mysticmomba/AirlockTools
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Pretty HTML and beginnings of Destination Policy

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2025-08-26 12:20:09 -04:00
parent f081594a7e
commit ebfb0d80a9
6 changed files with 184 additions and 36 deletions
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AirlockTools.py
+27 -20
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@@ -19,7 +19,7 @@ import utils.getdeviceevents
import utils.allowlist
import utils.hashfunctions
import utils.pathfunctions
import utils.colortext as ct
import utils.pretty as ct
import urllib3
import pandas as pd
import ast
@@ -186,7 +186,7 @@ def menu_prepare_to_enforce():
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"))
if os.path.isfile(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv"):
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"):
print(ct.colorText(" [✓] This step has been completed","green"))
else:
print(ct.colorText(" [✗] This step has not been completed","red"))
@@ -215,43 +215,43 @@ def menu_prepare_to_enforce():
if not os.path.exists("dataframe_csv\\df_aggregated_{first_policy}.csv"):
executionhist_policy1 = utils.allowlist.pullPolicyExechistories(url,first_policy_tuple[0], first_policy_tuple[1],True)
df_aggregated_policy1 = utils.hashfunctions.aggregateHashes(executionhist_policy1)
df_aggregated_policy1.to_html(f"dataframe_html\\df_aggregated_{first_policy}.html", index=False)
df_aggregated_policy1.to_csv(f"dataframe_csv\\df_aggregated_{first_policy}.csv", index=False)
ct.style_dataframe_dark(df_aggregated_policy1, f"dataframe_html\\df_aggregated_{first_policy}.html")
print(ct.colorText(f"Staging of Exection history for policy: {first_policy} is complete","green"))
if not os.path.exists("dataframe_csv\\df_aggregated_{second_policy}.csv"):
executionhist_policy2 = utils.allowlist.pullPolicyExechistories(url,second_policy_tuple[0], second_policy_tuple[1],True)
df_aggregated_policy2 = utils.hashfunctions.aggregateHashes(executionhist_policy2)
df_aggregated_policy2.to_html(f"dataframe_html\\df_aggregated_{second_policy}.html", index=False)
df_aggregated_policy2.to_csv(f"dataframe_csv\\df_aggregated_{second_policy}.csv", index=False)
ct.style_dataframe_dark(df_aggregated_policy2, f"dataframe_html\\df_aggregated_{second_policy}.html")
print(ct.colorText(f"Staging of Exection history for policy: {second_policy} is complete","green"))
elif choice == "3":
if second_policy is first_policy and os.path.exists(f"dataframe_csv\\df_aggregated_{first_policy}.csv"):
df1 = tryToReadCSV(f"dataframe_csv\\df_aggregated_{first_policy}.csv")
df_aggregated_combo = df1
df_aggregated_combo.to_html(f"dataframe_html\\df_aggregated_combo_{first_policy}_{second_policy}.html", index=False)
df_aggregated_combo.to_csv(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(df_aggregated_combo, f"dataframe_html\\df_aggregated_combo_{first_policy}_{second_policy}.html")
print(ct.colorText(f"Dataframes have been aggregated (combined)","green"))
elif os.path.exists(f"dataframe_csv\\df_aggregated_{first_policy}.csv") and os.path.exists(f"dataframe_csv\\df_aggregated_{second_policy}.csv"):
df1 = tryToReadCSV(f"dataframe_csv\\df_aggregated_{first_policy}.csv")
df2 = tryToReadCSV(f"dataframe_csv\\df_aggregated_{second_policy}.csv")
df_aggregated_combo = pd.concat([df1 , df2], ignore_index=True)
df_aggregated_combo.to_html(f"dataframe_html\\df_aggregated_combo_{first_policy}_{second_policy}.html", index=False)
df_aggregated_combo.to_csv(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(df_aggregated_combo, f"dataframe_html\\df_aggregated_combo_{first_policy}_{second_policy}.html")
print(ct.colorText(f"Dataframes have been aggregated (combined)","green"))
else:
print(ct.colorText(f"Please stage your data before attempting this step","red"))
elif choice == "4":
if os.path.exists(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv"):
df_augmented = utils.hashfunctions.augmentAggregatedHashes(url,tryToReadCSV(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv"))
df_augmented.to_html(f"dataframe_html\\df_augmented_combo_{first_policy}_{second_policy}.html", index=False)
df_augmented.to_csv(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(df_augmented, f"dataframe_html\\df_augmented_combo_{first_policy}_{second_policy}.html")
print(ct.colorText(f"Hash reputation info added to dataframe","green"))
else:
print(ct.colorText(f"Please combine your data with step 3 prior to attempting this step","red"))
@@ -259,16 +259,17 @@ def menu_prepare_to_enforce():
if os.path.exists(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv"):
categorized = utils.hashfunctions.categorizeHashes(pd.read_csv(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv"), threat_tolerance_constant, badpublisherlist)
categorized[0].to_html(f"dataframe_html\\df_hashes_needing_approval_{first_policy}_{second_policy}.html", index=False)
categorized[0].to_csv(f"dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(categorized[0], f"dataframe_html\\df_hashes_needing_approval_{first_policy}_{second_policy}.html")
categorized[1].to_html(f"dataframe_html\\df_automatically_approved_hashes_{first_policy}_{second_policy}.html", index=False)
categorized[1].to_csv(f"dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(categorized[1], f"dataframe_html\\df_automatically_approved_hashes_{first_policy}_{second_policy}.html")
categorized[2].to_html(f"dataframe_html\\df_unapproved_hashes__{first_policy}_{second_policy}.html", index=False)
categorized[2].to_csv(f"dataframe_csv\\df_unapproved_hashes__{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(categorized[2], f"dataframe_html\\df_unapproved_hashes_{first_policy}_{second_policy}.html")
print(ct.colorText(f"Hashes have been categorized","green"))
else:
print(ct.colorText(f"Please Augment your data with hash threat info using step 4 prior to attempting this step","red"))
@@ -278,19 +279,19 @@ def menu_prepare_to_enforce():
df2 = tryToReadCSV(f"manuallyapproved\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv")
df_all_approved_hashes = pd.concat([df1 , df2], ignore_index=True)
df_all_approved_hashes.to_html(f"dataframe_html\\df_all_approved_hashes_{first_policy}_{second_policy}.html", index=False)
df_all_approved_hashes.to_csv(f"dataframe_csv\\df_all_approved_hashes_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(df_all_approved_hashes, f"dataframe_html\\df_all_approved_hashes_{first_policy}_{second_policy}.html")
df_paths_needing_review, df_path_ineligible = utils.pathfunctions.filepathInitialGroup(pd.read_csv(f"dataframe_csv\\df_all_approved_hashes_{first_policy}_{second_policy}.csv"))
df_paths_needing_review.to_html(f"dataframe_html\\df_paths_needing_review_{first_policy}_{second_policy}.html", index=False)
df_paths_needing_review.to_csv(f"dataframe_csv\\df_paths_needing_review_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(df_paths_needing_review, f"dataframe_html\\df_paths_needing_review_{first_policy}_{second_policy}.html")
df_path_ineligible.to_html(f"dataframe_html\\df_path_ineligible_{first_policy}_{second_policy}.html", index=False)
df_path_ineligible.to_csv(f"dataframe_csv\\df_path_ineligible_{first_policy}_{second_policy}.csv", index=False)
ct.style_dataframe_dark(df_path_ineligible, f"dataframe_html\\df_path_ineligible_{first_policy}_{second_policy}.html")
print(ct.colorText(f"Eligible paths determined","green"))
else:
print(ct.colorText(f"Please manually approve hashes prior to this step","red"))
@@ -299,8 +300,14 @@ def menu_prepare_to_enforce():
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")
print(df1['grouped_directory'])
print(df2['sha256'])
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")
else:
print(ct.colorText(f"Please manually approve suggested paths prior to this step","red"))