Data

CSU-Malicious-Package-Metadata-Dataset

Charles Sturt University
Islam, Rafiqul
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://researchoutput.csu.edu.au/en/datasets/6830ab0a-c634-4e99-b3b3-03b3f0171398&rft.title=CSU-Malicious-Package-Metadata-Dataset&rft.identifier=6830ab0a-c634-4e99-b3b3-03b3f0171398&rft.publisher=GitHub&rft.description=The dataset consists of engineered features extracted from the metadata of software packages, designed to help identify whether a package is benign or malicious. These features capture various aspects of the package, including version details, description length, license presence, repository information, and dependency structure. Together, these features provide a rich set of metadata insights that can be used for machine learning models to predict potentially malicious packages and secure software supply chains.&rft.creator=Islam, Rafiqul &rft.date=2024&rft.type=dataset&rft.language=English Access the data
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The dataset consists of engineered features extracted from the metadata of software packages, designed to help identify whether a package is benign or malicious. These features capture various aspects of the package, including version details, description length, license presence, repository information, and dependency structure. Together, these features provide a rich set of metadata insights that can be used for machine learning models to predict potentially malicious packages and secure software supply chains.

Created: 2024-10 to 2024-10

Issued: 2024

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Identifiers
  • global : 6830ab0a-c634-4e99-b3b3-03b3f0171398