As security teams navigate the movement to remote work and the transition to cloud-hosted infrastructure, endpoint visibility remains a high priority for just about everyone. Whether we are monitoring a server in AWS or a remote employee’s laptop, cloud-native endpoint security platforms like CrowdStrike remain a vital part of our infrastructure.
However, the enhanced visibility and machine learning detections of a tool like CrowdStrike do have the potential to overwhelm our security operations centers with an overabundance of alerts. When these alerts pile up, analysts need a way to quickly gather more information related to the threat, determine the risk level, and respond immediately. That’s where an automation and orchestration tool comes in to save the day! Splunk Phantom is a SOAR tool that can orchestrate decisions and actions to more quickly investigate, triage, and respond to this high volume of alerts and reduce the manual burden of repetitive analysis.
The combination of Crowdstrike and Splunk Phantom together allows for a more smooth operational flow from detecting endpoint security alerts to operationalizing threat intelligence and automatically taking the first few response steps – all in a matter of seconds!
In this blog, I’ll walk you through an out-of-the-box playbook that you can set up in Phantom to triage malware detections from Crowdstrike and automate a variety of responses based on an informed decision by an analyst. This allows the analyst to skip the repetitive queries and jump into the investigation phase as soon as they see the alert. The playbook also uses the Custom Indicator of Compromise feature in CrowdStrike to correlate with previous infections related to the same malware and to tune future detections with false positive and true positive policies. This allows the analyst to not only respond more quickly to one alert in particular, but also to reduce future work by ignoring false positives and avoiding repeated analysis of the same malware.
This playbook walks through the steps that are performed automatically by Phantom to triage file hashes ingested from Crowdstrike.
As shown in the screenshot, there are a number of paths this playbook can take. The initial decision and filter ensure that the playbook is processing a detection with a SHA256 file hash. Next, the Custom Indicator table in CrowdStrike is queried to see if the hash represents a known file from a previous detection. If so, the bottom half of the playbook does a reduced workflow relying on the policy in place for that hash, allowing quarantine of the device if the hash is known malicious, and closing the event if the hash is known benign. The top half of the playbook does more investigation because the file hash is not a known quantity. The “hunt file” and “get process details” actions show other hosts in your environment with the same hash on disk and the behavior of other processes executing the same file. All of this information is summarized in the prompt and action widgets on the investigation page, allowing the analyst to make two decisions.
First, the analyst can ignore the indicator, create a false positive policy for the indicator (a policy of “none” in CrowdStrike), or create a true positive policy (a policy of “detect”). Second, the analyst can decide whether or not to immediately quarantine the endpoint, blocking all network traffic to and from, except for the configured allowlist of network addresses that can access the system during investigation. In CrowdStrike, the Configuration->Containment Policy page allows you to customize the quarantined device allowlist.
The video below walks through the deployment steps, how each block of the playbook works, and a demonstration of the playbook in use:
In order to get this playbook up and running you will just need to configure the CrowdStrike app on Phantom, then activate the playbook.
Here are the deployment steps shown in the video above:
As every analyst knows, there are endless different directions a malware investigation can go. As with any automated incident response, the best way to expand on this playbook is to see it in action for a trial period and keep a close feedback loop to add the most common manual actions that analysts are taking after its execution.
For example, if you have access to a threat intelligence platform such as VirusTotal, Recorded Future, ReversingLabs, or one of dozens of others that Phantom integrates with, it would just take a minute to add a few “file reputation” actions to this playbook. Similarly, a malware sandbox could provide a report on the behavior of the executable and compare it to similar executables.
Of course, querying Splunk could provide all sorts of useful supporting information, such as other similar command line executions across your environment, details about the network communications of the host around the time of the incident, and information about the assets and identities involved in the incident. With hundreds of apps and thousands of actions in Phantom, there are a wide range of possibilities to consider for endpoint alerts, and this playbook has just scratched the surface of those capabilities.
This blog is part of a series called “SOAR in Seconds” where our distinguished Splunk Phantom experts guide you through how to use out-of-the-box playbooks to automate repetitive tasks.
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Thanks!
Philip Royer
The Splunk platform removes the barriers between data and action, empowering observability, IT and security teams to ensure their organizations are secure, resilient and innovative.
Founded in 2003, Splunk is a global company — with over 7,500 employees, Splunkers have received over 1,020 patents to date and availability in 21 regions around the world — and offers an open, extensible data platform that supports shared data across any environment so that all teams in an organization can get end-to-end visibility, with context, for every interaction and business process. Build a strong data foundation with Splunk.