THIS IS A EXPERIMENTAL DETECTION
This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.
By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Network_Sessions
- Last Updated: 2017-09-13
- Author: Bhavin Patel, Splunk
- ID: dcfd6b40-42f9-469d-a433-2e53f7489ff4
Kill Chain Phase
- CIS 13
1 2 3 4 5 6 7 8 9 10 | tstats `security_content_summariesonly` count from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.tag=dhcp by All_Sessions.dest_ip All_Sessions.dest_mac | dedup All_Sessions.dest_mac | `drop_dm_object_name("Network_Sessions")` |`drop_dm_object_name("All_Sessions")` | search NOT [ | inputlookup asset_lookup_by_str |rename mac as dest_mac | fields + dest_mac] | `detect_unauthorized_assets_by_mac_address_filter`
The SPL above uses the following Macros:
detect_unauthorized_assets_by_mac_address_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated.
Known False Positives
This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information.
Associated Analytic Story
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 2