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Data Theft Repackaged: A Case Study in Malicious Wrapper Packages on npm
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
Simple self-use great functions
Use the package manager pip to install utilities.
pip install -i https://test.pypi.org/simple/ xin-util
# regular utilities
from xin_util.PrettyPrintDict import pretty_print_dict
from xin_util.CreateDIYdictFromDataFrame import CreateDIYdictFromDataFrame
from xin_util.ReadWritePicklefile import read_pickle, save_pickle
from xin_util.DownloadFromS3 import S3_download_folder, S3_upload_folder
from xin_util.BarPlots import plot_stacked_bar
from xin_util.ZipAndUnzip import zip, unzip
from xin_util.AccessSQL import getDBData, create
# TimeSeries
from xin_util.TimeSeriesFeatureEngineer import TimeSeries, create_average_feature
# NLP related
from xin_util.TextProcess import text_tokens
from xin_util.ResamplingData import up_resample
from xin_util.Scores import single_label_f_score, single_label_included_score, multiple_label_included_score
from xin_util.TFIDFpredict import tf_idf_classify
from xin_util.EmbeddingCNNpredict import Convolution_Network_classify
from xin_util.EmbeddingRNNpredict import Recurrent_Network_classify
from xin_util.FASTTEXTpredict import fasttext_classify
from xin_util.NBpredict import Naive_Bayes_classify
from xin_util.ONEHOTNNpredict import Onehot_Network_classify
from xin_util.LatentDirichletAllocationClass import MyLDA
# Model training time prediction
from model_trainingtime_prediction.layer_level_utils import get_train_data
from model_trainingtime_prediction.random_network_gen import gen_nn
from model_trainingtime_prediction.train_time_predict import prediction_model
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
FAQs
Xin's self created helper functions
We found that xin-util demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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