Ianhelle/velociraptor provider 2023 05 19

docs/source/DataAcquisition.rst

@@ -29,6 +29,7 @@ Individual Data Environments
    data_acquisition/DataProv-Kusto-New
    data_acquisition/DataProv-Cybereason
    data_acquisition/DataProv-OSQuery
+   data_acquisition/DataProv-Velociraptor
 
 
 Built-in Data Queries

docs/source/api/msticpy.data.drivers.local_velociraptor_driver.rst

@@ -0,0 +1,7 @@
+msticpy.data.drivers.local\_velociraptor\_driver module
+=======================================================
+
+.. automodule:: msticpy.data.drivers.local_velociraptor_driver
+   :members:
+   :undoc-members:
+   :show-inheritance:

docs/source/api/msticpy.data.drivers.rst

@@ -21,6 +21,7 @@ Submodules
    msticpy.data.drivers.kusto_driver
    msticpy.data.drivers.local_data_driver
    msticpy.data.drivers.local_osquery_driver
+   msticpy.data.drivers.local_velociraptor_driver
    msticpy.data.drivers.mdatp_driver
    msticpy.data.drivers.mordor_driver
    msticpy.data.drivers.odata_driver

docs/source/api/msticpy.init.mp_plugins.rst

@@ -0,0 +1,7 @@
+msticpy.init.mp\_plugins module
+===============================
+
+.. automodule:: msticpy.init.mp_plugins
+   :members:
+   :undoc-members:
+   :show-inheritance:

docs/source/data_acquisition/DataProv-OSQuery.rst

@@ -7,7 +7,7 @@ The ``OSQuery`` data provider can read OSQuery log files
 and provide convenient query functions for each OSQuery "table"
 (or event type) contained in the logs.
 
-The provide can read in one or more log files, or multiple log files
+The provider can read in one or more log files, or multiple log files
 in multiple folders. The files are read, converted to pandas
 DataFrames and grouped by table/event. In addition, date fields
 within the data are converted to pandas Timestamp format.
@@ -16,7 +16,7 @@ within the data are converted to pandas Timestamp format.
 
     qry_prov = mp.QueryProvider("OSQueryLogs", data_paths=["~/my_logs"])
     qry_prov.connect()
-    df_processes = qry_prov.processes()
+    df_processes = qry_prov.os_query.processes()
 
 The query provider query functions will ignore parameters and do
 no further filtering. You can use pandas to do additional filtering

docs/source/data_acquisition/DataProv-Velociraptor.rst

@@ -0,0 +1,167 @@
+The Velociraptor provider
+=========================
+
+:py:mod:`Velociraptor driver documentation<msticpy.data.drivers.local_velociraptor_driver>`
+
+The ``Velociraptor`` data provider can read Velociraptor
+offline collection log files (see
+`Velociraptor Offline Collection <https://docs.velociraptor.app/docs/offline_triage/#offline-collections>`__)
+and provide convenient query functions for each data set
+in the output logs.
+
+The provider can read files from one or more hosts, stored in
+in separate folders. The files are read, converted to pandas
+DataFrames and grouped by table/event. Multiple log files of the
+same type (when reading in data from multiple hosts) are concatenated
+into a single DataFrame.
+
+.. code::ipython3
+
+    qry_prov = mp.QueryProvider("Velociraptor", data_paths=["~/my_logs"])
+    qry_prov.connect()
+    df_processes = qry_prov.velociraptor.Windows_Forensics_ProcessInfo()
+
+The query provider query functions will ignore parameters and do
+no further filtering. You can use pandas to do additional filtering
+and sorting of the data, or use it directly with other MSTICPy
+functionality.
+
+.. note:: The examples used in this document were from data
+    provided by Blue Team Village at Defcon 30. You can find
+    this data at the
+    `Project-Obsidian-DC30 GitHub <https://github.com/blueteamvillage/Project-Obsidian-DC30>`__
+    and more about
+    `Project Obsidian <https://media.blueteamvillage.org/DC30/Obsidian/>`__
+    here.
+
+Velociraptor Configuration
+--------------------------
+
+You can (optionally) store your connection details in *msticpyconfig.yaml*,
+instead of supplying the ``data_paths`` parameter to
+the ``QueryProvider`` class.
+
+For more information on using and configuring *msticpyconfig.yaml* see
+:doc:`msticpy Package Configuration <../getting_started/msticpyconfig>`
+and :doc:`MSTICPy Settings Editor<../getting_started/SettingsEditor>`
+
+The Velociraptor settings in the file should look like the following:
+
+.. code:: yaml
+
+    DataProviders:
+        ...
+        Velociraptor:
+            data_paths:
+                - /home/user1/sample_data
+                - /home/shared/sample_data
+
+
+Expected log file format
+------------------------
+
+The log file format must be a text file of JSON records. An example
+is shown below
+
+.. parsed-literal::
+
+    {"Pid":1664,"Ppid":540,"Name":"spoolsv.exe","Path":"C:\\Windows\\System32\\spoolsv.exe","CommandLine":"C:\\Windows\\System32\\spoolsv.exe","Hash":{"MD5":"c111e3d38c71808a8289b0e49db40c96","SHA1":"e56df979d776fe9e8c3b84e6fef8559d6811898d","SHA256":"0ed0c6f4ddc620039f05719d783585d69f03d950be97b49149d4addf23609902"},"Username":"NT AUTHORITY\\SYSTEM","Authenticode":{"Filename":"C:\\Windows\\System32\\spoolsv.exe","ProgramName":"Microsoft Windows","PublisherLink":null,"MoreInfoLink":"http://www.microsoft.com/windows","SerialNumber":"33000002ed2c45e4c145cf48440000000002ed","IssuerName":"C=US, ST=Washington, L=Redmond, O=Microsoft Corporation, CN=Microsoft Windows Production PCA 2011","SubjectName":"C=US, ST=Washington, L=Redmond, O=Microsoft Corporation, CN=Microsoft Windows","Timestamp":null,"Trusted":"trusted","_ExtraInfo":{"Catalog":"C:\\Windows\\system32\\CatRoot\\{F750E6C3-38EE-11D1-85E5-00C04FC295EE}\\Package_6350_for_KB5007192~31bf3856ad364e35~amd64~~10.0.1.8.cat"}},"Family":"IPv4","Type":"TCP","Status":"LISTEN","Laddr.IP":"0.0.0.0","Laddr.Port":49697,"Raddr.IP":"0.0.0.0","Raddr.Port":0,"Timestamp":"2022-02-12T19:35:45Z"}
+    {"Pid":548,"Ppid":416,"Name":"lsass.exe","Path":"C:\\Windows\\System32\\lsass.exe","CommandLine":"C:\\Windows\\system32\\lsass.exe","Hash":{"MD5":"93212fd52a9cd5addad2fd2a779355d2","SHA1":"49a814f72292082a1cfdf602b5e4689b0f942703","SHA256":"95888daefd187fac9c979387f75ff3628548e7ddf5d70ad489cf996b9cad7193"},"Username":"NT AUTHORITY\\SYSTEM","Authenticode":{"Filename":"C:\\Windows\\System32\\lsass.exe","ProgramName":"Microsoft Windows","PublisherLink":null,"MoreInfoLink":"http://www.microsoft.com/windows","SerialNumber":"33000002f49e469c54137b85e00000000002f4","IssuerName":"C=US, ST=Washington, L=Redmond, O=Microsoft Corporation, CN=Microsoft Windows Production PCA 2011","SubjectName":"C=US, ST=Washington, L=Redmond, O=Microsoft Corporation, CN=Microsoft Windows Publisher","Timestamp":null,"Trusted":"trusted","_ExtraInfo":null},"Family":"IPv4","Type":"TCP","Status":"LISTEN","Laddr.IP":"0.0.0.0","Laddr.Port":49722,"Raddr.IP":"0.0.0.0","Raddr.Port":0,"Timestamp":"2022-02-12T19:35:54Z"}
+    {"Pid":540,"Ppid":416,"Name":"services.exe","Path":"C:\\Windows\\System32\\services.exe","CommandLine":"C:\\Windows\\system32\\services.exe","Hash":{"MD5":"fefc26105685c70d7260170489b5b520","SHA1":"d9b2cb9bf9d4789636b5fcdef0fdbb9d8bc0fb52","SHA256":"930f44f9a599937bdb23cf0c7ea4d158991b837d2a0975c15686cdd4198808e8"},"Username":"NT AUTHORITY\\SYSTEM","Authenticode":{"Filename":"C:\\Windows\\System32\\services.exe","ProgramName":"Microsoft Windows","PublisherLink":null,"MoreInfoLink":"http://www.microsoft.com/windows","SerialNumber":"33000002a5e1a081b7c895c0ed0000000002a5","IssuerName":"C=US, ST=Washington, L=Redmond, O=Microsoft Corporation, CN=Microsoft Windows Production PCA 2011","SubjectName":"C=US, ST=Washington, L=Redmond, O=Microsoft Corporation, CN=Microsoft Windows Publisher","Timestamp":null,"Trusted":"trusted","_ExtraInfo":null},"Family":"IPv4","Type":"TCP","Status":"LISTEN","Laddr.IP":"0.0.0.0","Laddr.Port":49728,"Raddr.IP":"0.0.0.0","Raddr.Port":0,"Timestamp":"2022-02-12T19:35:57Z"}
+
+
+The columns in each JSON will be used to create the pandas DataFrame columns.
+
+
+Using the Velociraptor provider
+-------------------------------
+
+To use the Velociraptor provider you need to create an QueryProvider
+instance, passing the string "VelociraptorLogs" as the ``data_environment``
+parameter. If you have not configured ``data_paths`` in msticpyconfig.yaml,
+you also need to add the ``data_paths`` parameter to specify
+specific folders or files that you want to read.
+
+.. code::ipython3
+
+    qry_prov = mp.QueryProvider("VelociraptorLogs", data_paths=["~/my_logs"])
+
+Calling the ``connect`` method triggers the provider to register the paths of the
+log files to be read (although the log files are not read and parsed
+until the related query is run - see below).
+
+.. code::ipython3
+
+    qry_prov.connect()
+
+
+
+Listing Velociraptor tables
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Until you run ``connect`` no queries will be available. After running
+``connect`` you can list the available queries using the ``list_queries``
+
+.. code:: ipython3
+
+    qry_prov.list_queries()
+
+.. parsed-literal::
+
+    ['velociraptor.Custom_Windows_NetBIOS',
+    'velociraptor.Custom_Windows_Patches',
+    'velociraptor.Custom_Windows_Sysinternals_PSInfo',
+    'velociraptor.Custom_Windows_Sysinternals_PSLoggedOn',
+    'velociraptor.Custom_Windows_System_Services',
+    'velociraptor.Windows_Applications_Chrome_Cookies',
+    'velociraptor.Windows_Applications_Chrome_Extensions',
+    'velociraptor.Windows_Applications_Chrome_History',
+    'velociraptor.Windows_Applications_Edge_History',
+    'velociraptor.Windows_Forensics_Lnk',
+    'velociraptor.Windows_Forensics_Prefetch',
+    'velociraptor.Windows_Forensics_ProcessInfo',
+    'velociraptor.Windows_Forensics_Usn',
+    ...]
+
+Querying Velociraptor table schema
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+The schema of the log tables is built by sampling the first record
+from each log file type, so is relatively fast to retrieve even
+if you have large numbers and sizes of logs.
+
+.. code:: ipython3
+
+    vc_prov.schema["Windows_Network_InterfaceAddresses"]
+
+.. parsed-literal::
+
+    {'Index': 'int64',
+    'MTU': 'int64',
+    'Name': 'object',
+    'HardwareAddr': 'object',
+    'Flags': 'int64',
+    'IP': 'object',
+    'Mask': 'object'}
+
+Running a Velociraptor query
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Each query returns a pandas DataFrame retrieved
+from the logs of that type (potentially containing records from
+multiple hosts depending on the ``data_paths`` you specified).
+
+.. code:: python3
+
+    qry_prov.vc_prov.velociraptor.Windows_Forensics_ProcessInfo()
+
+
+====  ===========  ================  =====  ===============================  ================================================================  ====================  ===================================
+  ..  Name         PebBaseAddress      Pid  ImagePathName                    CommandLine                                                       CurrentDirectory      Env
+====  ===========  ================  =====  ===============================  ================================================================  ====================  ===================================
+  10  LogonUI.exe  0x95bd3d2000        804  C:\Windows\system32\LogonUI.exe  "LogonUI.exe" /flags:0x2 /state0:0xa3b92855 /state1:0x41c64e6d    C:\Windows\system32\  {'ALLUSERSPROFILE': 'C:\\ProgramD..
+  11  dwm.exe      0x6cf4351000        848  C:\Windows\system32\dwm.exe      "dwm.exe"                                                         C:\Windows\system32\  {'ALLUSERSPROFILE': 'C:\\ProgramD..
+  12  svchost.exe  0x6cd64d000         872  C:\Windows\System32\svchost.exe  C:\Windows\System32\svchost.exe -k termsvcs                       C:\Windows\system32\  {'ALLUSERSPROFILE': 'C:\\ProgramD..
+  13  svchost.exe  0x7d18e99000        912  C:\Windows\System32\svchost.exe  C:\Windows\System32\svchost.exe -k LocalServiceNetworkRestricted  C:\Windows\system32\  {'ALLUSERSPROFILE': 'C:\\ProgramD..
+  14  svchost.exe  0x5c762eb000        920  C:\Windows\system32\svchost.exe  C:\Windows\system32\svchost.exe -k LocalService                   C:\Windows\system32\  {'ALLUSERSPROFILE': 'C:\\ProgramD..
+====  ===========  ================  =====  ===============================  ================================================================  ====================  ===================================

docs/source/data_acquisition/DataProviders.rst

@@ -85,7 +85,7 @@ would only use this parameter if you were building your own
 data driver backend, which is not common.
 
 2. You can choose to import additional queries from a custom
-query directory (see `Creating new queries`_ for more
+query directory (see :doc:`../extending/Queries` for more
 details) with:
 
 .. code:: ipython3
@@ -494,7 +494,7 @@ for Timedelta in the
 .. warning:: There are some important caveats to this feature.
 
    1. It currently only works with pre-defined queries (including ones
-      that you may create and add yourself, see `Creating new queries`_
+      that you may create and add yourself, see :doc:`../extending/Queries`
       below). It does not work with `Running an ad hoc query`_
    2. If the query contains joins, the joins will only happen within
       the time ranges of each subquery.
@@ -512,7 +512,7 @@ Dynamically adding new queries
 You can use the :py:meth:`msticpy.data.core.data_providers.QueryProvider.add_query`
 to add parameterized queries from a notebook or script. This
 let you use temporary parameterized queries without having to
-add them to a YAML file (as described in `Creating new queries`_).
+add them to a YAML file (as described in :doc:`../extending/Queries`).
 
 get_host_events
 

msticpy/data/core/query_defns.py

@@ -91,6 +91,7 @@ class DataEnvironment(Enum):
     AzureSentinel = 1  # alias of LogAnalytics
     LogAnalytics = 1
     Kusto = 2
+    AzureDataExplorer = 2  # alias of Kusto
     AzureSecurityCenter = 3
     MSGraph = 4
     SecurityGraph = 4
@@ -106,8 +107,11 @@ class DataEnvironment(Enum):
     Cybereason = 12
     Elastic = 14
     OSQueryLogs = 15
+    OSQuery = 15
     MSSentinel_New = 16
     Kusto_New = 17
+    VelociraptorLogs = 18
+    Velociraptor = 18
 
     @classmethod
     def parse(cls, value: Union[str, int]) -> "DataEnvironment":

msticpy/data/drivers/__init__.py

@@ -34,6 +34,10 @@
     DataEnvironment.Elastic: ("elastic_driver", "ElasticDriver"),
     DataEnvironment.MSSentinel_New: ("azure_monitor_driver", "AzureMonitorDriver"),
     DataEnvironment.Kusto_New: ("azure_kusto_driver", "AzureKustoDriver"),
+    DataEnvironment.VelociraptorLogs: (
+        "local_velociraptor_driver",
+        "VelociraptorLogDriver",
+    ),
 }
 
 CUSTOM_PROVIDERS: Dict[str, type] = {}

msticpy/data/drivers/azure_kusto_driver.py

@@ -162,7 +162,7 @@ def __init__(self, connection_str: Optional[str] = None, **kwargs):
         self._strict_query_match = kwargs.get("strict_query_match", False)
         self._kusto_settings: Dict[str, Dict[str, KustoConfig]] = _get_kusto_settings()
         self._default_database: Optional[str] = None
-        self.current_connection: Optional[str] = connection_str
+        self._current_connection: Optional[str] = connection_str
         self._current_config: Optional[KustoConfig] = None
         self.client: Optional[KustoClient] = None
         self._az_auth_types: Optional[List[str]] = None
@@ -189,6 +189,18 @@ def _set_public_attribs(self):
             "set_database": self.set_database,
         }
 
+    @property
+    def current_connection(self) -> Optional[str]:
+        """Return current connection string or URI."""
+        if self._current_connection:
+            return self._current_connection
+        return self.cluster_uri
+
+    @current_connection.setter
+    def current_connection(self, value: str):
+        """Set current connection string or URI."""
+        self._current_connection = value
+
     @property
     def cluster_uri(self) -> str:
         """Return current cluster URI."""
@@ -318,6 +330,7 @@ def connect(self, connection_str: Optional[str] = None, **kwargs):
             kusto_cs = self._get_connection_string_for_cluster(self._current_config)
         else:
             logger.info("Using connection string %s", connection_str)
+            self._current_connection = connection_str
             kusto_cs = connection_str
 
         self.client = KustoClient(kusto_cs)