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Ransomware_Detection_Using_PE_Imports Rows: 140261 | Cols: 5 | Reports Used: 3084

Description: A dataset of the function names of PE imports and the DLL the functions are called from.

Dataset SHA256: 239115234c1ba81d16badf2babd1c3d48b28541c137628739d5919d458449313

Features (sample):

	function_name	dll	category	label	SHA256
0	SysFreeString	oleaut32.dll	Ransomware	M	4e0d1edb76747fd945b87dd18299298f0df719edbea946119d91db59a9b6527a
1	SysReAllocStringLen	oleaut32.dll	Ransomware	M	4e0d1edb76747fd945b87dd18299298f0df719edbea946119d91db59a9b6527a
...	...	...	...	...	...
140259	VariantClear	oleaut32.dll	Ransomware	M	eb920e0fc0c360abb901e04dce172459b63bbda3ab8152350885db4b44d63ce5
140260	VariantInit	oleaut32.dll	Ransomware	M	eb920e0fc0c360abb901e04dce172459b63bbda3ab8152350885db4b44d63ce5

140261 rows × 5 columns

Created by: Tanatswa Dendere
Downloaded 3 times
Comments Enabled: True
Comments: 0
Associated Dataset (datasets that are linked to this dataset):
Ransomware_Detection_Using_Features_of_PE_Imports
Ransomware_Detection_Using_Features_of_PE_Imports_2

def process(data, filename, sha256, category, malicious):
    try:
        # Implement your data processing here, this function will get called with the data of each 
        # report in the category you have selected along with the filename of the report and hash. 
        # Do your processing and add your data to the features array, and return the features_lables, features, and sha256
        # PLEASE NOTE: THE CODE BELOW SERVES AS AN EXAMPLE ONLY! This example extracts the entropy of the PE Sections. Which can be seen here: https://malfe.cs.up.ac.za/datasets/view/Entropy_of_PE_Sections/5
        ###

features_labels = ["function_name", "dll", "category", "label"]
        features = []
        label =   "M" if malicious else "B"
        if "static" in data:
            if "pe_imports" in data["static"]:
                for pe in data["static"]["pe_imports"]:
                    dll = pe["dll"]
                    for i in pe["imports"]:
                        features.append([i["name"], dll, category, label])                
        
        ###
        return features_labels, features, sha256
        
    except Exception as e:
        log("|process error| " + filename + " -> " + sha256 + " (" + str(e) + ")")
        pass

April 26, 2023, 9:22 a.m. Public Create New Vesion Download Dataset (15.0 MB)

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Public Datasets

Ransomware_Detection_Using_PE_Imports Rows: 140261 | Cols: 5 | Reports Used: 3084

Reports Used

Dataset Code

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