mysticmomba/AirlockTools
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Everything Ready for the API Calls to approve in airlock

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2025-08-25 14:43:37 -04:00
parent 5f06e60fdd
commit d767ba9621
1 changed files with 51 additions and 43 deletions
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AirlockTools.py
+51 -43
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@@ -19,10 +19,10 @@ import utils.getdeviceevents
import utils.allowlist import utils.allowlist
import utils.hashfunctions import utils.hashfunctions
import utils.pathfunctions import utils.pathfunctions
import utils.allowfunctions
import utils.colortext as ct import utils.colortext as ct
import urllib3 import urllib3
import pandas as pd import pandas as pd
import ast
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
dotenv.load_dotenv() dotenv.load_dotenv()
@@ -117,6 +117,7 @@ def menu_prepare_to_enforce():
first_policy = " " first_policy = " "
second_policy = " " second_policy = " "
#If the directorys where we're going to store our output dont exist, make them. #If the directorys where we're going to store our output dont exist, make them.
if not os.path.exists("dataframe_html"): os.makedirs("dataframe_html") if not os.path.exists("dataframe_html"): os.makedirs("dataframe_html")
@@ -164,38 +165,32 @@ def menu_prepare_to_enforce():
else: else:
print(ct.colorText(" [✗] This step has not been completed","red")) print(ct.colorText(" [✗] This step has not been completed","red"))
print(ct.colorText("5. Determine if path exclusions are possible", "cyan")) print(ct.colorText("5. Categorize your hashes ", "cyan"))
if os.path.exists(f"dataframe_csv\\df_path_eligible_{first_policy}_{second_policy}.csv") == True:
print(ct.colorText(" [✓] This step has been completed","green"))
else:
print(ct.colorText(" [✗] This step has not been completed", "red"))
print(ct.colorText("6. Categorize your hashes ", "cyan"))
if os.path.isfile(f"dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_unapproved_hashes__{first_policy}_{second_policy}.csv"): if os.path.isfile(f"dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_unapproved_hashes__{first_policy}_{second_policy}.csv"):
print(ct.colorText(" [✓] This step has been completed","green")) print(ct.colorText(" [✓] This step has been completed","green"))
else: else:
print(ct.colorText(" [✗] This step has not been completed","red")) print(ct.colorText(" [✗] This step has not been completed","red"))
print(ct.colorText(f"7. Manually review the files \\dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv and dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv", "cyan")) print(ct.colorText(f"6. Manually review the files \\dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv and dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv", "cyan"))
print(ct.colorText(" Remove the rows containing hashes you do not approve of, and those you would not approve of without metarules.", "cyan")) print(ct.colorText(" Remove the rows containing hashes you do not approve of, and those you would not approve of without metarules.", "cyan"))
print(ct.colorText(" If metarules need to be created, please make note of them, and remove the row from the csv.", "cyan")) print(ct.colorText(" If metarules need to be created, please make note of them, and remove the row from the csv.", "cyan"))
print(ct.colorText(" When complete, move both csv files to the directory 'manuallyapproved' and choose this option to combine these approved hashes with the automatically approved hashes", "cyan")) print(ct.colorText(" When complete, save both csv files to the directory 'manuallyapproved' and choose this option to combine these approved hashes with the automatically approved hashes and generate a list of paths to be reviewed", "cyan"))
if os.path.isfile(f"dataframe_csv\\df_all_approved_hashes_{first_policy}_{second_policy}.csv"): if os.path.isfile(f"dataframe_csv\\df_paths_needing_review_{first_policy}_{second_policy}.csv"):
print(ct.colorText(" [✓] This step has been completed","green")) print(ct.colorText(" [✓] This step has been completed","green"))
else: else:
print(ct.colorText(" [✗] This step has not been completed","red")) print(ct.colorText(" [✗] This step has not been completed","red"))
""" print(ct.colorText(f"7. Manually review the file df_paths_needing_review_{first_policy}_{second_policy}.csv", "cyan"))
print(ct.colorText("7. Compare potential path exclusions with allowed hashes", "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"))
if os.path.exists(f"dataframe_csv\\df_allowed_paths_{first_policy}_{second_policy}.csv") == True:
if os.path.isfile(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv"):
print(ct.colorText(" [✓] This step has been completed","green")) print(ct.colorText(" [✓] This step has been completed","green"))
else: else:
print(ct.colorText(" [✗] This step has not been completed","red")) print(ct.colorText(" [✗] This step has not been completed","red"))
"""
print(ct.colorText("Q. Quit", "cyan")) print(ct.colorText("Q. Quit", "cyan"))
@@ -235,11 +230,14 @@ def menu_prepare_to_enforce():
if second_policy is first_policy and os.path.exists(f"dataframe_csv\\df_aggregated_{first_policy}.csv"): 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") df1 = tryToReadCSV(f"dataframe_csv\\df_aggregated_{first_policy}.csv")
df_aggregated_combo = df1 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_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) df_aggregated_combo.to_csv(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv", index=False)
elif os.path.exists(f"dataframe_csv\\df_aggregated_{first_policy}.csv") and os.path.exists(f"dataframe_csv\\df_aggregated_{second_policy}.csv"): 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") df1 = tryToReadCSV(f"dataframe_csv\\df_aggregated_{first_policy}.csv")
df2 = tryToReadCSV(f"dataframe_csv\\df_aggregated_{second_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 = 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_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) df_aggregated_combo.to_csv(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv", index=False)
@@ -249,43 +247,63 @@ def menu_prepare_to_enforce():
elif choice == "4": elif choice == "4":
if os.path.exists(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv"): 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 = 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_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) df_augmented.to_csv(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv", index=False)
print(ct.colorText(f"Hash reputation info added to dataframe","green")) print(ct.colorText(f"Hash reputation info added to dataframe","green"))
else: else:
print(ct.colorText(f"Please combine your data with step 3 prior to attempting this step","red")) print(ct.colorText(f"Please combine your data with step 3 prior to attempting this step","red"))
elif choice == "5": elif choice == "5":
if os.path.exists(f"dataframe_html\\df_augmented_combo_{first_policy}_{second_policy}.html"):
path_eligible, path_ineligible = utils.pathfunctions.filepathInitialGroup(pd.read_csv(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv"))
path_eligible.to_html(f"dataframe_html\\df_path_eligible_{first_policy}_{second_policy}.html", index=False)
path_eligible.to_csv(f"dataframe_csv\\df_path_eligible_{first_policy}_{second_policy}.csv", index=False)
path_ineligible.to_html(f"dataframe_html\\df_path_ineligible_{first_policy}_{second_policy}.html", index=False)
path_ineligible.to_csv(f"dataframe_csv\\df_path_ineligible_{first_policy}_{second_policy}.csv", index=False)
print(ct.colorText(f"Eligible paths determined","green"))
else:
print(ct.colorText(f"Please Augment your data with hash threat info using step 4 prior to attempting this step","red"))
elif choice == "6":
if os.path.exists(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv"): 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 = 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_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) categorized[0].to_csv(f"dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv", index=False)
categorized[1].to_html(f"dataframe_html\\df_automatically_approved_hashes_{first_policy}_{second_policy}.html", index=False) 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) categorized[1].to_csv(f"dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv", index=False)
categorized[2].to_html(f"dataframe_html\\df_unapproved_hashes__{first_policy}_{second_policy}.html", index=False) 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) categorized[2].to_csv(f"dataframe_csv\\df_unapproved_hashes__{first_policy}_{second_policy}.csv", index=False)
print(ct.colorText(f"Hashes have been categorized","green")) print(ct.colorText(f"Hashes have been categorized","green"))
else: else:
print(ct.colorText(f"Please Augment your data with hash threat info using step 4 prior to attempting this step","red")) print(ct.colorText(f"Please Augment your data with hash threat info using step 4 prior to attempting this step","red"))
elif choice == "7": elif choice == "6":
if os.path.isfile(f"manuallyapproved\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv"): if os.path.exists(f"manuallyapproved\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv") and os.path.exists(f"manuallyapproved\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv"):
df1 = tryToReadCSV(f"manuallyapproved\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv") df1 = tryToReadCSV(f"manuallyapproved\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv")
df2 = tryToReadCSV(f"manuallyapproved\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv") 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 = pd.concat([df1 , df2], ignore_index=True)
df_aggregated_combo.to_html(f"dataframe_html\\df_all_approved_hashes_{first_policy}_{second_policy}.html", index=False) df_all_approved_hashes.to_html(f"dataframe_html\\df_all_approved_hashes_{first_policy}_{second_policy}.html", index=False)
df_aggregated_combo.to_csv(f"dataframe_csv\\df_all_approved_hashes_{first_policy}_{second_policy}.csv", index=False) df_all_approved_hashes.to_csv(f"dataframe_csv\\df_all_approved_hashes_{first_policy}_{second_policy}.csv", index=False)
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)
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)
print(ct.colorText(f"Eligible paths determined","green"))
else:
print(ct.colorText(f"Please manually approve hashes prior to this step","red"))
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")
print(df1['grouped_directory'])
print(df2['sha256'])
elif choice == "Q": elif choice == "Q":
@@ -293,17 +311,7 @@ def menu_prepare_to_enforce():
else: else:
print(ct.colorText("Invalid choice. Please try again.", "red")) print(ct.colorText("Invalid choice. Please try again.", "red"))
"""
elif choice == "7":
if os.path.exists(f"dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv") and os.path.exists(f"dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv") and os.path.exists(f"dataframe_csv\\df_unapproved_hashes__{first_policy}_{second_policy}.csv"):
allowpaths = utils.allowfunctions.filter_and_drop(pd.read_csv(f"dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv"),tryToReadCSV(f"dataframe_csv\\df_path_eligible_{first_policy}_{second_policy}.csv"), path_exclusion_constant)
allowpaths.to_html(f"dataframe_html\\df_allowed_paths_{first_policy}_{second_policy}.html", index=False)
allowpaths.to_csv(f"dataframe_csv\\df_allowed_paths_{first_policy}_{second_policy}.csv", index=False)
print(ct.colorText(f"Allowable paths determined","green"))
else:
print(ct.colorText(f"Please complete step 6 prior to attempting this step","red"))
"""
def tryToReadCSV(csv): def tryToReadCSV(csv):
try: try: