According to the SANS CTI 2019 survey results, 72% of organizations either consume or produce Threat Intelligence. Although most organizations have Intelligence data, they struggle with defining requirements and managing Cyber Threat Intelligence (CTI) as a program with measurable output. This likely results from threat data and intelligence being perceived as a technical function unrelated to business objectives.

We need to change this perception.

In my opinion, the key business objectives most closely related to threat intelligence are Risk Management and Cyber Resilience. Threat Intelligence can influence the outcomes of both.

Cyber Resilience itself requires risk management and adaptability. The need for businesses to become more resilient is driving the demand for an adaptable security architecture—one that not only effectively leverages threat intelligence to improve Security Operations, especially Incident Response, but also adapts cyber defenses such as endpoint and network controls to prevent the latest threats.

Meanwhile, regulations focused on improving cyber security are driving a continuous risk management approach. For example, in 2016, the European Union released the NIS (Network and Information Systems) Directive, which provides a legal framework to boost the overall level of cybersecurity in critical industries and calls specifically for threat intelligence and incident sharing among organizations and national authorities. With these drivers in mind, we now need to design a managed process with the goal of creating an efficient way to increase the business value of CTI. We can define this process as follows:

  • Discovering the most valuable data sources
  • Using automation to collect, investigate, respond and share
  • Integrating CTI into cyber defense processes
  • Measuring to prove the value of Threat Intelligence

1. Collection, Deduplication and Aggregation

The first step in the CTI Management Process is the collection, deduplication and aggregation of the data or feeds. One of the main gaps at the enterprise level is the collection of local produced Threat Intelligence. Local Threat Intelligence includes data generated from analytics solutions like sandboxes and from incidents. Sandboxes usually produce intelligence data in the form of Indicators of Compromise (IOCs). These local sources could expose targeted attacks, and therefore are potentially the most valuable threat data source.

McAfee’s Open Architecture allows for the production, consumption and sharing of threat intelligence in various ways. Here is an example of how our architecture automates aggregation of various CTI sources with an open-source tool, MISP. The MISP platform subscribes to the McAfee Data Exchange Layer messaging fabric to consume IoCs from McAfee’s Advanced Threat Defense sandbox in real time. Additionally, MISP consumes and manages feeds from open or paid sources, providing an entry-level tool to manage the threat intel process.

Here is another example of how our architecture supports the aggregation process, this time by working with a commercial vendor, ThreatQ.

2. Investigation and Hunting

The second step in the CTI management process is investigation and hunting. Here, the biggest task is figuring out how to make Threat Intelligence actionable, which can be done by answering questions like:

  • Have we seen any related artifacts (IP address connections, Hash/File executions) in my enterprise in the past?
  • Do we have, right now, any devices that have related artifacts?

Before answering these questions, the right data must be collected from the enterprise sensors. Fundamental information should include IP address connections, file hashes on endpoints, web proxy, DNS and Active Directory logs. These logs provide the necessary data for correlation and historical analysis. The following example demonstrates how the architecture can automate some of the key triage steps.

MISP can push Threat Intelligence into McAfee’s SIEM solution, ESM (Enterprise Security Manager), to automate historical analysis. There, it can query McAfee’s Threat Intelligence Exchange server to identify which systems executed related artifacts, and where and when they did so. Furthermore, MISP can run real-time queries against McAfee-protected endpoints with McAfee Active Response to identify any persistent artifacts that are currently in the enterprise network.

Here is another example working with ThreatQ. This time, ThreatQ interacts with McAfee ESM, Active Response and McAfee TIE to identify systems that have or had artifacts related to Threat Intelligence indicators. These various integrations support manual enrichment task and investigations.

The screenshot below highlights the various McAfee integrations as part of an investigation.

3. Response

The third step in the CTI Management Process is response. Cyber Threat Intelligence is essential to prevent the latest threats and should be integrated into key cyberdefense countermeasures. The following example demonstrates an automated update process using McAfee’s Open Architecture, with the Data Exchange Layer (DXL) fabric as the key component.

ThreatQ can communicate via the DXL fabric with McAfee technologies. During this process ThreatQ is able to update key cyber defense countermeasure tools with Threat Intelligence to protect against the latest threats.

Another part of this process step is sharing threat intelligence with other parties, such as partners and communities. Most Threat Intelligence Platforms (open source and commercial) support various protocols for external CTI sharing. This includes TLP, STIX, TAXII and DXL. These protocols support the automated exchange and governance of the shared data.

Another part of this process step is sharing threat intelligence with other parties, such as partners and communities. Most Threat Intelligence Platforms (open source and commercial) support various protocols for external CTI sharing. This list includes TLP, STIX, TAXII and DXL, which feature protocols facilitating the automated exchange and governance of the shared data.

4. Measurement

Finally, the value of Threat Intelligence can be proven by measuring a variety of outcomes. The following are some of the metrics commonly quantified and reported on:

  1. Number of duplicate Threat Intelligence Artifacts removed
  2. Impact on Mean-Time-To-Respond
  3. Number of IOCs generated from Threat Intelligence
  4. Number of incidents identified based on Threat Intelligence
  5. Number of attacks blocked via Threat Intelligence


The creation and implementation of the right process is critical to the success of Cyber Threat Intelligence within the enterprise. In this blog, we defined a CTI management process of Collection, Investigation, Response and Measurement. McAfee’s research, management platform and open architecture enable you to implement this process and get the best value out of Cyber Threat Intelligence, promoting resilience and enabling better risk management.

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