1. Dataset of malicious software packages.
2. FGI extraction code.
3. Data analysis code.

We have written the front-end of the webpage type. We have two extraction modes: online or offline.
You need to enter the file (.txt) address or folder address respectively to perform batch processing to extract information.

Contains code and dataset for classifier training (NPM ecosystem):

• word2vec_embedding
  Embed many kinds of text data as vectors.

• machine_learing_4kinds
  Use machine learning and deep learning algorithms to learn and classify vectors.

• end_result
  Metadata, static, dynamic, and all 3 machine/deep learning result data.

• other folder

  • Word-text dataset
  • Embedding-vector dataset
  • The dataset with noget in the name represents the dataset after removing the empty data in static.

Contains dataset we extracted and the extraction method:

• get_all_sum
  Get all types of data (name, OSS, description, author, maintainer, URL, dependencies number, Static_APIs, Dynamic_APIs).

• Dynamic_msg_ip
  Count the number of messages and IP addresses in dynamic API.

• Data_acquisition contains dataset we extracted and the extraction method

  • get_all_sum: get all types of data(name, OSS, description, author, maintainer, URL, dependencies number, Static_APIs, Dynamic_APIs).
  • Dynamic_msg_ip: count the number of messages and IP addresses in the dynamic API.
  • other folder: Statistical dataset.

• other folder
  Statistical dataset.