mysticmomba/AirlockTools
1
1
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases 3 Wiki Activity

Second Draft

Browse Source
This commit is contained in:
=
2025-08-22 14:08:52 -04:00
parent e2398c687b
commit ac57773a9a
3 changed files with 50 additions and 33 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.gitignore
+1
View File
@@ -1,3 +1,4 @@
.env
*.html
*.csv
*__pycache__*
AirlockTools.py
+49 -28
View File
@@ -7,6 +7,8 @@ import utils.pathfunctions
import utils.allowfunctions
import urllib3
import pandas as pd
import sqlite3
import pathlib
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
dotenv.load_dotenv()
@@ -92,6 +94,9 @@ def menu_feature2():
print("Invalid choice. Please try again.")
def menu_prepare_to_enforce():
first_policy = " "
second_policy = " 4"
history_pol1_staged = True
history_pol2_staged = True
history_staged = True
@@ -104,16 +109,15 @@ def menu_prepare_to_enforce():
while True:
print("\n--- Prepare to Enforce Policy ---")
print("Sequentually follow steps to prepare for policy enforcement")
#print("1. Choose first policy, Typically the audit version of the policy - Currently selected first policy is: " + str([[first_policy[0]]))
#print("2. Choose second policy, If an enforcement policy of that type exists, include it here - Currently selected second policy is: " + str(second_policy[0]))
print("1. Choose first policy, Typically the audit version of the policy - Currently selected first policy is: " + first_policy)
print("2. Choose second policy, If an enforcement policy of that type exists, include it here - Currently selected second policy is: " + second_policy)
print("3. Pull and stage event history for the first policy - This step has been done - " + str(history_pol1_staged))
print("4. Pull and stage event history for the second policy - This step has been done - " + str(history_pol2_staged))
print("5. Combine aggregated policies -")
print("4. Pull Hash info - This step has been done - " + str(hashes_threat_pulled))
print("5. Determine if path exclusions are possible: - This step has been done - " + str(path_exclusions_calculated))
print("6. Categorize your hashes - This step has been done - " + str(hashes_categorized))
print("7. Combine Potential path exclusions and allowed hashes - This step has been done" + str(allowed_paths_determined))
print("6. Pull Hash info - This step has been done - " + str(hashes_threat_pulled))
print("7. Determine if path exclusions are possible: - This step has been done - " + str(path_exclusions_calculated))
print("8. Categorize your hashes - This step has been done - " + str(hashes_categorized))
print("9. Combine Potential path exclusions and allowed hashes - This step has been done" + str(allowed_paths_determined))
print("11. Exit")
choice = input("Enter your choice: ")
@@ -128,57 +132,68 @@ def menu_prepare_to_enforce():
elif choice == "3":
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"df_aggregated_{first_policy}.html", index=False)
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)
history_pol1_staged =True
elif choice == "4":
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"df_aggregated_{second_policy}.html", index=False)
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)
history_pol2_staged =True
elif choice == "5":
if history_pol1_staged == True & history_pol2_staged == True:
df1 = pd.read_html(f"df_aggregated_{first_policy}.html")[0]
df2 = pd.read_html(f"df_aggregated_{second_policy}.html")[0]
df1 = tryToReadCSV(f"df_aggregated_{first_policy}.csv")
df2 = tryToReadCSV(f"df_aggregated_{second_policy}.csv")
df_aggregated_combo= pd.concat([df1 , df2], ignore_index=True)
df_aggregated_combo.to_html(f"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)
history_staged = True
else:
print("Both Policies have to be staged to combine them")
elif choice == "6":
if history_staged == True:
df_augmented = utils.hashfunctions.augmentAggregatedHashes(url, pd.read_html(f"df_aggregated_combo_{first_policy}_{second_policy}.html")[0])
df_augmented.to_html(f"df_augmented_combo_{first_policy}_{second_policy}.html", index=False)
df_augmented = utils.hashfunctions.augmentAggregatedHashes(url,tryToReadCSV(f"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)
hashes_threat_pulled = True
else:
print("Data not yet staged, please complete earlier steps")
elif choice == "7":
if hashes_threat_pulled == True:
path_eligible, path_ineligible = utils.pathfunctions.filepathInitialGroup(pd.read_html(f"df_augmented_combo_{first_policy}_{second_policy}.html")[0])
path_eligible.to_html(f"df_path_eligible_{first_policy}_{second_policy}.html", index=False)
path_ineligible.to_html(f"df_path_ineligible_{first_policy}_{second_policy}.html", index=False)
path_eligible, path_ineligible = utils.pathfunctions.filepathInitialGroup(pd.read_csv(f"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)
path_exclusions_calculated = True
else:
print("Step 6 not complete, Please complete step 6")
elif choice == "8":
if path_exclusions_calculated == True:
categorized = utils.hashfunctions.categorizeHashes(pd.read_html(f"df_augmented_combo_{first_policy}_{second_policy}.html")[0], treat_tolerance_constant, badpublisherlist)
categorized[0].to_html(f"df_hashes_needing_approval_{first_policy}_{second_policy}.html", index=False)
categorized[1].to_html(f"df_automatically_approved_hashes_{first_policy}_{second_policy}.html", index=False)
categorized[2].to_html(f"df_remaining_hashes__{first_policy}_{second_policy}.html", index=False)
categorized = utils.hashfunctions.categorizeHashes(pd.read_csv(f"df_augmented_combo_{first_policy}_{second_policy}.csv"), treat_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)
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[2].to_html(f"dataframe_html\\df_remaining_hashes__{first_policy}_{second_policy}.html", index=False)
categorized[2].to_csv(f"dataframe_csv\\df_remaining_hashes__{first_policy}_{second_policy}.csv", index=False)
hashes_categorized = True
else:
print("Step 7 not complete, Please complete step 7")
elif choice == "9":
if hashes_categorized == True:
allowpaths = utils.allowfunctions.filter_and_drop(pd.read_html(f"df_automatically_approved_hashes_{first_policy}_{second_policy}.html")[0], pd.read_html(f"df_path_eligible_{first_policy}_{second_policy}.html")[0], path_exclusion_constant)
allowpaths.to_html(f"df_allowed_paths_{first_policy}_{second_policy}.html", index=False)
allowpaths = utils.allowfunctions.filter_and_drop(pd.read_csv(f"df_automatically_approved_hashes_{first_policy}_{second_policy}.csv"),tryToReadCSV(f"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)
allowed_paths_determined = True
else:
print("Step 8 not complete, Please complete step 8")
@@ -187,11 +202,17 @@ def menu_prepare_to_enforce():
else:
print("Invalid choice. Please try again.")
def tryToReadCSV(csv):
try:
df =tryToReadCSV(csv)
if df.empty:
print("CSV file has headers but no data rows.")
else:
print("Data loaded successfully.")
except pd.errors.EmptyDataError:
print("CSV file is completely empty (no headers, no data).")
df = pd.DataFrame() # Create an empty DataFrame as fallback
return df
if __name__ == "__main__":
apivalidation()
hashtest.py
-5
View File
@@ -1,5 +0,0 @@
hashes = ''
while True:
inputhash = input("Hash: ")
hashes = hashes + ',' + inputhash
print(hashes)