mysticmomba/AirlockTools
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Added Preflights

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2025-08-26 17:12:06 -04:00
parent ebfb0d80a9
commit b7082ffb5e
4 changed files with 155 additions and 36 deletions
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AirlockTools.py
+27 -9
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@@ -123,6 +123,7 @@ def menu_prepare_to_enforce():
if not os.path.exists("dataframe_html"): os.makedirs("dataframe_html")
if not os.path.exists("dataframe_csv"): os.makedirs("dataframe_csv")
if not os.path.exists("manuallyapproved"): os.makedirs("manuallyapproved")
if not os.path.exists("preflight"): os.makedirs("preflight")
df_aggregated_combo = pd.DataFrame()
while True:
@@ -184,9 +185,9 @@ def menu_prepare_to_enforce():
print(ct.colorText(f"7. Manually review the file df_paths_needing_review_{first_policy}_{second_policy}.csv", "cyan"))
print(ct.colorText(" Remove the rows containing path exclusions you do not approve of" , "cyan"))
print(ct.colorText(" When complete, save the csv file to the directory 'manuallyapproved' and choose this option to generate the proposed list of changes", "cyan"))
print(ct.colorText(" When complete, save the csv file to the directory 'manuallyapproved' and choose this option to generate the preflight lists", "cyan"))
if os.path.isfile(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_hashdestination_{first_policy}_{second_policy}.csv"):
if os.path.isfile(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv") and os.path.isfile("dataframe_csv\\df_hashdestination_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_addtochildpolicy_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\f_addtobaseline_{first_policy}_{second_policy}.csv"):
print(ct.colorText(" [✓] This step has been completed","green"))
else:
print(ct.colorText(" [✗] This step has not been completed","red"))
@@ -298,13 +299,30 @@ def menu_prepare_to_enforce():
elif choice == "7":
if os.path.exists(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv"):
df1 = tryToReadCSV(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv")
df2 = tryToReadCSV(f"dataframe_csv\\df_path_ineligible_{first_policy}_{second_policy}.csv")
df3 = tryToReadCSV(f"manuallyapproved\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv")
df_hashdestination = utils.hashfunctions.destinationbuilder(df2,df3)
df_hashdestination.to_csv("dataframe_csv\\df_hashdestination_{first_policy}_{second_policy}.csv")
ct.style_dataframe_dark(df_hashdestination,f"dataframe_html\\df_hashdestination_{first_policy}_{second_policy}.html")
df_approved = tryToReadCSV(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv")
df_eligible = tryToReadCSV(f"dataframe_csv\\df_paths_needing_review_{first_policy}_{second_policy}.csv")
df_ineligible = tryToReadCSV(f"dataframe_csv\\df_path_ineligible_{first_policy}_{second_policy}.csv")
approved_set = set([tuple(map(tuple, row)) for row in df_approved.values])
# Identify rows in eligible that are not in approved
not_approved_rows = df_eligible[~df_eligible.apply(lambda row: tuple(map(tuple, row)) in approved_set, axis=1)]
# Append these rows to ineligible
df_ineligible= pd.concat([df_ineligible, not_approved_rows], ignore_index=True)
df_approved.to_csv(f"preflight\\Approved_Path_Exclusions_{first_policy}_{second_policy}.csv")
ct.style_dataframe_dark(df_approved, f"preflight\\Approved_Path_Exclusions_{first_policy}_{second_policy}.html")
#Seperate out what we arent excluding by path into those that will go into the baseline, and those that will b added to the child.
df_addtobaseline = df_ineligible[df_ineligible['reputation status'] == 'KNOWN']
df_addtobaseline.to_csv(f"preflight\\Add_to_Baseline_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(df_addtobaseline, f"preflight\\Add_to_Baseline_{first_policy}_{second_policy}.html")
df_addtochildpolicy = df_ineligible[df_ineligible['reputation status'] == 'UNKNOWN']
df_addtochildpolicy.to_csv(f"preflight\\Add_to_Child_Policy_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(df_addtochildpolicy, f"preflight\\Add_to_Child_Policy_{first_policy}_{second_policy}.html")
else:
print(ct.colorText(f"Please manually approve suggested paths prior to this step","red"))