TOR Traffic
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.
Description
This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Network_Traffic
- Last Updated: 2020-07-22
- Author: David Dorsey, Splunk
- ID: ea688274-9c06-4473-b951-e4cb7a5d7a45
Annotations
ATT&CK
Kill Chain Phase
- Command and Control
NIST
- DE.CM
CIS20
- CIS 13
CVE
Search
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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.app=tor AND All_Traffic.action=allowed by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `drop_dm_object_name("All_Traffic")`
| `tor_traffic_filter`
Macros
The SPL above uses the following Macros:
tor_traffic_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- All_Traffic.app
- All_Traffic.action
- All_Traffic.src_ip
- All_Traffic.dest_ip
- All_Traffic.dest_port
How To Implement
In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated.
Known False Positives
None at this time
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | tbd |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
Test Dataset
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 2