Cyberdefense/VulnWhisperer
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refactor cvss normalisation

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pemontto
2019-04-22 10:56:01 +10:00
parent 2b6afe31c2
commit 7c2aa54156
1 changed files with 32 additions and 53 deletions
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73
vulnwhisp/vulnwhisp.py
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@ -246,63 +246,42 @@ class vulnWhispererBase(object):
def common_normalise(self, df): def common_normalise(self, df):
"""Map and transform common data values""" """Map and transform common data values"""
self.logger.info('Start common mapping') self.logger.info('Start common normalisation')
if 'cvss_base' in df: self.logger.info('Normalising CVSS')
self.logger.info('Normalising CVSS base') for cvss_version in ['cvss', 'cvss3']:
if cvss_version + '_base' in df:
self.logger.info('Normalising {} base'.format(cvss_version))
# CVSS = cvss_temporal or cvss_base # CVSS = cvss_temporal or cvss_base
df['cvss'] = df['cvss_base'] df[cvss_version] = df[cvss_version + '_base']
df.loc[df['cvss_temporal'] != '', 'cvss'] = df['cvss_temporal'] df.loc[df[cvss_version + '_temporal'] != '', cvss_version] = df[cvss_version + '_temporal']
if 'cvss3_base' in df:
self.logger.info('Normalising CVSS3 base')
# CVSS3 = cvss3_temporal or cvss3_base
df['cvss3'] = df['cvss3_base']
df.loc[df['cvss3_temporal'] != '', 'cvss3'] = df['cvss3_temporal']
# Combine CVSS and CVSS3 vectors # Combine CVSS and CVSS3 vectors
if 'cvss_vector' in df and 'cvss_temporal_vector' in df: if cvss_version + '_vector' in df and cvss_version + '_temporal_vector' in df:
self.logger.info('Normalising CVSS Vector') self.logger.info('Normalising {} vector'.format(cvss_version))
df['cvss_vector'] = ( df[cvss_version + '_vector'] = (
df[['cvss_vector', 'cvss_temporal_vector']] df[[cvss_version + '_vector', cvss_version + '_temporal_vector']]
.apply(lambda x: '{}/{}'.format(x[0], x[1]), axis=1) .apply(lambda x: '{}/{}'.format(x[0], x[1]), axis=1)
.str.rstrip('/nan') .str.rstrip('/nan')
) )
df.drop('cvss_temporal_vector', axis=1, inplace=True) df.drop(cvss_version + '_temporal_vector', axis=1, inplace=True)
if 'cvss3_vector' in df and 'cvss3_temporal_vector' in df:
self.logger.info('Normalising CVSS3 Vector')
df['cvss3_vector'] = (
df[['cvss3_vector', 'cvss3_temporal_vector']]
.apply(lambda x: '{}/{}'.format(x[0], x[1]), axis=1)
.str.rstrip('/nan')
)
df.drop('cvss3_temporal_vector', axis=1, inplace=True)
if 'cvss' in df: if cvss_version in df:
self.logger.info('Normalising CVSS severity') self.logger.info('Normalising {} severity'.format(cvss_version))
# Map CVSS to severity name # Map CVSS to severity name
df.loc[df['cvss'] == '', 'cvss'] = None df.loc[df[cvss_version] == '', cvss_version] = None
df['cvss'] = df['cvss'].astype('float') df[cvss_version] = df[cvss_version].astype('float')
# df.loc[df['cvss'].isnull(), 'cvss_severity'] = 'info' # df.loc[df[cvss_version].isnull(), cvss_version + '_severity'] = 'info'
df.loc[df['cvss'] == 0, 'cvss3_severity'] = 'info' df.loc[df[cvss_version] == 0, cvss_version + '_severity'] = 'info'
df.loc[(df['cvss'] > 0) & (df['cvss'] < 3), 'cvss_severity'] = 'low' df.loc[(df[cvss_version] > 0) & (df[cvss_version] < 3), cvss_version + '_severity'] = 'low'
df.loc[(df['cvss'] >= 3) & (df['cvss'] < 6), 'cvss_severity'] = 'medium' df.loc[(df[cvss_version] >= 3) & (df[cvss_version] < 6), cvss_version + '_severity'] = 'medium'
df.loc[(df['cvss'] >= 6) & (df['cvss'] < 9), 'cvss_severity'] = 'high' df.loc[(df[cvss_version] >= 6) & (df[cvss_version] < 9), cvss_version + '_severity'] = 'high'
df.loc[(df['cvss'] > 9) & (df['cvss'].notnull()), 'cvss_severity'] = 'critical' df.loc[(df[cvss_version] > 9) & (df[cvss_version].notnull()), cvss_version + '_severity'] = 'critical'
if 'cvss3' in df: # Make rename cvss to cvss2
self.logger.info('Normalising CVSS3 severity') # Make cvss with no suffix == cvss3 else cvss2
# Map CVSS to severity name # cvss = cvss3 if cvss3 else cvss2
df.loc[df['cvss3'] == '', 'cvss3'] = None # cvss_severity = cvss3_severity if cvss3_severity else cvss2_severity
df['cvss3'] = df['cvss3'].astype('float')
# df.loc[df['cvss3'].isnull(), 'cvss3_severity'] = 'info'
df.loc[df['cvss3'] == 0, 'cvss3_severity'] = 'info'
df.loc[(df['cvss3'] > 0) & (df['cvss3'] < 3), 'cvss3_severity'] = 'low'
df.loc[(df['cvss3'] >= 3) & (df['cvss3'] < 6), 'cvss3_severity'] = 'medium'
df.loc[(df['cvss3'] >= 6) & (df['cvss3'] < 9), 'cvss3_severity'] = 'high'
df.loc[(df['cvss3'] > 9) & (df['cvss3'].notnull()), 'cvss3_severity'] = 'critical'
# Ensure empty strings are output as nulls
df.replace({'': np.nan}, inplace=True) df.replace({'': np.nan}, inplace=True)
return df return df