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View Code? Open in Web Editor NEWA python app to predict Att&ck tactics and techniques from cyber threat reports
License: MIT License
A python app to predict Att&ck tactics and techniques from cyber threat reports
License: MIT License
When I try to run rcATT_gui.py, it runs fine. When I access the website, put some dummy text inside and press "Predict", the whole thing crashes and displays "ModuleNotFoundError: No module named 'sklearn.feature_selection.univariate_selection'", as seen in the screenshots below.
Is there anything that can be done?
Where did you get your dataset to train the model?
Just labeled data from
https://github.com/mitre/cti ?
I see there are 1700 records in total, which is not enough to train a machine learning model I suppose.
Or have you ever thought about collecting threat reports from other sites and human label them?
This is a basic requirements.txt just in case you want to add it for an easier installation via pip.
colorama == 0.4.3
flask == 1.1.2
joblib == 0.14.1
nltk == 3.4.5
numpy == 1.17.4
pandas == 0.25.3
sklearn <= 0.22
stix2 == 1.2.1
this should be:
predprob_techniques_corrected[i][j] = 0
k makes no sense. See confidence_propagation
-function.
I also changed the effectiveness of the function with numpy arrays. See my pending pull request.
I noticed that when running the train command, the "added data" CSV file classification_tools/data/training_data_added.csv
is not actually appended to the "original" training dataset:
rcATT/classification_tools/__init__.py
Line 70 in f82f7fd
Note that the Pandas DataFrame.append
function returns a new DataFrame and does not modify its input, so the corrected version would be:
train_data_df = train_data_df.append(train_data_added, ignore_index = True)
I'd be happy to submit this as a merge request, if that'd work.
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