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Merge pull request #138 from ahouseholder/feature/fix_135
Add python lookup helper for v2
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,49 +1,49 @@ | ||
| Public?,Contacted?,Credible?,Cardinality,Engagement,Utility,PublicSafetyImpact,Outcome | ||
| No,Yes,Yes,one,active,laborious,minor,decline | ||
| Public,Contacted,Credible,Cardinality,Engagement,Utility,PublicSafetyImpact,Outcome | ||
| No,Yes,Yes,one,active,laborious,minimal,decline | ||
| No,Yes,Yes,one,active,laborious,significant,decline | ||
| No,Yes,Yes,one,active,efficient,minor,decline | ||
| No,Yes,Yes,one,active,efficient,minimal,decline | ||
| No,Yes,Yes,one,active,efficient,significant,track | ||
| No,Yes,Yes,one,active,super-effective,minor,decline | ||
| No,Yes,Yes,one,active,super-effective,minimal,decline | ||
| No,Yes,Yes,one,active,super-effective,significant,track | ||
| No,Yes,Yes,one,unresponsive,laborious,minor,track | ||
| No,Yes,Yes,one,unresponsive,laborious,minimal,track | ||
| No,Yes,Yes,one,unresponsive,laborious,significant,coordinate | ||
| No,Yes,Yes,one,unresponsive,efficient,minor,coordinate | ||
| No,Yes,Yes,one,unresponsive,efficient,minimal,coordinate | ||
| No,Yes,Yes,one,unresponsive,efficient,significant,coordinate | ||
| No,Yes,Yes,one,unresponsive,super-effective,minor,coordinate | ||
| No,Yes,Yes,one,unresponsive,super-effective,minimal,coordinate | ||
| No,Yes,Yes,one,unresponsive,super-effective,significant,coordinate | ||
| No,Yes,Yes,multiple,active,laborious,minor,decline | ||
| No,Yes,Yes,multiple,active,laborious,minimal,decline | ||
| No,Yes,Yes,multiple,active,laborious,significant,track | ||
| No,Yes,Yes,multiple,active,efficient,minor,decline | ||
| No,Yes,Yes,multiple,active,efficient,minimal,decline | ||
| No,Yes,Yes,multiple,active,efficient,significant,track | ||
| No,Yes,Yes,multiple,active,super-effective,minor,coordinate | ||
| No,Yes,Yes,multiple,active,super-effective,minimal,coordinate | ||
| No,Yes,Yes,multiple,active,super-effective,significant,coordinate | ||
| No,Yes,Yes,multiple,unresponsive,laborious,minor,coordinate | ||
| No,Yes,Yes,multiple,unresponsive,laborious,minimal,coordinate | ||
| No,Yes,Yes,multiple,unresponsive,laborious,significant,coordinate | ||
| No,Yes,Yes,multiple,unresponsive,efficient,minor,coordinate | ||
| No,Yes,Yes,multiple,unresponsive,efficient,minimal,coordinate | ||
| No,Yes,Yes,multiple,unresponsive,efficient,significant,coordinate | ||
| No,Yes,Yes,multiple,unresponsive,super-effective,minor,coordinate | ||
| No,Yes,Yes,multiple,unresponsive,super-effective,minimal,coordinate | ||
| No,Yes,Yes,multiple,unresponsive,super-effective,significant,coordinate | ||
| No,Yes,No,one,active,laborious,minor,decline | ||
| No,Yes,No,one,active,laborious,minimal,decline | ||
| No,Yes,No,one,active,laborious,significant,decline | ||
| No,Yes,No,one,active,efficient,minor,decline | ||
| No,Yes,No,one,active,efficient,minimal,decline | ||
| No,Yes,No,one,active,efficient,significant,track | ||
| No,Yes,No,one,active,super-effective,minor,decline | ||
| No,Yes,No,one,active,super-effective,minimal,decline | ||
| No,Yes,No,one,active,super-effective,significant,track | ||
| No,Yes,No,one,unresponsive,laborious,minor,decline | ||
| No,Yes,No,one,unresponsive,laborious,minimal,decline | ||
| No,Yes,No,one,unresponsive,laborious,significant,decline | ||
| No,Yes,No,one,unresponsive,efficient,minor,decline | ||
| No,Yes,No,one,unresponsive,efficient,minimal,decline | ||
| No,Yes,No,one,unresponsive,efficient,significant,track | ||
| No,Yes,No,one,unresponsive,super-effective,minor,decline | ||
| No,Yes,No,one,unresponsive,super-effective,minimal,decline | ||
| No,Yes,No,one,unresponsive,super-effective,significant,track | ||
| No,Yes,No,multiple,active,laborious,minor,decline | ||
| No,Yes,No,multiple,active,laborious,minimal,decline | ||
| No,Yes,No,multiple,active,laborious,significant,track | ||
| No,Yes,No,multiple,active,efficient,minor,decline | ||
| No,Yes,No,multiple,active,efficient,minimal,decline | ||
| No,Yes,No,multiple,active,efficient,significant,track | ||
| No,Yes,No,multiple,active,super-effective,minor,track | ||
| No,Yes,No,multiple,active,super-effective,minimal,track | ||
| No,Yes,No,multiple,active,super-effective,significant,coordinate | ||
| No,Yes,No,multiple,unresponsive,laborious,minor,decline | ||
| No,Yes,No,multiple,unresponsive,laborious,minimal,decline | ||
| No,Yes,No,multiple,unresponsive,laborious,significant,track | ||
| No,Yes,No,multiple,unresponsive,efficient,minor,decline | ||
| No,Yes,No,multiple,unresponsive,efficient,minimal,decline | ||
| No,Yes,No,multiple,unresponsive,efficient,significant,track | ||
| No,Yes,No,multiple,unresponsive,super-effective,minor,track | ||
| No,Yes,No,multiple,unresponsive,super-effective,minimal,track | ||
| No,Yes,No,multiple,unresponsive,super-effective,significant,coordinate |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,114 @@ | ||
| #!/usr/bin/env python | ||
| ''' | ||
| file: ssvc_v2 | ||
| author: adh | ||
| created_at: 3/23/21 3:23 PM | ||
| ''' | ||
|
|
||
| import os | ||
| import pandas as pd | ||
|
|
||
| DATAPATH="../data/v2/csv" | ||
|
|
||
| PATHS = { | ||
| 'coord_pub': os.path.join(DATAPATH,"ssvc_2_coord-publish.csv"), | ||
| 'coord_triage': os.path.join(DATAPATH,"ssvc_2_coord-triage.csv"), | ||
| 'deployer': os.path.join(DATAPATH,"ssvc_2_deployer.csv"), | ||
| 'supplier': os.path.join(DATAPATH,"ssvc_2_supplier.csv"), | ||
| } | ||
|
|
||
| DEFAULTS = { | ||
| 'coord_pub': { | ||
| # An analyst should feel comfortable selecting none if they (or their search scripts) have performed searches | ||
| # in the appropriate places for public PoCs and active exploitation (as described above) and found none. | ||
| "Exploitation": "none", | ||
| }, | ||
| 'coord_triage': { | ||
|
|
||
| }, | ||
| 'deployer': { | ||
| # An analyst should feel comfortable selecting none if they (or their search scripts) have performed searches | ||
| # in the appropriate places for public PoCs and active exploitation (as described above) and found none. | ||
| "Exploitation": "none", | ||
| "Exposure": "unavoidable" | ||
| }, | ||
| 'supplier': { | ||
| # An analyst should feel comfortable selecting none if they (or their search scripts) have performed searches | ||
| # in the appropriate places for public PoCs and active exploitation (as described above) and found none. | ||
| "Exploitation": "none", | ||
| }, | ||
| } | ||
|
|
||
| # confirm that PATHS and DEFAULTS keys match | ||
| assert(set(PATHS.keys()) == set(DEFAULTS.keys())) | ||
|
|
||
| def _load_csvs(path_dict): | ||
| data = {} | ||
| for key,path in path_dict.items(): | ||
| df = pd.read_csv(path) | ||
| data[key] = df | ||
| return data | ||
|
|
||
| DATA = _load_csvs(PATHS) | ||
|
|
||
| # confirm that PATHS and DATA keys match | ||
| assert(set(PATHS.keys()) == set(DATA.keys())) | ||
|
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||
|
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| def lookup(key, query_dict,use_defaults=True): | ||
| # get the full table | ||
| df = DATA[key] | ||
|
|
||
| if use_defaults: | ||
| # copy the defaults before we use them | ||
| defaults = DEFAULTS.get(key,{}) | ||
| q = dict(defaults) | ||
| else: | ||
| q = {} | ||
|
|
||
| q.update(query_dict) | ||
|
|
||
| # with each pass, slice the table | ||
| for k,v in q.items(): | ||
|
|
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| df = df.loc[df[k] == v] | ||
| return df | ||
|
|
||
| def outcome_dist(df,normalize=True): | ||
| ''' | ||
| Given a dataframe representing an SSVC tree fragment, | ||
| compute and return the distribution of outcomes | ||
| ''' | ||
| return df['Outcome'].value_counts(normalize=normalize) | ||
|
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||
|
|
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| def main(): | ||
| for key,df in DATA.items(): | ||
| print(key, df.columns) | ||
|
|
||
| print() | ||
| query = { | ||
| "Utility": "laborious", | ||
| "PublicSafetyImpact": "minimal", | ||
| } | ||
| df = lookup('coord_triage',query) | ||
| print(query) | ||
| print(df) | ||
| print(outcome_dist(df).round(decimals=3).to_dict()) | ||
|
|
||
| print() | ||
| query = {'Value added': "precedence"} | ||
| df = lookup('coord_pub',query) | ||
| print(query) | ||
| print(df) | ||
| print(outcome_dist(df).round(decimals=3).to_dict()) | ||
|
|
||
| print() | ||
| query = {"PublicSafetyImpact": "minimal"} | ||
| df = lookup('supplier',query) | ||
| print(query) | ||
| print(df) | ||
| print(outcome_dist(df).round(decimals=3).to_dict()) | ||
|
|
||
| if __name__ == '__main__': | ||
| main() |