:no_entry: THIS IS A DEPRECATED DETECTION

This detection has been marked deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported.

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Description

This detection identifies potential Pass the Token or Pass the Hash credential stealing. We detect the main side effect of these attacks, which is a transition from the dominant Kerberos logins to rare NTLM logins for a given user, as reported by a detination device.

  • Type: TTP
  • Product: Splunk Behavioral Analytics
  • Datamodel: Authentication
  • Last Updated: 2021-11-30
  • Author: Stanislav Miskovic, Splunk
  • ID: 82e76b80-5cdb-4899-9b43-85dbe777b36d

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1550 Use Alternate Authentication Material Defense Evasion, Lateral Movement
T1550.002 Pass the Hash Defense Evasion, Lateral Movement
Kill Chain Phase
  • Exploitation
NIST
  • PR.PT
  • PR.AT
  • PR.AC
  • PR.IP
CIS20
  • CIS 16
  • CIS 20
CVE 


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| from read_ssa_enriched_events() 
| where "Authentication" IN(_datamodels) 
| eval timestamp=parse_long(ucast(map_get(input_event, "_time"), "string", null)), dest_user=lower(ucast(map_get(input_event, "dest_user_primary_artifact"), "string", null)), dest_user_id=   ucast(map_get(input_event, "dest_user_id"), "string", null), dest_device_id=       ucast(map_get(input_event, "dest_device_id"), "string", null), signature_id=   lower(ucast(map_get(input_event, "signature_id"), "string", null)), authentication_method=  lower(ucast(map_get(input_event, "authentication_method"), "string", null)), event_id=ucast(map_get(input_event, "event_id"), "string", null)

| where signature_id = "4624" AND (authentication_method="ntlmssp" OR authentication_method="kerberos") AND dest_user_id != null AND dest_device_id != null

| eval isKerberos=if(authentication_method == "kerberos", 1, 0), isNtlm=if(authentication_method == "ntlmssp", 1, 0), timeNTLM=if(isNtlm > 0, timestamp, null)

| stats sum(isKerberos) as totalKerberos, sum(isNtlm)     as totalNtlm, min(timestamp)  as startTime, min(timeNTLM)   as startNTLMTime, max(timestamp)  as endTime, max(timeNTLM)   as endNTLMTime by dest_user_id, dest_user, dest_device_id, span(timestamp, 86400s)

| where NOT dest_user="-" AND totalKerberos > 0 AND totalNtlm > 0 AND endTime - startTime > 1800000 AND (totalKerberos > 10 * totalNtlm AND totalKerberos > 50)  AND (endTime - startTime) > 3 * (endNTLMTime - startNTLMTime)

| eval start_time=ucast(startNTLMTime, "long", null), end_time=ucast(endNTLMTime, "long", null), entities=mvappend(dest_user_id, dest_device_id), body=create_map(["event_id", event_id, "total_kerberos", totalKerberos, "total_ntlm", totalNtlm, "analysis_start_time", startTime, "analysis_end_time", endTime, "pth_start_time", startNTLMTime, "pth_end_time", endNTLMTime])

| into write_ssa_detected_events();

Macros

The SPL above uses the following Macros:

:information_source: potential_pass_the_token_or_hash_observed_at_the_destination_device_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
  • signature_id
  • dest_user
  • dest_user_id
  • dest_device_id
  • authentication_method

How To Implement

You must be ingesting Windows Security logs from endpoint devices, i.e., destinations of interest. Please make sure that event ID 4624 is being logged.

Known False Positives

Environments in which NTLM is used extremely rarely and for benign purposes (such as a rare use of SMB shares).

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
72.0 80 90 Potential lateral movement and credential stealing via Pass the Token or Pass the Hash techniques. Operation is performed via credentials of the account $dest_user_id$ and observed by the destination device $dest_device_id$

:information_source: 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: 3