McAfee Labs highlights critical challenges to threat intel sharing
McAfee Labs highlights critical challenges to threat intel sharing

McAfee has released its McAfee Labs Threats Report: April 2017, which details the challenges facing threat intelligence sharing efforts, probes the architecture and inner workings of Mirai botnets, assesses reported attacks across industries, and reveals growth trends in malware, ransomware, mobile malware and other threats in Q4 2016.

“The security industry faces critical challenges in our efforts to share threat intelligence between entities, among vendor solutions, and even within vendor portfolios,” said Vincent Weafer, vice president of McAfee Labs. “Working together is power. Addressing these challenges will determine the effectiveness of cyber-security teams to automate detection and orchestrate responses, and ultimately tip the cyber-security balance in favour of defenders.”

The report reviews the background and drivers of threat intelligence sharing; various threat intelligence components, sources, and sharing models; how mature security operations can use shared data; and critical sharing challenges that the industry must overcome. Those challenges include:

  • Volume. A massive signal-to-noise problem continues to plague defenders trying to triage, process, and act on the highest-priority security incidents.

  • Validation. Attackers may file false threat reports to mislead or overwhelm threat intelligence systems, and data from legitimate sources can be tampered with if poorly handled.

  • Quality. If vendors focus just on gathering and sharing more threat data, there is a risk that much of it will be duplicated, wasting valuable time and effort. Sensors must capture richer data to help identify key structural elements of persistent attacks.

  • Speed. Intelligence received too late to prevent an attack is still valuable, but only for the cleanup process. Security sensors and systems must share threat intelligence in near real time to match attack speeds.

  • Correlation. The failure to identify relevant patterns and key data points in threat data makes it impossible to turn data into intelligence and then into knowledge that can inform and direct security operations teams.

To move threat intelligence sharing to the next level of efficiency and effectiveness, McAfee Labs suggests focusing on three areas:

  • Triage and prioritisation. Simplify event triage and provide a better environment for security practitioners to investigate high-priority threats.

  • Connecting the dots. Establish relationships between indicators of compromise so that threat hunters can understand their connections to attack campaigns.

  • Better sharing models. Improve ways to share threat intelligence between our own products and with other vendors.

“Increasingly sophisticated attackers are evading discrete defence systems, and siloed systems let in threats that have been stopped elsewhere because they do not share information,” Weafer continued. “Threat intelligence sharing enables us to learn from each other's experiences, gaining insight based on multiple attributes that build a more complete picture of the context of cyber-events.”

Mirai botnet proliferation

Mirai was responsible for the fourth quarter's highly publicised DDoS attack on Dyn, a major DNS service provider. Mirai is notable because it detects and infects poorly secured IoT devices, transforming them into bots to attack its targets.

The October public release of the Mirai source code led to a proliferation of derivative bots, although most appear to be driven by script kiddies and are relatively limited in their impact. But the source code release has also led to offerings of “DDoS-as-a-service” based on Mirai, making it simple for unsophisticated yet willing attackers to execute DDoS attacks that leverage other poorly secured IoT devices. Mirai botnet-based DDoS attacks are available as a service in the cyber-criminal marketplace for $50 to $7,500 per day.

McAfee Labs estimates that 2.5 million Internet of Things (IoT) devices were infected by Mirai by the end of Q4 2016, with about five IoT device IP addresses added to Mirai botnets each minute at that time.