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#!/usr/bin/env python3
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import os
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from ldap3 import Server, Connection, ALL, NTLM, ALL_ATTRIBUTES, ALL_OPERATIONAL_ATTRIBUTES, AUTO_BIND_NO_TLS, SUBTREE
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from ldap3.core.exceptions import LDAPCursorError
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import json
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import pandas as pd
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from io import StringIO
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from datetime import datetime, timedelta
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# from email.message import EmailMessage
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import smtplib
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from email.mime.multipart import MIMEMultipart
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from email.mime.text import MIMEText
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from tabulate import tabulate
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# global variables
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ad_audit_user = ""
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ad_audit_password = ""
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ad_server = ""
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ad_server2 = ""
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report_email = ""
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# development config flags
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detailed_output = True # results to stdout
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verbose = False # debug output
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inactive_enabled_onprem_ad_users_html_report = StringIO()
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def read_config():
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"""
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Read config file and check if it is valid
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:return:
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"""
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with open('config.json') as f:
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# parse the JSON file and assert the values
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try:
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d = json.load(f)
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assert 'admin' in d['user']
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assert isinstance(d['password'], str)
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assert isinstance(d['ad_server'], str)
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assert isinstance(d['ad_server_2'], str)
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assert isinstance(d['report_email'], str)
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except AssertionError:
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print("Config file is not valid")
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return 0
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# move the values to global variables
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global ad_audit_user
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global ad_audit_password
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global ad_server
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global ad_server_2
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global report_email
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ad_audit_user = d['user']
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ad_audit_password = d['password']
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ad_server = d['ad_server']
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ad_server_2 = d['ad_server_2']
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report_email = d['report_email']
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def _parse_date(date_string: str):
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"""
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Parse date string, internal function
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:param date_string:
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:return: datetime object
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"""
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# print(date_string)
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# https://bugs.python.org/msg169952 BUG in Python
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if ":" == date_string[-3:-2]:
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date_string = date_string[:-3] + date_string[-2:]
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# handle optional microseconds - https://strftime.org/ - %f if the parse fails (chain)
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try:
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return datetime.strptime(date_string, "%Y-%m-%d %H:%M:%S.%f%z")
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except ValueError:
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return datetime.strptime(date_string, "%Y-%m-%d %H:%M:%S%z")
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def send_email(message, subject="Inactive on-prem AD employee accounts (180d)", server='10.1.1.2',
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from_email='audit-tool@company.com'):
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"""
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Send email (to Slack, Exchange, etc.
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:param message:
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:param to_email:
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:param subject:
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:param server:
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:param from_email:
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:return:
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"""
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# msg = EmailMessage()
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msg = MIMEMultipart('alternative')
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msg['Subject'] = subject
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msg['From'] = from_email
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msg['To'] = "monitoring@company.com"
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message = '<font face="Courier New, Courier, monospace"><pre>' + message + '</pre></font>'
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part2 = MIMEText(message, 'html')
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# msg.set_content(message)
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msg.attach(part2)
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server = smtplib.SMTP(server)
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server.set_debuglevel(1)
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# server.login(from_email, ad_audit_password) # user & password
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server.send_message(msg)
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server.quit()
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print('successfully sent the mail.')
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def _resolve_ms_ad_status_code(code : int):
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"""
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Resolve the status code from MS AD
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:param code:
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:return:
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"""
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code_lookup_table = {
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512: "Enabled, PW policy enforced",
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514: "Disabled, PW policy enforced",
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544: "Enabled, PW policy NOT enforced",
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66048: "Enabled, PW policy NOT enforced"
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}
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if code in code_lookup_table:
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return code_lookup_table[code]
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else:
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return code
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def _connect_to_msaddcs():
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pass
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def analyze_ad_groups():
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# move global variables to local scope
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domain_name = 'company'
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domain_suffix = "int"
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server_name = ad_server
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failover_server_name = ad_server_2
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user_name = ad_audit_user
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password = ad_audit_password
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# Setup the connection to the AD server
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server = Server(server_name, port=636, use_ssl=True, get_info=ALL, connect_timeout=10, allowed_referral_hosts=[(failover_server_name, True)])
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conn = Connection(server, user='{}\\{}'.format(domain_name, user_name), password=password, authentication=NTLM,
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auto_bind=True)
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# Search for all empty security groups(, excluding dynamic groups)
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conn.search(
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search_base=f'dc={domain_name},dc={domain_suffix}',
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search_filter = '(&(objectClass=group)(groupType:1.2.840.113556.1.4.803:=2147483648))',
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# search_filter='(&(objectClass=group)(groupType:1.2.840.113556.1.4.803:=2147483648)(!(groupType:1.2.840.113556.1.4.803:=2147483648)))',
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search_scope=SUBTREE,
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attributes=['member']
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)
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# filer out dynamic groups manually (not supported by the search filter) based on the prefix
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empty_groups = [entry.entry_dn for entry in conn.entries if len(entry.member) == 0 and not any(entry.entry_dn.startswith(s) for s in ['CN=dyn', 'CN=app'])]
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# tabulate the results
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empty_ad_security_groups = pd.DataFrame({'Empty Security Groups': empty_groups})
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# Print the list of empty security groups
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print(empty_ad_security_groups)
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# Close the connection
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conn.unbind()
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def analyze_ad_admins():
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# move global variables to local scope
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domain_name = 'company'
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domain_suffix = "int"
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server_name = ad_server
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failover_server_name = ad_server_2
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user_name = ad_audit_user
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password = ad_audit_password
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# Setup the connection to the AD server
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server = Server(server_name, port=636, use_ssl=True, get_info=ALL, connect_timeout=10, allowed_referral_hosts=[(failover_server_name, True)])
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conn = Connection(server, user='{}\\{}'.format(domain_name, user_name), password=password, authentication=NTLM,
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auto_bind=True)
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# diff the results against the prior run (if available)
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if os.path.isfile('ad_admins.csv'):
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prior_ad_admins = pd.read_csv('ad_admins.csv')
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# Search for all users who are members of Domain Admins or Enterprise Admins group
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search_filter = f'(&(objectClass=user)(|(memberOf=CN=Domain Admins,CN=Users,DC={domain_name},DC={domain_suffix})(memberOf=CN=Enterprise Admins,CN=Users,DC=your_domain,DC=com)))'
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search_base = f'dc={domain_name},dc={domain_suffix}'
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search_scope = SUBTREE
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attributes = ['sAMAccountName', 'displayName']
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conn.search(search_base=search_base, search_filter=search_filter, search_scope=search_scope, attributes=attributes)
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admin_users = [entry.sAMAccountName.value for entry in conn.entries]
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# Print the list of admin users
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# tabulate the results
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ad_admin_users = pd.DataFrame({'AD Domain Admin Users': admin_users})
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print(ad_admin_users)
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# Close the connection
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conn.unbind()
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def analyze_ad_service_users():
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# move global variables to local scope
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domain_name = 'company'
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domain_suffix = "int"
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server_name = ad_server
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failover_server_name = ad_server_2
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user_name = ad_audit_user
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password = ad_audit_password
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# Setup the connection to the AD server
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server = Server(server_name, port=636, use_ssl=True, get_info=ALL, connect_timeout=10, allowed_referral_hosts=[(failover_server_name, True)])
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conn = Connection(server, user='{}\\{}'.format(domain_name, user_name), password=password, authentication=NTLM,
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auto_bind=True)
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# Search for all service users
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search_filter = '(servicePrincipalName=*)'
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# search_filter = '(&(objectClass=user)(servicePrincipalName=*)(!(objectCategory=computer))(userAccountControl:1.2.840.113556.1.4.803:=2))'
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search_base = f'dc={domain_name},dc={domain_suffix}'
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search_scope = SUBTREE
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attributes = ['sAMAccountName', 'displayName']
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conn.search(search_base=search_base, search_filter=search_filter, search_scope=search_scope, attributes=attributes)
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service_users = [entry.sAMAccountName.value for entry in conn.entries]
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# Print the list of service users
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# tabulate the results
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ad_service_users = pd.DataFrame({'AD Service Users': service_users})
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print(ad_service_users)
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# Close the connection
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conn.unbind()
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def analyze_ad_users():
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"""
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Query AD for users
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:param server_name:
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:param user_name:
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:param password:
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:return:
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"""
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# move global variables to local scope
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server_name = ad_server
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failover_server_name = ad_server_2
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user_name = ad_audit_user
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password = ad_audit_password
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# scope: employee, contractor, etc.
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domain_name = 'company'
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domain_suffix = "int"
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org_ou = "companynetwork"
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root_ou = "company"
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sub_ou = "users"
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# print header
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format_string = '{:25} {:>6} {:19} {:35} {}'
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print(format_string.format('User', 'Logins', 'Last Login', 'State', 'Description'))
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# global exception handling
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try:
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server = Server(server_name, port=636, use_ssl=True, get_info=ALL, connect_timeout=10, allowed_referral_hosts=[(failover_server_name, True)])
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conn = Connection(server, user='{}\\{}'.format(domain_name, user_name), password=password, authentication=NTLM,
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auto_bind=True)
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# ldap search query
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conn.search(
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search_base=f'OU={root_ou},OU={sub_ou},OU={org_ou},DC={domain_name},DC={domain_suffix}',
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search_filter='(objectClass=person)',
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search_scope=SUBTREE,
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attributes=[ALL_ATTRIBUTES, ALL_OPERATIONAL_ATTRIBUTES]
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)
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# check if we have any results, and if not exit the program
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if len(conn.entries) == 0:
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print("No results")
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return 0
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# list of object entries from LDAP query
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onprem_ad_user_list = []
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for e in conn.entries:
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# handle missing description
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try:
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desc = e.description
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except LDAPCursorError:
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desc = ""
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# lookup the status code from ms ad
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status_text = _resolve_ms_ad_status_code(e.userAccountControl.value)
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print(format_string.format(str(e.name), str(e.logonCount), str(e.lastLogon)[:19], str(status_text)[:35],
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desc))
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# convert the entry to JSON, and append it to the list as a dictionary
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onprem_ad_user_entry_dict = json.loads(e.entry_to_json())
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onprem_ad_user_list.append(onprem_ad_user_entry_dict)
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if verbose:
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print(e)
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def _tabularize_ad_user_data(onprem_ad_user_entry_dict : dict):
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# convert the list of dictionaries to a pandas dataframe
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# normalize the data, flatten the JSON
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onprem_ad_user_df = pd.json_normalize(onprem_ad_user_entry_dict)
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# due to issues with the processing in Elastic, we need to remove the following attributes
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onprem_ad_user_df.drop("attributes.msExchSafeSendersHash", inplace=True, axis=1)
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onprem_ad_user_df.drop("attributes.msExchBlockedSendersHash", inplace=True, axis=1)
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# fill in the lastLogonTimestamp with the lastLogon value if the lastLogonTimestamp is empty
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onprem_ad_user_df["attributes.lastLogonTimestamp"].fillna(onprem_ad_user_df["attributes.lastLogon"], inplace=True)
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# convert the date fields to datetime type, use UTC
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onprem_ad_user_df["attributes.lastLogonTimestamp"] = onprem_ad_user_df["attributes.lastLogonTimestamp"].apply(
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lambda x: _parse_date(str(x[0])))
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onprem_ad_user_df["attributes.lastLogonTimestamp"] = onprem_ad_user_df["attributes.lastLogonTimestamp"].apply(
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lambda x: pd.to_datetime(x, errors='coerce', utc=True))
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# check if last logon is 180 days ago, localize local timestamp to UTC for the comparison
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onprem_ad_user_df["inactive"] = onprem_ad_user_df["attributes.lastLogonTimestamp"].apply(
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lambda x: pd.Timestamp.now().tz_localize('UTC') - timedelta(days=180) > x)
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# simplify the account analysis by storing the user status in columns
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onprem_ad_user_df["inactive"] = onprem_ad_user_df["inactive"].astype(bool)
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onprem_ad_user_df["enabled"] = onprem_ad_user_df["attributes.userAccountControl"].apply(lambda x: 512 in x)
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return onprem_ad_user_df
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onprem_ad_users_df = _tabularize_ad_user_data(onprem_ad_user_list)
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def _filter_inactive_and_non_disabled_users(onprem_ad_users_df : pd.DataFrame):
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# filter for the inactive users AND enabled users
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inactive_ad_users_df = onprem_ad_users_df.loc[onprem_ad_users_df["inactive"] & onprem_ad_users_df["enabled"]]
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return inactive_ad_users_df
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inactive_onprem_ad_users_df = _filter_inactive_and_non_disabled_users(onprem_ad_users_df)
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# prepare the email report html part
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inactive_onprem_ad_users_count = inactive_onprem_ad_users_df.shape[0]
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# print the inactive users if detailed output is enabled
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if detailed_output and inactive_onprem_ad_users_count > 0:
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print()
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print("Inactive users enabled:")
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print(
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inactive_onprem_ad_users_df[["attributes.name", "attributes.lastLogonTimestamp"]]
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)
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inactive_ad_users_description_result = "Found " + str(inactive_onprem_ad_users_count) + \
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" inactive enabled users in on-prem AD."
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print(inactive_ad_users_description_result)
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if inactive_onprem_ad_users_count == 0:
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inactive_enabled_onprem_ad_users_html_report.write("No inactive enabled users found in on-prem AD.\r\n")
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print("Terminated successfully")
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exit(0)
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def _prepare_html_email_report_section_inactive_enabled_onprem_ad_users(inactive_ad_users_df : pd.DataFrame):
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inactive_enabled_onprem_ad_users_html_report.write("The following employee accounts are active in COMPANY " +
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"onprem AD, and have not logged in for 180 days:\r\n\r\n")
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inactive_enabled_onprem_ad_users_html_report.write(
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tabulate(
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inactive_ad_users_df[["attributes.name", "attributes.lastLogonTimestamp"]],
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headers=["Name", "Last Logon"],
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tablefmt="psql",
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showindex=False)
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)
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inactive_enabled_onprem_ad_users_html_report.write("\r\nThese may have been missed within the Joiner / Leaver process\r\n")
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return inactive_enabled_onprem_ad_users_html_report
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inactive_enabled_ad_users_html_report = _prepare_html_email_report_section_inactive_enabled_onprem_ad_users(inactive_onprem_ad_users_df)
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print("Report Mail prepared, sending email...")
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send_email(message=inactive_enabled_ad_users_html_report.getvalue())
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def __append_log_output_to_json_file(onprem_ad_users_df : pd.DataFrame):
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# serialize the dataframe to json and csv, keep lines for Elastic (append)
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log_output = StringIO()
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onprem_ad_users_df.to_json(path_or_buf=log_output, orient='records', lines=True)
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# append the JSON output to a file
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with open("data.json", "a+") as f:
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f.write(log_output.getvalue())
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__append_log_output_to_json_file(onprem_ad_users_df)
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if detailed_output:
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# overwrite the output to a file
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onprem_ad_users_df.to_csv('data.csv', sep=";", index=False)
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# global exception with failure message
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except Exception as e:
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print(e)
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return 0
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# close the connection, clean up
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finally:
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conn.unbind()
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if __name__ == '__main__':
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read_config()
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analyze_ad_users()
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# analyze_ad_groups()
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analyze_ad_admins()
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# analyze_ad_service_users()
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# send_email(message=inactive_enabled_onprem_ad_users_html_report.getvalue())
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Reference in New Issue