github microsoft/msticpy v2.15.0
Multi-dimensional plots for outliers

12 days ago

Highlights

Multi-dimensional plots for outliers by @Tatsuya-hasegawa

The outliers module has lived in MSTICPy for a long time but been some neglected
@Tatsuya-hasegawa (hacker-T) has contributed some cool visualizations to
better interpret the data.
Many thanks!!!

import numpy as np
from msticpy.analysis.outliers import identify_outliers,plot_outlier_results

n_dimension = 7

# create random numeric samples
data = np.random.rand(100, n_dimension)

# calc outliers by Isolation Forest algorism
clf, X_outliers, y_pred_outliers = identify_outliers(data, data, contamination=0.1, max_features=0.4)
    
feature_columns = [f'feature{i}' for i in range(1, n_dimension+1)]

plot_outlier_results(
    clf, 
    data,
    data, 
    X_outliers, 
    feature_columns=feature_columns, 
    plt_title="MSTICPY Isolation Forest Anomaly Detection for Multi Dimension Features"
)

image

Improved code/docs for federated authentication for M365D/M356 Graph providers - @ryan-detect-dot-dev

Although using federated auth (rather than client secret) has been possible for a while, the documentation
for how to use this was in the MSTICPy docs. Thanks to Ryan we now have this (along with cleaned up code
for the Defender* data providers.
(although Ryan is listed as a new contributor below - he has made several previous contributions under
a different GitHub identity)

Rigorous Type Annotation work started by @FlorianBracq earlier this year continues.

This helps to make the code more robust and clearer to read and use. This is thankless work but my
huge thanks go out to @FlorianBracq for this!

Other fixes

Some other important fixes to CyberReason driver and Azure Monitor/MS Sentinel driver are also included

What's Changed

New Contributors

Full Changelog: v2.14.0...v2.15.0

Don't miss a new msticpy release

NewReleases is sending notifications on new releases.