As soon as the first indicator of compromise is located, the most common next step is to try to pivot from that indicator to find additional indicators or evidence on the network. While it is sometimes necessary to perform your own research to determine what additional indicators may be present, it is common to make use of previous research when looking for new indicators to hunt for.
This is especially true when dealing with an indicator of malicious software. Perhaps you have found a host communicating with an IP address known to be associated with a particular malware variant; the logical next step would be to search for communication with other IPs, domains and URLs the malware may be associated with, along with looking for the host-based activity the malware is known to use.
For example, suppose an IDS alerted on the IP address 144.202.87[.]106. A quick search on VirusTotal indicates that this IP address may be malicious, however, it does not provide much information which could be used to pivot to other indicators. So where does every good analyst turn at this point? Google, of course! A quick Google search for the IP address returns several results, including a blog post from MalwareBytes on the Hidden Bee miner.
Along with a detailed analysis of the Hidden Bee miner, the post also includes several other IP addresses and URLs which analysts observed in this attack. Now we have some data to pivot and hunt with!
This entire analysis from the MalwareBytes team can easily be added into DFLabs’ IncMan SOAR platform by copying and pasting the blog into the Additional Info section of the incident. In addition to allowing this information to be accessed by the working on this incident, adding this text to the Additional Info field has an additional advantage we have not yet discussed; Automatic Observable Harvesting.
When text is added to a field such as the Additional Info fields in IncMan, Automatic Observable Harvesting will automatically parse through the text and attempt to harvest observables from the unstructured text.
In the case of the Hidden Bee analysis from MalwareBytes, Automatic Observable Harvesting automatically harvested four IP addresses, a URL and a domain from the unstructured text and added them to the observables section.
While six observables may not take long to manually enter into the platform, it is not uncommon to find detailed malware analysis that contains dozens of IP addresses, hash values, domains, and other observables. Entering this many observables into IncMan manually in order to take advantage of IncMan’s automation and orchestration features on the new observables would be a time-consuming process. Automatic Observable Harvesting performs this task automatically.
Once these new observables are added into IncMan, analysts can take advantage of IncMan’s automation and orchestration features to begin performing additional enrichment on the observables, as well as searching across any internal data sources for evidence of the observables and blocking them if needed.
DFLabs is excited to announce the latest release of its industry-leading Security Orchestration, Automation and Response platform, IncMan version 4.3. Solving customer’s problems and adding value to our customer’s security programs is one of our core goals here at DFLabs and this is reflected in our 4.3 release with over 100 enhancements, additions, and fixes; many suggested by customers, all designed to make the complex task of responding to potential security incidents faster, easier and more efficient.
IncMan 4.3 includes many new bidirectional integrations from a variety of product categories including threat intelligence, malware analysis, ticket management and endpoint protection, chosen to broaden the orchestration and automation capabilities of our customers. These new bidirectional integrations include:
- Atlassian Jira
- BMC Remedy
- Carbon Black Defense
- Cuckoo Sandbox
- McAfee Advanced Threat Defense
- McAfee Threat Intelligence Exchange
- Recorded Future
With IncMan 4.3, we have also greatly enhanced the flexibility of our R3 Rapid Response Runbooks with the addition of two new decision nodes; Filter and User Choice. Filter nodes allow users to further filter and refine information returned by previously executed integrations; for example, filtering IT asset information to include only servers, focusing on key assets first. Unlike automated Enrichment actions, automated Containment actions could have serious unintended impacts on the organization. User Choice nodes allow users to minimize this risk by allowing them to define critical junctions in the workflow at which a human must intervene and make a decision. For example, human verification may be required before banning a hash value across the enterprise or quarantining a host pending further analysis.
Improvements to our patent-pending Automated Responder Knowledge (DF-ARK) module allow IncMan to make even more intelligent decisions when suggesting response actions, and enhancements to IncMan’s correlation engine allow users a more advanced view of the threat landscape over time and across the organization. IncMan’s report engine has been significantly bolstered, allowing users to create more flexible reports for a variety of purposes than ever before. Finally, numerous changes have been made to IncMan’s Dashboard and KPI features, allowing users to create more actionable KPIs and gather a complete picture of the organization’s current state of security at a moment’s glance.
These are just some of the highlights of our latest IncMan release; IncMan 4.3 includes many other enhancements designed to streamline your orchestration, automation and response process. If you would like a demo of our latest release, please go to our demo request site. Stay tuned to our website for additional updates, feature highlights, and demos of our latest release.