Cleaned up menu by functionalizing

This commit is contained in:
=
2025-09-04 12:18:22 -04:00
parent 73811ba4d2
commit 781edcfa99
5 changed files with 299 additions and 309 deletions
+26 -290
View File
@@ -14,11 +14,8 @@
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import dotenv
import gc
import json
import os
import pandas as pd
import re
import urllib3
import utils.allowlist
import utils.getdeviceevents
@@ -41,7 +38,6 @@ path_exclusion_constant = 3
min_files_for_path = 4
threat_tolerance_constant = 4
def apivalidation():
match os.getenv('APIKEY'):
case '':
@@ -140,9 +136,12 @@ def menu_prepare_to_enforce():
first_policy = " "
second_policy = " "
allowlist_parent_name = " "
allowlist_child_name = " "
destination_name = " "
destination_id = " "
allowlist_parent_name = " "
allowlist_parent_id = " "
allowlist_child_name = " "
allowlist_child_id = " "
#If the directorys where we're going to store our output dont exist, make them.
if not os.path.exists("parquet"): os.makedirs("parquet")
@@ -176,247 +175,34 @@ def menu_prepare_to_enforce():
elif choice == "2":
if not os.path.exists(f"parquet\\execution_history_{first_policy}.parquet"):
print(choice)
print(first_policy)
exe1 = utils.allowlist.pullPolicyExechistories(url, first_policy, 60, True)
data = json.loads(exe1)
executionhist_policy1 = pd.DataFrame(data["response"]["exechistories"])
if not executionhist_policy1.empty:
executionhist_policy1 = executionhist_policy1[['sha256', 'publisher', 'filename', 'hostname', 'username', 'pprocess', 'gprocess', 'commandline']]
executionhist_policy1 = executionhist_policy1.drop_duplicates(subset=['sha256', 'filename', 'hostname'])
executionhist_policy1 = executionhist_policy1.sort_values(by=['sha256', 'filename'])
executionhist_policy1.to_parquet(f"parquet\\execution_history_{first_policy}.parquet", index=False)
print(ct.colorText(f"Staging of Execution history for policy: {first_policy} is complete", "green"))
del data
del exe1
del executionhist_policy1
gc.collect()
utils.policyfunctions.getPolicyInfo(url, first_policy, 60)
if not os.path.exists(f"parquet\\execution_history_{second_policy}.parquet"):
exe2 = utils.allowlist.pullPolicyExechistories(url,second_policy, 60, True)
data2 = json.loads(exe2)
executionhist_policy2 = pd.DataFrame(data2["response"]["exechistories"])
if not executionhist_policy2.empty:
executionhist_policy2 = executionhist_policy2[['sha256', 'publisher', 'filename', 'hostname', 'username', 'pprocess', 'gprocess', 'commandline']]
executionhist_policy2 = executionhist_policy2.drop_duplicates(subset=['sha256', 'filename', 'hostname'])
executionhist_policy2 = executionhist_policy2.sort_values(by=['sha256', 'filename'])
executionhist_policy2.to_parquet(f"parquet\\execution_history_{second_policy}.parquet", index=False)
print(ct.colorText(f"Staging of Execution history for policy: {second_policy} is complete", "green"))
del executionhist_policy2
del data2
del exe2
gc.collect()
utils.policyfunctions.getPolicyInfo(url, second_policy, 60)
if not os.path.exists(f"parquet\\combined_hashlist_{first_policy}_{second_policy}.parquet"):
combined_hashes = pd.DataFrame(columns=['sha256', 'publisher'])
hashes = []
try:
hash1 = pd.read_parquet(f"parquet\\execution_history_{first_policy}.parquet", columns=['sha256', 'publisher'])
utils.pathfunctions.inspect_parquet(f"parquet\\execution_history_{first_policy}.parquet")
if not hash1.empty:
hashes.append(hash1)
else:
print("⚠️ First dataframe is empty.")
except Exception as e:
print(f"❌ Error reading first Parquet file: {e}")
try:
hash2 = pd.read_parquet(f"parquet\\execution_history_{second_policy}.parquet", columns=['sha256', 'publisher'])
utils.pathfunctions.inspect_parquet(f"parquet\\execution_history_{second_policy}.parquet")
if not hash2.empty:
hashes.append(hash2)
else:
print("⚠️ Second dataframe is empty.")
except Exception as e:
print(f"❌ Error reading second Parquet file: {e}")
if hashes:
combined_hashes = pd.concat(hashes, ignore_index=True)
print(f"✅ Combined {len(combined_hashes)} hashes.")
else:
print("⚠️ No valid dataframes to combine.")
combined_hashes = combined_hashes.drop_duplicates(subset=['sha256'])
augmented_combo = utils.hashfunctions.augmentAggregatedHashes(url, combined_hashes)
numeric_reputation_cols = [
'reputation_scannermatch',
'reputation_scannercount',
'reputation_threatlevel'
]
for col in numeric_reputation_cols:
if col in augmented_combo.columns:
augmented_combo[col] = pd.to_numeric(augmented_combo[col].replace('N/A', pd.NA), errors='coerce')
augmented_combo = augmented_combo.rename(columns={'publisher_x': 'publisher'})
augmented_combo = augmented_combo[['sha256', 'publisher', 'description', 'productname', 'productversion',
'reputation_lastseen', 'reputation_scannermatch', 'reputation_scannercount',
'reputation_status', 'reputation_threatlevel', 'reputation_threatname',
'reputation_timestamp']]
augmented_combo = augmented_combo.sort_values(by=['publisher', 'description', 'productname'])
augmented_combo.to_parquet(f"parquet\\combined_hashlist_{first_policy}_{second_policy}.parquet", index=False)
del combined_hashes
del augmented_combo
gc.collect()
print(ct.colorText("Hash reputation info added to dataframe", "green"))
utils.hashfunctions.combineHashes(url, first_policy, second_policy)
if not os.path.exists(f"parquet\\hashes_rep_unknown_{first_policy}_{second_policy}.parquet") and not os.path.exists(f"parquet\\hashes_rep_good_{first_policy}_{second_policy}.parquet") and not os.path.exists(f"parquet\\hashes_rep_bad_{first_policy}_{second_policy}.parquet"):
# Categorize the hashes
categorized = utils.hashfunctions.categorizeHashes(
utils.hashfunctions.categorizeHashes(
first_policy,
second_policy,
pd.read_parquet(f"parquet\\combined_hashlist_{first_policy}_{second_policy}.parquet"),
threat_tolerance_constant,
bad_publisher_list,
pups
)
categorized[0].to_parquet(f"parquet\\hashes_rep_unknown_{first_policy}_{second_policy}.parquet", index=False)
categorized[1].to_parquet(f"parquet\\hashes_rep_good_{first_policy}_{second_policy}.parquet", index=False)
categorized[2].to_parquet(f"parquet\\hashes_rep_bad_{first_policy}_{second_policy}.parquet", index=False)
del categorized
gc.collect()
if not os.path.exists(f"parquet\\condensed_executions_{first_policy}_{second_policy}.parquet"):
# Condense execution history
try:
exe1 = pd.read_parquet(f"parquet\\execution_history_{first_policy}.parquet")
utils.pathfunctions.inspect_parquet(f"parquet\\execution_history_{first_policy}.parquet")
if not exe1.empty:
print()
else:
print("⚠️ First dataframe is empty.")
except Exception as e:
print(f"❌ Error reading first Parquet file: {e}")
try:
exe2 = pd.read_parquet(f"parquet\\execution_history_{second_policy}.parquet")
utils.pathfunctions.inspect_parquet(f"parquet\\execution_history_{second_policy}.parquet")
if not exe2.empty:
print()
else:
print("⚠️ Second dataframe is empty.")
except Exception as e:
print(f"❌ Error reading second Parquet file: {e}")
if not exe1.empty and not exe2.empty:
condensed_combo = pd.concat([exe1, exe2], ignore_index=True)
print(f"✅ Combined {len(condensed_combo)} hashes.")
elif exe1.empty:
condensed_combo = exe2
elif exe2.empty:
condensed_combo = exe1
else:
print("⚠️ No valid dataframes to combine.")
condensed_combo.to_parquet(f"parquet\\condensed_executions_{first_policy}_{second_policy}.parquet", index=False)
del condensed_combo
gc.collect()
utils.hashfunctions.condenseExecutions(first_policy,second_policy)
if os.path.exists(f"parquet\\hashes_rep_unknown_{first_policy}_{second_policy}.parquet") & os.path.exists(f"parquet\\hashes_rep_good_{first_policy}_{second_policy}.parquet") & os.path.exists(f"parquet\\hashes_rep_bad_{first_policy}_{second_policy}.parquet"):
utils.hashfunctions.divideSortedHashExecutions(first_policy,second_policy,pups)
utils.hashfunctions.combineHashAndHist(f"parquet\\hashes_rep_unknown_{first_policy}_{second_policy}.parquet", first_policy, second_policy)
utils.hashfunctions.combineHashAndHist(f"parquet\\hashes_rep_good_{first_policy}_{second_policy}.parquet", first_policy, second_policy)
utils.hashfunctions.combineHashAndHist(f"parquet\\hashes_rep_bad_{first_policy}_{second_policy}.parquet", first_policy, second_policy)
unknown = pd.read_parquet(f"parquet\\hashes_rep_unknown_{first_policy}_{second_policy}.parquet")
good = pd.read_parquet(f"parquet\\hashes_rep_good_{first_policy}_{second_policy}.parquet")
bad = pd.read_parquet(f"parquet\\hashes_rep_bad_{first_policy}_{second_policy}.parquet")
# Build regex pattern once
pattern = utils.pathfunctions.regulator(pups)
# Move matching rows from unknown and good to bad
bad = pd.concat([
bad,
unknown[unknown["filename"].str.contains(pattern, na=False)],
good[good["filename"].str.contains(pattern, na=False)]
], ignore_index=True)
# Remove matching rows from unknown and good
unknown = unknown[~unknown["filename"].str.contains(pattern, na=False)]
good = good[~good["filename"].str.contains(pattern, na=False)]
unknown.to_csv(f"needs_approved\\hashes_rep_unknown_{first_policy}_{second_policy}.csv",index=False)
good.to_csv(f"needs_approved\\hashes_rep_good_{first_policy}_{second_policy}.csv",index=False)
bad.to_csv(f"needs_approved\\hashes_rep_bad_{first_policy}_{second_policy}.csv",index=False)
ct.style_dataframe_dark(unknown, f"needs_approved\\hashes_rep_unknown_{first_policy}_{second_policy}.html")
ct.style_dataframe_dark(good, f"needs_approved\\hashes_rep_good_{first_policy}_{second_policy}.html")
ct.style_dataframe_dark(bad, f"needs_approved\\hashes_rep_bad_{first_policy}_{second_policy}.html")
elif choice == "3":
if os.path.exists(f"approved\\hashes_rep_unknown_{first_policy}_{second_policy}.csv") and os.path.exists(f"approved\\hashes_rep_good_{first_policy}_{second_policy}.csv"):
if not os.path.exists(f"parquet\\all_approved_hashes_{first_policy}_{second_policy}.parquet"):
df1 = tryToReadCSV(f"approved\\hashes_rep_unknown_{first_policy}_{second_policy}.csv")
df2 = tryToReadCSV(f"approved\\hashes_rep_good_{first_policy}_{second_policy}.csv")
all_approved_hashes = pd.concat([df1 , df2], ignore_index=True).sort_values(by=['filename'])
print(ct.colorText(f"Approved hash lists have been combined","green"))
all_approved_hashes.to_parquet(f"parquet\\all_approved_hashes_{first_policy}_{second_policy}.parquet", index=False)
del all_approved_hashes
gc.collect()
if not os.path.exists(f"parquet\\path_needs_approved_{first_policy}_{second_policy}.parquet"):
all_approved_hashes = pd.read_parquet(f"parquet\\all_approved_hashes_{first_policy}_{second_policy}.parquet")
print(ct.colorText(f"Beginning calculating longest common filepaths for path exceptions","green"))
haslcp = utils.pathfunctions.split_filepaths_grouped(all_approved_hashes)
haslcp.drop_duplicates()
forbidden = utils.pathfunctions.regulator(badpathparts, True)
forbidden_lcfp = haslcp["longestcfp"].str.contains(forbidden, na=False)
print(ct.colorText("Removing forbidden filepaths for path exceptions", "green"))
# Make a real DataFrame copy before modifying
lcp_not_forbidden = haslcp[~forbidden_lcfp].copy()
#For the review, drop down to only the columns we care, and then group by the commmon file path, consolidating and dropping dupes
lcp_not_forbidden_review = lcp_not_forbidden[['longestcfp', 'middle', 'filename_only', 'sha256']]
# Count unique sha256 per longestcfp
unique_sha_counts = lcp_not_forbidden_review.groupby('longestcfp')['sha256'].nunique().reset_index()
unique_sha_counts.columns = ['longestcfp', 'unique_sha256_count']
# Merge the count back into the original DataFrame
lcp_not_forbidden_review = lcp_not_forbidden_review.merge(unique_sha_counts, on='longestcfp', how='left')
lcp_not_forbidden_review = lcp_not_forbidden_review[lcp_not_forbidden_review['unique_sha256_count'] >= min_files_for_path]
lcp_not_forbidden_review.to_parquet(f"parquet\\path_needs_approved_{first_policy}_{second_policy}.parquet",index=False)
lcp_not_forbidden_review.to_csv(f"needs_approved\\path_needs_approved_{first_policy}_{second_policy}.csv",index=False)
utils.pathfunctions.generatePathReview(first_policy, second_policy, badpathparts, min_files_for_path)
else:
print(ct.colorText(f"Please manually approve hashes prior to this step","red"))
@@ -424,26 +210,7 @@ def menu_prepare_to_enforce():
if os.path.exists(f"approved\\path_needs_approved_{first_policy}_{second_policy}.csv"):
if not os.path.exists(f"parquet\\final_hash_approvals_{first_policy}_{second_policy}.parquet") and not os.path.exists(f"parquet\\final_path_exclusions_{first_policy}_{second_policy}.parquet"):
allhashes = pd.read_parquet(f"parquet\\all_approved_hashes_{first_policy}_{second_policy}.parquet")
pathexclusions = tryToReadCSV(f"approved\\path_needs_approved_{first_policy}_{second_policy}.csv")
pathexclusions.to_parquet(f"parquet\\final_path_exclusions_{first_policy}_{second_policy}.parquet", index=False)
allowbyhash = allhashes[~allhashes['sha256'].isin(pathexclusions['sha256'])]
allowbyhash.to_parquet(f"parquet\\final_hash_approvals_{first_policy}_{second_policy}.parquet", index=False)
allowbyhash.sort_values(by=["filename"])
ct.style_dataframe_dark(allowbyhash, f"preflight\\final_hash_approvals_{first_policy}_{second_policy}.html")
ct.style_dataframe_dark(pathexclusions, f"preflight\\final_path_exclusions_{first_policy}_{second_policy}.html")
del allowbyhash
del pathexclusions
gc.collect()
utils.hashfunctions.generatePreflights(first_policy, second_policy)
elif choice == "5":
@@ -467,47 +234,16 @@ def menu_prepare_to_enforce():
elif choice == "6":
if os.path.exists(f"preflight\\final_path_exclusions_{first_policy}_{second_policy}.html") and os.path.exists(f"preflight\\final_hash_approvals_{first_policy}_{second_policy}.html") and allowlist_parent_name != " " and allowlist_child_name != " " and destination_name != " ":
pathexclusions = pd.read_parquet(f"parquet\\final_path_exclusions_{first_policy}_{second_policy}.parquet")
allowbyhash = pd.read_parquet(f"parquet\\final_hash_approvals_{first_policy}_{second_policy}.parquet")
ct.areYouSure()
confirmation = input(ct.colorText("Type 'I AGREE' to continue: ","white"))
if confirmation.strip().upper() == "I AGREE":
print(ct.colorText("Proceeding with the code...", "yellow"))
print(ct.colorText(f"Adding path exclusions to {destination_name}", "yellow"))
pathexcludelist = pathexclusions['longestcfp'].unique().tolist()
# Regex to match a Windows drive letter at the start (e.g., C:\)
drive_letter_pattern = re.compile(r'^[a-zA-Z]:\\')
# Processed list
processed_paths = [
(path if drive_letter_pattern.match(path) else f"\\\\{path}") + "**"
for path in pathexcludelist
]
utils.policyfunctions.addPath(destination_id,processed_paths)
print(ct.colorText(f"Adding hashes to {allowlist_parent_name}", "yellow"))
allowlist_parenthashlist = allowbyhash[allowbyhash['reputation_status'] == 'KNOWN']['sha256'].unique().tolist()
utils.policyfunctions.addHash(allowlist_parent_id,allowlist_parenthashlist)
print(ct.colorText(f"Adding hashes to {allowlist_child_name}", "yellow"))
allowlist_childhashlist = allowbyhash[allowbyhash['reputation_status'] == 'UNKNOWN']['sha256'].unique().tolist()
utils.policyfunctions.addHash(allowlist_child_id, allowlist_childhashlist)
ct.locked()
exit()
else:
print(ct.colorText("Operation aborted. You MUST EXPLICITLY AGREE to proceed.", "red"))
break
utils.policyfunctions.sendToPolicy(
first_policy,
second_policy,
destination_name,
destination_id,
allowlist_parent_name,
allowlist_parent_id,
allowlist_child_name,
allowlist_child_id
)
elif choice == "Q":
break