Investigate Trojan Alerts in Seconds with SentinelOne, VirusTotal, and Azure Active Directory

In this post, we’ll be using SentinelOne, VirusTotal, and Azure Active Directory to investigate and respond to a potential trojan virus. SentinelOne provides deep enrichment on the endpoint, VirusTotal will tell us if the file has been marked as malicious by the wider community, and Azure Active Directory will give us more information on the user involved. We will also use Azure AD to reset the user’s sign-in session.

The alert we’ll be reviewing was generated by SentinelOne. Here we can see key details extracted from the alert and mapped to D3’s system fields. This normalization lets you analyze artifacts between different tools in your environment. The artifacts we’re most interested in are the agent id, threat id, file hash, and the affected user.

SentinelOne alert details mapped to D3's system fields

SentinelOne has also included MITRE TTPs in the original alert. D3 automatically adds them to our global Monitor dashboard so users can have a birds-eye view of the active threats in their environment:

MITRE TTPs generated by SentinelOne are automatically added to our global Monitor dashboard

The incident playbook executed on this alert has three main stages: enrichment, correlation and remediation.

D3's incident playbook at a glance

Playbook Stage: Enrichment

A look at the enrichment stage of the playbook

In the enrichment stage, we use SentinelOne, VirusTotal, and Azure Active Directory to collect relevant data on the agent, file hash, and user. The ‘link’ to the right of the task name means there is a nested playbook within it. By expanding on the SentinelOne task we can see three enrichment tasks: Get Agent Applications, Get Agent Info, and Get Threat Analysis.

An expanded view of three enrichment tasks using SentinelOne

Get Agent Applications shows us all of the applications installed on the agent. Nothing suspicious is found here:

Screenshot: Get Agent Applications in D3's Smart SOAR

Get Agent Info shows us any data on this agent that wasn’t included in the original alert.

Screenshot: Get Agent Info in D3's Smart SOAR

Get Threat Analysis uses the threat ID from the original alert and pulls in its classification, confidence level, verification type, initiated users, and more:

Screenshot: Get Threat Analysis in D3's Smart SOAR

From VirusTotal we can retrieve the reputation and risk levels for the MD5 hash. From the summary we can see that the risk level is “High”.

Screenshot: VirusTotal summary in D3 Smart SOAR

Within the Azure Active Directory enrichment task we can ingest activity logs on the user as well as general information on the account:

Screenshot: Azure Active Directory playbook in D3 Smart SOAR

From the activity logs we can see the category of action and whether or not it was successful:

Screenshot: User Activity Logs in D3 Smart SOAR

All of the enrichment data is displayed to the analyst in table format so they don’t have to comb through lines of raw data:

Screenshot: Consolidated enrichment data in D3 Smart SOAR

Screenshot: Consolidated enrichment data in D3 Smart SOAR

Playbook Stage: Correlation

Playbook Stage: Correlation in D3 Smart SOAR

In the correlation stage we search the SentinelOne database for any events that contain the threat ID associated with our trojan file and search D3’s incident database for other incidents that have this file included as an artifact.

Search for threat ID associated with our trojan file in SentinelOne

Link Artifact-related incidents with D3 Smart SOAR

The results show six events from SentinelOne and two related D3 incidents:

Playbook Stage: Remediation

In the remediation stage we have three options:

  1. Isolate the endpoint with SentinelOne.
  2. Revoke the user sign-in sessions, and
  3. Reset the user password.

Playbook Stage: Remediation in D3 Smart SOAR

For this case, we’ve revoked the user’s sign-in sessions and have skipped the reset and isolation commands.

Return on Time

As a reusable playbook, this can be executed any time a trojan alert from SentinelOne is ingested into D3. The remediation process can be controlled with manual check points or automated entirely. Typically, playbooks are used to automate the collection of contextual data to assist with the analyst’s decisions.

The enrichment and correlation stages took five seconds to run. When comparing this to the manual process of querying and consolidating data manually, for each alert, it’s easy to save 90% or more of your investigation time on each alert.

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Pierre Noujeim

Pierre is a cybersecurity analytics grad with hands-on NextGen SOAR experience. He has helped multinationals, MSSPs, and specialized enterprises boost efficiency and productivity with automation. Pierre has led product deployments and pre-sales engagements to implement NextGen SOAR for clients.