipe(s) will be used with 1 template(s) to create 4 file(s).

Generating 4 'video/libx264/h264/mp4' file(s) using template 'test'...

Optimizing corpus, checking for duplicates...

Done.

```

Resulting corpus:

```

$ ls generated-corpus/

video-h264-libx264-test-monochrome-00.mp4

video-h264-libx264-test-resolution-01.mp4

video-h264-libx264-test-resolution-00.mp4

video-h264-libx264-test-resolution-02.mp4

```

A more complex corpus can be generated by using multiple `Recipes` and `Templates` at

once.

Recipes are stored in [src/corpus_replicator/recipes](/src/corpus_replicator/recipes/).