Detection: Steal or Forge Authentication Certificates Behavior Identified

Updated Date: 2024-05-26 ID: 87ac670e-bbfd-44ca-b566-44e9f835518d Author: Michael Haag, Splunk Type: Correlation Product: Splunk Enterprise Security

Description

The following analytic identifies potential threats related to the theft or forgery of authentication certificates. It detects when five or more analytics from the Windows Certificate Services story trigger within a specified timeframe. This detection leverages aggregated risk scores and event counts from the Risk data model. This activity is significant as it may indicate an ongoing attack aimed at compromising authentication mechanisms. If confirmed malicious, attackers could gain unauthorized access to sensitive systems and data, potentially leading to severe security breaches.

1
2| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime sum(All_Risk.calculated_risk_score) as risk_score, count(All_Risk.calculated_risk_score) as risk_event_count, values(All_Risk.annotations.mitre_attack.mitre_tactic_id) as annotations.mitre_attack.mitre_tactic_id, dc(All_Risk.annotations.mitre_attack.mitre_tactic_id) as mitre_tactic_id_count, values(All_Risk.annotations.mitre_attack.mitre_technique_id) as annotations.mitre_attack.mitre_technique_id, dc(All_Risk.annotations.mitre_attack.mitre_technique_id) as mitre_technique_id_count, values(All_Risk.tag) as tag, values(source) as source, dc(source) as source_count from datamodel=Risk.All_Risk where All_Risk.analyticstories="Windows Certificate Services" All_Risk.risk_object_type="system" by All_Risk.risk_object All_Risk.risk_object_type All_Risk.annotations.mitre_attack.mitre_tactic 
3| `drop_dm_object_name(All_Risk)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| where source_count >= 5 
7| `steal_or_forge_authentication_certificates_behavior_identified_filter`

Data Source

Name Platform Sourcetype Source Supported App
N/A N/A N/A N/A N/A

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
steal_or_forge_authentication_certificates_behavior_identified_filter search *
steal_or_forge_authentication_certificates_behavior_identified_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1649 Steal or Forge Authentication Certificates Credential Access
KillChainPhase.EXPLOITAITON
NistCategory.DE_AE
Cis18Value.CIS_10
APT29

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event False
This configuration file applies to all detections of type Correlation. These correlations will generate Notable Events.

Implementation

The Windows Certificate Services analytic story must have 5 or more analytics enabled. In addition, ensure data is being logged that is required. Modify the correlation as needed based on volume of noise related to the other analytics.

Known False Positives

False positives may be present based on automated tooling or system administrators. Filter as needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Steal or Forge Authentication Certificates Behavior Identified on $risk_object$. 72 80 90
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation ✅ Passing N/A N/A N/A
Unit ✅ Passing Dataset certs stash
Integration ✅ Passing Dataset certs stash

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: GitHub | Version: 2