We are in the midst of an unprecedented convergence of events that are forcing enterprises to dramatically change how they secure their modern businesses. With the acceleration of digital transformation from COVID-19, work-from-home initiatives, the continued growth of SaaS and the increasing adoption of microservices-based applications, the modern enterprise threat landscaping is transforming rapidly.

Containers and Kubernetes have revolutionized the way many teams deploy applications. But with the many benefits that these technologies provide come new challenges. Key among those challenges is security. By adding more layers and complexity to application environments, containers and Kubernetes create new opportunities for attackers and new security threats for Kubernetes admins to address.

With the growing popularity of cloud computing, security incidents related to it have been on the rise. Logs are indispensable resources for countering these threats, and they can be utilized for alerting, taking remedial action, and even preventing future attacks. In this post, we will examine ways to better secure cloud-native applications using logs.

Persistence is effectively the ability of the attacker to maintain access to a compromised host through intermittent network access, system reboots, and (to a certain degree) remediation activities. The ability of an attacker to compromise a system or network and successfully carry out their objectives typically relies on their ability to maintain some sort of persistence on the target system/network.

Today’s organizations have the challenge of managing several different applications and software within their technology stack. The more public-facing platforms an organization utilizes, the greater their public attack surface risks. Without proper protection, they and their community can become an easy target for malicious actors.

Compared to even just a few years ago, the tools available for data scientists and machine learning engineers today are of remarkable variety and ease of use. However, the availability and sophistication of such tools belies the ongoing challenges in implementing end-to-end data analytics use cases in the enterprise and in production.

Customers regularly ask me what types of data sources they should be sending to their SIEMs to get the most value out of the solution. The driver for these conversations is often because the customers have been locked into a SIEM product where they have to pay more for consumption. More log data equals more money and, as a result, enterprises have to make a difficult choice around what log sources and data are what they guess is the most important.

Ever since JASK was founded, we have heavily integrated with threat intelligence platforms to gain context into attacker activity through indicators of compromise (IOCs). Now that we have joined Sumo Logic, our customers have the ability to pull in more data than ever making this feature even more powerful. One of our tightest integrations is with the Anomali (formerly ThreatStream) platform.

As more and more enterprises shift to the cloud, the pressure on SOC teams to protect them against threats rises exponentially. They are the very first line of defense against data breaches and cyber threats that become more frequent and more sophisticated.