mysticmomba/AirlockTools
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Commiting before rebase

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brotoskyj
2025-08-28 11:29:14 -04:00
parent b24682c97a
commit 337ff99915
1 changed files with 30 additions and 9 deletions
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AirlockTools.py
+29 -8
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@@ -215,8 +215,8 @@ def menu_prepare_to_enforce():
print(ct.colorText(" When complete, save the csv file to the directory 'manuallyapproved'", "cyan"))
print(ct.colorText(" Preflight Lists will be generated", "cyan"))
if os.path.exists(f"manuallyapproved\\lcf_needs_approved_{first_policy}_{second_policy}.csv"):
print(ct.colorText(" [✓] Reviewed path list detected","green"))
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(" [✗] Path review list has not been detected","red"))
@@ -355,14 +355,35 @@ def menu_prepare_to_enforce():
print(ct.colorText(f"Please manually approve hashes prior to this step","red"))
elif choice == "4":
elif choice == "7":
if os.path.exists(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv"):
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")
if os.path.exists(f"dataframe_csv\\allinfo_{first_policy}_{second_policy}.csv") and os.path.exists(f"manuallyapproved\\lcf_needs_approved_{first_policy}_{second_policy}.csv"):
df1 = tryToReadCSV(f"dataframe_csv\\allinfo_{first_policy}_{second_policy}.csv")
pathexclusions,allowbyhash = utils.pathfunctions.mask_from_csv(df1, f"manuallyapproved\\lcf_needs_approved_{first_policy}_{second_policy}.csv","longestcfp")
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"))
pathexclusions.to_csv(f"preflight\\final_path_exclusions_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(pathexclusions, f"preflight\\final_path_exclusions_{first_policy}_{second_policy}.html")
allowbyhash.to_csv(f"preflight\\final_hash_approvals_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(allowbyhash, f"preflight\\final_hash_approvals_{first_policy}_{second_policy}.html")