This was the basis of CTF Runtime Research Scenario developed with the illustrious Cloud Native Dudes Crew: https://github.com/kurtiepie/k8s_in_mem_lab
The prevalence of fileless, in-memory attacks in cloud-native Kubernetes environments is on the rise, posing new challenges for administrators and engineering teams. While these teams have honed their skills in limiting attack surfaces and responding to threats, the emergence of fileless attacks demands innovative defense strategies.
Host-based agents leveraging eBPF (extended Berkeley Packet Filter) technology emerge as crucial components for real-time detection and response. Research from Aqua Nautilus underscores a significant uptick in fileless attacks, underscoring the urgency for robust defense mechanisms.
In-memory system calls, particularly those invoking simple APIs, can serve as indicators of malicious activity. Tools like Falco come equipped with default rules designed to detect such behavior. Additionally, strategies like restricting container capabilities and implementing read-only filesystems help mitigate risks.
Delving into scenarios such as in-memory lateral movement and harnessing admission controllers to enforce policies further bolsters security posture. Custom eBPF detection rules enable the identification of suspicious activities, prompting automated responses to neutralize threats swiftly.
For practical insights and tools to reinforce cloud-native defenses against in-memory attacks, explore our GitHub repository, k8s_in_mem_lab. Together, let’s stay vigilant and resilient against evolving threats in Kubernetes environments.