Pretty HTML and beginnings of Destination Policy

AirlockTools.py

@@ -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'])
+				df3 = tryToReadCSV(f"manuallyapproved\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv")
-				print(df2['sha256'])
+				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"))
+			
 
 
 

utils/allowlist.py

@@ -17,8 +17,9 @@ import requests
 import json
 import os
 import time
-import utils.colortext as ct
+import utils.pretty as ct
 import ijson
+
 def pullPolicyExechistories(url, choice, policiesnames, outputjson: bool): 
     headers = {
         "X-APIKey": os.getenv('APIKEY')

utils/colortext.py

@@ -1,14 +0,0 @@
-
-def colorText(text: str, color: str) -> str:
-    colors = {
-        "red": "\033[91m",
-        "green": "\033[92m",
-        "yellow": "\033[93m",
-        "blue": "\033[94m",
-        "magenta": "\033[95m",
-        "cyan": "\033[96m",
-        "white": "\033[97m",
-		"reset": "\033[0m"
-    }
-    
-    return f"{colors.get(color, colors['reset'])}{text}{colors['reset']}"

utils/getdeviceevents.py

@@ -16,7 +16,7 @@ import datetime
 import requests
 import json
 import os
-import utils.colortext as ct
+import utils.pretty as ct
 
 def devicehistory(url, outputjson: bool):
 	endpoint = url + '/v1/getexechistory'

utils/hashfunctions.py

@@ -125,3 +125,19 @@ def categorizeHashes(aug_df: pd.DataFrame, threat_tolerance: int, untrusted_publ
     unapproved_df = df[~(mask_needsreview | mask_approved)]
 
     return needsreview_df, approved_df, unapproved_df
+
+def destinationbuilder(df, df2):
+    # Step 1: Explode the 'sha256' list in df2 to create one row per sha256 value
+    df_expanded = df.explode('sha256')
+
+    # Step 2: Create a new dataframe for the result
+    df_hashdestination = df_expanded.copy()
+
+    # Step 3: Populate the 'Destination Allowlist' column based on comparison with df3
+    df_hashdestination['Destination Allowlist'] = df_hashdestination['sha256'].apply(
+        lambda x: 'Parent Policy Baseline' if x in df2['sha256'].values else "Destination Policy Allowlist"
+    )
+
+    # Step 4: Return the new dataframe
+    return df_hashdestination
+

utils/pretty.py

@@ -0,0 +1,138 @@
+
+def colorText(text: str, color: str) -> str:
+    colors = {
+        "red": "\033[91m",
+        "green": "\033[92m",
+        "yellow": "\033[93m",
+        "blue": "\033[94m",
+        "magenta": "\033[95m",
+        "cyan": "\033[96m",
+        "white": "\033[97m",
+		"reset": "\033[0m"
+    }
+    
+    return f"{colors.get(color, colors['reset'])}{text}{colors['reset']}"
+
+def style_dataframe_dark(df, output_html_path=None, overwrite=True):
+    from datetime import datetime
+
+    # Get current date and filename for subtitle
+    today = datetime.now().strftime("%d %B %Y")  # Changed to "Day Month Year"
+    filename = output_html_path.replace('.html', '') if output_html_path else "Report"
+
+    dark_css = """
+    <style>
+    body {
+        background-color: #000000;
+        margin: 0;
+        padding: 0;
+        font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+        color: #f8f8f2;
+    }
+    .header {
+        text-align: center;
+        margin: 20px auto;
+        padding: 10px;
+        border-bottom: 2px solid #ffd700;
+        max-width: 95%;
+    }
+    .header h1 {
+        color: #ffd700;
+        margin: 0;
+        font-size: 32px;
+    }
+    .header p {
+        color: #00bfff;
+        margin: 5px 0 0 0;
+        font-size: 18px;
+    }
+    .table-container {
+        overflow-y: scroll;
+        margin: 0 auto;
+        width: 95%;
+        max-height: calc(80vh - 100px);
+        display: block;
+        border: 1px solid #3a3a4d;
+        margin-bottom: 0;
+    }
+    table {
+        border-collapse: collapse;
+        font-size: 14px;
+        background-color: #1e1e2f;
+        color: #f8f8f2;
+        width: max-content;
+    }
+    th, td {
+        border: 1px solid #3a3a4d;
+        text-align: left;
+        padding: 10px;
+        max-width: 300px;
+        word-wrap: break-word;
+        overflow-wrap: break-word;
+    }
+    /* First column: no wrap */
+    td:nth-child(1), th:nth-child(1) {
+        white-space: nowrap;
+        max-width: none !important;
+        word-wrap: normal !important;
+    }
+    th {
+        background-color: #2e2e40;
+        color: #ffd700;
+        position: sticky;
+        top: 0;
+        z-index: 10;
+    }
+    tr:nth-child(even) {
+        background-color: #262638;
+    }
+    tr:hover {
+        background-color: #33334d;
+        color: #00bfff;
+    }
+    /* Custom scrollbar styling */
+    .table-container::-webkit-scrollbar {
+        width: 12px;
+    }
+    .table-container::-webkit-scrollbar-track {
+        background: #1e1e2f;
+    }
+    .table-container::-webkit-scrollbar-thumb {
+        background-color: #3a3a4d;
+        border-radius: 6px;
+    }
+    </style>
+    """
+
+    header = f"""
+    <div class="header">
+        <h1>Airlock Tools</h1>
+        <p>{filename} - {today}</p>
+    </div>
+    """
+
+    html_table = df.to_html(index=False, escape=False)
+    styled_html = (
+        f"<html>\n"
+        f"<head><title>Airlock Tools Report</title></head>\n"
+        f"<body>\n"
+        f"{dark_css}\n"
+        f"{header}\n"
+        f"<div class='table-container'>\n"
+        f"  {html_table}\n"
+        f"</div>\n"
+        f"</body>\n"
+        f"</html>"
+    )
+    if output_html_path:
+        with open(output_html_path, "w", encoding="utf-8") as f:
+            f.write(styled_html)
+        print(f"✅ Styled table saved to '{output_html_path}'")
+    elif overwrite:
+        import tempfile
+        temp_path = tempfile.mktemp(suffix=".html")
+        with open(temp_path, "w", encoding="utf-8") as f:
+            f.write(styled_html)
+        print(f"✅ Styled table saved to temporary file: {temp_path}")
+    else:
+        return styled_html