{"id":13845628,"url":"https://github.com/eshard/scared","last_synced_at":"2025-07-12T03:31:22.844Z","repository":{"id":40432369,"uuid":"191954655","full_name":"eshard/scared","owner":"eshard","description":"Make your first side-channel attack on public datasets with eShard. This is a mirror of scared Gitlab repository. 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Tools","Python"],"sub_categories":["Side-Channel Analysis"],"readme":"# SCAred\n\n[![pipeline status](https://gitlab.com/eshard/scared/badges/master/pipeline.svg)](https://gitlab.com/eshard/scared/commits/master)\n[![PyPI version](https://badge.fury.io/py/scared.svg)](https://pypi.org/project/scared/)\n[![Conda installer](https://anaconda.org/eshard/scared/badges/installer/conda.svg)](https://anaconda.org/eshard/scared)\n[![Latest Conda release](https://anaconda.org/eshard/scared/badges/latest_release_date.svg)](https://anaconda.org/eshard/scared)\n\nscared is a side-channel analysis framework maintained by [eShard](http://www.eshard.com) team.\n\n## Getting started\n\n### Requirements\n\nScared need python **3.7**, **3.8**, **3.9** or **3.10**.\n\nYou can install `scared`, depending on your setup:\n\n- from source\n- with `pip`\n- with `conda`\n\n#### Install with `conda`\n\nYou just have to run:\n\n```bash\nconda install -c eshard scared\n```\n\n#### Install with `pip`\n\nPython wheels are available from Pypi, just run:\n\n```bash\npip install scared\n```\n\n#### Install from sources\n\nTo install from sources, you will need to run:\n\n```bash\npip install .\n```\n\nfrom the source folder.\n\nIf you are planning to contribute, see [CONTRIBUTING.md](CONTRIBUTING.md) to install the library in development mode and run the test suite.\n\n### Make a first cool thing\n\nStart using scared by doing a cool thing:\n\n```python\n# First import the lib\nimport scared\nimport numpy as np\n\n# Define a selection function\n@scared.attack_selection_function\ndef first_add_key(plaintext, guesses):\n    res = np.empty((plaintext.shape[0], len(guesses), plaintext.shape[1]), dtype='uint8')\n    for i, guess in enumerate(guesses):\n        res[:, i, :] = np.bitwise_xor(plaintext, guess)\n    return res\n\n# Create an analysis CPA\na = scared.CPAAttack(\n        selection_function=first_add_key,\n        model=scared.HammingWeight(),\n        discriminant=scared.maxabs)\n\n# Load some traces, for example a dpa v2 subset\nths = scared.traces.read_ths_from_ets_file('dpa_v2.ets')\n\n# Create a container for your ths\ncontainer = scared.Container(ths)\n\n# Run!\na.run(container)\n```\n\n## Documentation\n\nTo go further and learn all about scared, please go to [the full documentation](https://eshard.gitlab.io/scared).\nYou can also have an interactive introduction to scared by launching these [notebooks with Binder](https://mybinder.org/v2/gl/eshard%2Fscared-notebooks/master).\n\n## Contributing\n\nAll contributions, starting with feedbacks, are welcomed.\nPlease read [CONTRIBUTING.md](CONTRIBUTING.md) if you wish to contribute to the project.\n\n## License\n\nThis library is licensed under LGPL V3 license. See the [LICENSE](LICENSE) file for details.\n\nIt is mainly intended for non-commercial use, by academics, students or professional willing to learn the basics of side-channel analysis.\n\nIf you wish to use this library in a commercial or industrial context, [eShard](https://www.eshard.com) provides commercial licenses under fees. [Contact us](mailto:scared@eshard.com)!\n\n## Authors\n\nSee [AUTHORS](AUTHORS.md) for the list of contributors to the project.\n\n## Binary builds available\n\nBinary builds (wheels on pypi and conda builds) are available for the following platforms and Python version.\n\nPlatforms:\n\n- Linux x86 64\n- Macosx x86 64\n\nPython version:\n\n- 3.6\n- 3.7\n- 3.8\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feshard%2Fscared","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Feshard%2Fscared","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feshard%2Fscared/lists"}