# -*- coding: utf-8 -*-
#
# privacyIDEA
# May 11, 2014 Cornelius Kölbel, info@privacyidea.org
# http://www.privacyidea.org
#
# This code is free software; you can redistribute it and/or
# modify it under the terms of the GNU AFFERO GENERAL PUBLIC LICENSE
# License as published by the Free Software Foundation; either
# version 3 of the License, or any later version.
#
# This code is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU AFFERO GENERAL PUBLIC LICENSE for more details.
#
# You should have received a copy of the GNU Affero General Public
# License along with this program. If not, see <http://www.gnu.org/licenses/>.
#
#
__doc__ = """The SQL Audit Module is used to write audit entries to an SQL
database.
The SQL Audit Module is configured like this:
PI_AUDIT_MODULE = privacyidea.lib.auditmodules.sqlaudit
PI_AUDIT_KEY_PRIVATE = tests/testdata/private.pem
PI_AUDIT_KEY_PUBLIC = tests/testdata/public.pem
Optional:
PI_AUDIT_SQL_URI = sqlite://
If the PI_AUDIT_SQL_URI is omitted the Audit data is written to the
token database.
"""
import logging
from privacyidea.lib.auditmodules.base import (Audit as AuditBase, Paginate)
from privacyidea.lib.crypto import Sign
from sqlalchemy import Table, MetaData, Column
from sqlalchemy import Integer, String, DateTime, asc, desc, and_
from sqlalchemy.orm import mapper
import datetime
import traceback
from sqlalchemy.exc import OperationalError
log = logging.getLogger(__name__)
try:
import matplotlib
MATPLOT_READY = True
matplotlib.use('Agg')
# We need to set the matplotlib backend before importing pandas with pyplot
from pandas import DataFrame
PANDAS_READY = True
# matplotlib is needed to plot
except Exception as exx:
log.warning(exx)
PANDAS_READY = False
metadata = MetaData()
TABLE_NAME = 'pidea_audit'
logentry = Table(TABLE_NAME,
metadata,
Column('id', Integer, primary_key=True),
Column('date', DateTime),
Column('signature', String(620)),
Column('action', String(50)),
Column('success', Integer),
Column('serial', String(20)),
Column('token_type', String(12)),
Column('user', String(20)),
Column('realm', String(20)),
Column('administrator', String(20)),
Column('action_detail', String(50)),
Column('info', String(50)),
Column('privacyidea_server', String(20)),
Column('client', String(20)),
Column('loglevel', String(12)),
Column('clearance_level', String(12))
)
class LogEntry(object):
def __init__(self,
action="",
success=0,
serial="",
token_type="",
user="",
realm="",
administrator="",
action_detail="",
info="",
privacyidea_server="",
client="",
loglevel="default",
clearance_level="default"
):
self.signature = ""
self.date = datetime.datetime.now()
self.action = action
self.success = success
self.serial = serial
self.token_type = token_type
self.user = user
self.realm = realm
self.administrator = administrator
self.action_detail = action_detail
self.info = info
self.privacyidea_server = privacyidea_server
self.client = client
self.loglevel = loglevel
self.clearance_level = clearance_level
mapper(LogEntry, logentry)
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
[docs]class Audit(AuditBase):
"""
This is the SQLAudit module, which writes the audit entries
to an SQL database table.
It requires the configuration parameters.
PI_AUDIT_SQL_URI
"""
def __init__(self, config=None):
self.name = "sqlaudit"
self.config = config or {}
self.audit_data = {}
self.sign_object = None
self.read_keys(self.config.get("PI_AUDIT_KEY_PUBLIC"),
self.config.get("PI_AUDIT_KEY_PRIVATE"))
# an Engine, which the Session will use for connection
# resources
connect_string = self.config.get("PI_AUDIT_SQL_URI",
self.config.get(
"SQLALCHEMY_DATABASE_URI"))
log.debug("using the connect string %s" % connect_string)
self.engine = create_engine(connect_string)
# create a configured "Session" class
Session = sessionmaker(bind=self.engine)
# create a Session
self.session = Session()
self.session._model_changes = {}
try:
metadata.create_all(self.engine)
except OperationalError as exx: # pragma: no cover
log.info("%r" % exx)
pass
def _create_filter(self, param):
"""
create a filter condition for the logentry
"""
conditions = []
for search_key in param.keys():
search_value = param.get(search_key)
if search_value.strip() != '':
# We do not search if the search value only consists of '*'
if search_value.strip('*') != '':
try:
search_value = search_value.replace('*', '%')
if '%' in search_value:
conditions.append(getattr(LogEntry,
search_key).like(search_value))
else:
conditions.append(getattr(LogEntry, search_key) ==
search_value)
except:
# The search_key was no search key but some
# bullshit stuff in the param
pass
# Combine them with or to a BooleanClauseList
filter_condition = and_(*conditions)
return filter_condition
[docs] def get_total(self, param, AND=True, display_error=True):
"""
This method returns the total number of audit entries
in the audit store
"""
count = 0
# if param contains search filters, we build the search filter
# to only return the number of those entries
filter_condition = self._create_filter(param)
try:
count = self.session.query(LogEntry.id)\
.filter(filter_condition)\
.count()
finally:
self.session.close()
return count
[docs] def log(self, param):
"""
Add new log details in param to the internal log data self.audit_data.
:param param: Log data that is to be added
:type param: dict
:return: None
"""
for k, v in param.items():
self.audit_data[k] = v
[docs] def add_to_log(self, param):
"""
Add new text to an existing log entry
:param param:
:return:
"""
for k, v in param.items():
self.audit_data[k] += v
[docs] def finalize_log(self):
"""
This method is used to log the data.
It should hash the data and do a hash chain and sign the data
"""
try:
le = LogEntry(action=self.audit_data.get("action"),
success=int(self.audit_data.get("success", 0)),
serial=self.audit_data.get("serial"),
token_type=self.audit_data.get("token_type"),
user=self.audit_data.get("user"),
realm=self.audit_data.get("realm"),
administrator=self.audit_data.get("administrator"),
action_detail=self.audit_data.get("action_detail"),
info=self.audit_data.get("info"),
privacyidea_server=self.audit_data.get("privacyidea_server"),
client=self.audit_data.get("client", ""),
loglevel=self.audit_data.get("log_level"),
clearance_level=self.audit_data.get("clearance_level")
)
self.session.add(le)
self.session.commit()
# Add the signature
if self.sign_object:
s = self._log_to_string(le)
sign = self.sign_object.sign(s)
le.signature = sign
self.session.merge(le)
self.session.commit()
except Exception as exx: # pragma: no cover
log.error("exception %r" % exx)
log.error("DATA: %s" % self.audit_data)
log.debug("%s" % traceback.format_exc())
self.session.rollback()
finally:
self.session.close()
# clear the audit data
self.audit_data = {}
[docs] def read_keys(self, pub, priv):
"""
Set the private and public key for the audit class. This is achieved by
passing the entries.
#priv = config.get("privacyideaAudit.key.private")
#pub = config.get("privacyideaAudit.key.public")
:param pub: Public key, used for verifying the signature
:type pub: string with filename
:param priv: Private key, used to sign the audit entry
:type priv: string with filename
:return: None
"""
self.sign_object = Sign(priv, pub)
def _check_missing(self, audit_id):
"""
Check if the audit log contains the entries before and after
the given id.
TODO: We can not check at the moment if the first or the last entries
were deleted. If we want to do this, we need to store some signed
meta information
1. Which one was the first entry. (use initialize_log)
2. Which one was the last entry.
"""
res = False
try:
id_bef = self.session.query(LogEntry.id
).filter(LogEntry.id ==
int(audit_id) - 1).count()
id_aft = self.session.query(LogEntry.id
).filter(LogEntry.id ==
int(audit_id) + 1).count()
# We may not do a commit!
# self.session.commit()
if id_bef and id_aft:
res = True
except Exception as exx: # pragma: no cover
log.error("exception %r" % exx)
log.debug("%s" % traceback.format_exc())
# self.session.rollback()
finally:
# self.session.close()
pass
return res
def _log_to_string(self, le):
"""
This function creates a string from the logentry so
that this string can be signed.
Note: Not all elements of the LogEntry are used to generate the
string (the Signature is not!), otherwise we could have used pickle
"""
s = "id=%s,date=%s,action=%s,succ=%s,serial=%s,t=%s,u=%s,r=%s,adm=%s,"\
"ad=%s,i=%s,ps=%s,c=%s,l=%s,cl=%s" % (le.id,
le.date,
le.action,
le.success,
le.serial,
le.token_type,
le.user,
le.realm,
le.administrator,
le.action_detail,
le.info,
le.privacyidea_server,
le.client,
le.loglevel,
le.clearance_level)
return s
def _get_logentry_attribute(self, key):
"""
This function returns the LogEntry attribute for the given key value
"""
sortname = {'number': LogEntry.id,
'action': LogEntry.action,
'success': LogEntry.success,
'serial': LogEntry.serial,
'date': LogEntry.date,
'token_type': LogEntry.token_type,
'user': LogEntry.user,
'realm': LogEntry.realm,
'administrator': LogEntry.administrator,
'action_detail': LogEntry.action_detail,
'info': LogEntry.info,
'privacyidea_server': LogEntry.privacyidea_server,
'client': LogEntry.client,
'loglevel': LogEntry.loglevel,
'clearance_level': LogEntry.clearance_level}
return sortname.get(key)
[docs] def csv_generator(self, param=None, user=None):
"""
Returns the audit log as csv file.
:param config: The current flask app configuration
:type config: dict
:param param: The request parameters
:type param: dict
:param user: The user, who issued the request
:return: None. It yields results as a generator
"""
logentries = self.session.query(LogEntry).all()
for le in logentries:
audit_dict = self.audit_entry_to_dict(le)
audit_list = audit_dict.values()
string_list = ["'%s'" % x for x in audit_list]
yield ",".join(string_list)+"\n"
def get_count(self, search_dict, timedelta=None, success=None):
# create filter condition
filter_condition = self._create_filter(search_dict)
conditions = [filter_condition]
if success is not None:
conditions.append(LogEntry.success == success)
if timedelta is not None:
conditions.append(LogEntry.date >= datetime.datetime.now() -
timedelta)
filter_condition = and_(*conditions)
log_count = self.session.query(LogEntry).filter(filter_condition).count()
return log_count
[docs] def search(self, search_dict, page_size=15, page=1, sortorder="asc"):
"""
This function returns the audit log as a Pagination object.
"""
page = int(page)
page_size = int(page_size)
paging_object = Paginate()
paging_object.page = page
paging_object.total = self.get_total(search_dict)
if page > 1:
paging_object.prev = page - 1
if paging_object.total > (page_size * page):
paging_object.next = page + 1
auditIter = self.search_query(search_dict, page_size=page_size,
page=page, sortorder=sortorder)
try:
le = auditIter.next()
while le:
# Fill the list
paging_object.auditdata.append(self.audit_entry_to_dict(le))
le = auditIter.next()
except StopIteration:
pass
return paging_object
[docs] def search_query(self, search_dict, page_size=15, page=1, sortorder="asc",
sortname="number"):
"""
This function returns the audit log as an iterator on the result
"""
logentries = None
try:
limit = int(page_size)
offset = (int(page) - 1) * limit
# create filter condition
filter_condition = self._create_filter(search_dict)
if sortorder == "desc":
logentries = self.session.query(LogEntry).filter(
filter_condition).order_by(
desc(self._get_logentry_attribute("number"))).limit(
limit).offset(offset)
else:
logentries = self.session.query(LogEntry).filter(
filter_condition).order_by(
asc(self._get_logentry_attribute("number"))).limit(
limit).offset(offset)
except Exception as exx: # pragma: no cover
log.error("exception %r" % exx)
log.debug("%s" % traceback.format_exc())
self.session.rollback()
finally:
self.session.close()
if logentries is None:
return iter([])
else:
return iter(logentries)
[docs] def get_dataframe(self,
start_time=datetime.datetime.now()
-datetime.timedelta(days=7),
end_time=datetime.datetime.now()):
"""
The Audit module can handle its data the best. This function is used
to return a pandas.dataframe with all audit data in the given time
frame.
This dataframe then can be used for extracting statistics.
:param start_time: The start time of the data
:type start_time: datetime
:param end_time: The end time of the data
:type end_time: datetime
:return: Audit data
:rtype: dataframe
"""
if not PANDAS_READY:
log.warning("If you want to use statistics, you need to install "
"python-pandas.")
return None
result = self.engine.execute("select * from %s where date "
"> '%s' and date < "
"'%s'"
% (TABLE_NAME, start_time, end_time))
rows = result.fetchall()
df = DataFrame(rows, columns=result.keys())
return df
[docs] def clear(self):
"""
Deletes all entries in the database table.
This is only used for test cases!
:return:
"""
self.session.query(LogEntry).delete()
self.session.commit()
def audit_entry_to_dict(self, audit_entry):
sig = self.sign_object.verify(self._log_to_string(audit_entry),
audit_entry.signature)
is_not_missing = self._check_missing(int(audit_entry.id))
# is_not_missing = True
audit_dict = {'number': audit_entry.id,
'date': audit_entry.date.isoformat(),
'sig_check': "OK" if sig else "FAIL",
'missing_line': "OK" if is_not_missing else "FAIL",
'action': audit_entry.action,
'success': audit_entry.success,
'serial': audit_entry.serial,
'token_type': audit_entry.token_type,
'user': audit_entry.user,
'realm': audit_entry.realm,
'administrator': audit_entry.administrator,
'action_detail': audit_entry.action_detail,
'info': audit_entry.info,
'privacyidea_server': audit_entry.privacyidea_server,
'client': audit_entry.client,
'log_level': audit_entry.loglevel,
'clearance_level': audit_entry.clearance_level
}
return audit_dict
