There is a considerable amount of data being generated every second, leading to new vulnerabilities and attack vectors targeting the system. As a result of this increased influx and sophistication of cyber-attacks, SOCs today are under tremendous pressure.
Organizations are now using and implementing cyber threat intelligence more than ever before. And the ones measuring the effectiveness of Cyber Threat Intelligence (CTI) programs are more prominent today. It increased from 4% in 2020 to 38% in 2021, as per the SANS 2021 Cyber Threat Intelligence (CTI) Survey.
However, CTI adoption appears to be lacking in some areas such as automation, integration and operationalizing threat intelligence. The report discovered that teams depend on automation in the SIEM more, and this provides a clear understanding of why CTI adoption trails in these areas. SIEMs have been around for a long time and were created to replace conventional log correlation to recognize suspicious network activity by normalizing alerts across various technology vendors. It was never designed to deal with full volume of data from modern security tools and technologies like EDR and CDR.
It is critical to comprehend the context of the available data. Given the current business environment, network design, technology stack, and risk profile, organizations need to understand what are the most critical and high-priority information they need to focus on to alleviate risk.
Security teams need to have a complete understanding of the threat immediately, examine its impact, make decisions and decide what steps need to be taken. Utilizing the platform to aggregate, normalize and deduplicate information from every source automatically, internal or external, structured or unstructured, could build a central archive of what was identified.
Associating events and correlating indicators from inside the environment with external data on adversaries, indicators, and their systems, offers organizations the context to understand the details about the attacks including who, where, what, why, when, and how.
How to respond to a threat?
Security teams with a complete understanding of the attack with context could enable the data as part of their operations and infrastructure with the flexibility to do so automatically, manually, or some mixture. They could identify if anyone else within the organization is required to utilize and interpret this data – the network security team, threat hunters, threat intelligence analysts, management, forensics and investigations, etc. – and share it. Moreover, they could transfer the data to their current infrastructure, supporting those technologies to function more efficiently and deliver fewer fake positives. Also, they could move the accurate data back to the right tools across the sensor grid to create and apply updated policies and rules to mitigate risk.
Security teams can rely on the platform continuously and automatically re-prioritize and re-evaluate as and when new data, observations, and learnings appear. From tactical intelligence that can be utilized to make block lists or use signatures to operational intelligence on what methods are used, tools to look out for, and strategic intelligence to recognize potential threat leads and what they are later.
With a modern platform designed for automating, integrating and operationalizing intelligence, it’s now possible to reach different levels of effectiveness of CTI programs, such as a measurable and decisive influence on time to response and detection.