Instance Created by Unusual User

Description

Detects the first time a user creates a new instance.


Use Case

Advanced Threat Detection

Category

Account Compromise, IAM Analytics, SaaS

Security Impact

The risk that this detection intends to reduce is the compromise of an IaaS environment, where all of a sudden instance creation occurs from a user that isn't known to provision accounts. Assuming that the user has not changed roles, and that new orchestration tools are not being used, this would suggest that credentials have been created or compromised, and are in control of an adversary. This could result in potential cost run-up or other activities.

Alert Volume

Medium (?)

SPL Difficulty

Medium

Journey

Stage 3

MITRE ATT&CK Tactics

Persistence
Privilege Escalation

MITRE ATT&CK Techniques

Valid Accounts

MITRE Threat Groups

APT18
APT28
APT3
APT32
APT33
APT39
APT41
Carbanak
Dragonfly 2.0
FIN10
FIN4
FIN5
FIN6
FIN8
Leviathan
Night Dragon
OilRig
PittyTiger
Soft Cell
Stolen Pencil
Suckfly
TEMP.Veles
Threat Group-1314
Threat Group-3390
menuPass

Kill Chain Phases

Actions on Objectives

Data Sources

Audit Trail
GCP
Azure
AWS

   How to Implement

Assuming you use the ubiquitous AWS, GCP, or Azure Add-ons for Splunk to pull these logs in, this search should work automatically for you without issue. While implementing, make sure you follow the best practice of specifying the index for your data.

   Known False Positives

This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over (or for the lookup cache feature, the first occurrence over whatever time period you built the lookup). But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.

For this use case, you probably don't care every time a new user starts creating instances in a large environment, but you may care when they change resources in sensitive environments. Smaller organizations with a limited number of admins would likely care the minute that a new account is created. For all organizations, having this data around for context or to aggregate risk is extremely useful!

   How To Respond

When this alert fires, call the user and see if they expected this behavior. If the user cannot attribute this activity, it is best to reset the keys and continue your investigation to see what occurred.

   Help

Instance Created by Unusual User Help

This example leverages the Detect New Values search assistant. Our example dataset is a collection of anonymized AWS CloudTrail logs, during which someone does something bad. Our live search looks for the same behavior using the very standardized index and sourcetype for AWS CloudTrail, GCP, or Azure, as detailed in How to Implement.

SPL for Instance Created by Unusual User

Demo Data

First we bring in our basic demo dataset. In this case, anonymized AWS CloudTrail logs. We're using a macro called Load_Sample_Log_Data to wrap around | inputlookup, just so it is cleaner for the demo data.
Then we filter for Instance Creation.
Here we use the stats command to calculate what the earliest and the latest time is that we have seen this combination of fields.
Next we calculate the most recent value in our demo dataset
We end by seeing if the earliest time we've seen this value is within the last day of the end of our demo dataset.

AWS Data

First we bring in our AWS CloudTrail logs, filtered for Instance Creation.
Here we use the stats command to calculate what the earliest and the latest time is that we have seen this combination of fields.
We end by seeing if the earliest time we've seen this value is within the last day.

GCP Data

First we bring in our GCP Audit logs, filtered for Instance Creation.
Here we use the stats command to calculate what the earliest and the latest time is that we have seen this combination of fields.
We end by seeing if the earliest time we've seen this value is within the last day.

Azure Data

First we bring in our Azure Audit logs. We weren't able to determine a difference between instance creation and instance modification, so this is the same SPL as Instance Modification by Unusual user, specifically for Azure.
Here we use the stats command to calculate what the earliest and the latest time is that we have seen this combination of fields.
We end by seeing if the earliest time we've seen this value is within the last day.

Screenshot of Demo Data