Aqua Cloud Native Blog › Tags: Runtime Security

A fileless attack is a technique that takes incremental steps toward gaining control of your environment while remaining undetected. In a fileless attack, the malware is directly loaded into memory and executed, evading common defenses and static scanning.

Attackers are sophisticated, there is always a lag between zero days and mitigation, and production workloads are critical. So why is the adoption of runtime security for cloud native applications still lower than shift-left security practices for the same applications?

We recently came across a real-life scenario that is very common for organizations. A developer with admin access launched a cloud native application but made a mistake and misconfigured it with weak credentials. Just 12 hours later, the environment was attacked by the DreamBus botnet, which proceeded to evade defenses and run Kinsing malware and …

eBPF technology is seeing strong growth, being widely adopted in the cloud native ecosystem for monitoring, networking, and security goals. At Aqua, along with being used in commercial products, eBPF powers our open source project Tracee to detect events in running containers.

While container environments grow in size and complexity, many misconceptions persist about securing cloud native applications. Our latest survey reveals a huge knowledge gap around runtime security, with 97% of cloud native security practitioners still unaware of crucial container security principles. Here are the insights we gained into the challenges that DevOps and security teams …

A single vulnerability in one of the code dependencies can put an entire application at risk, yet 48% of organizations knowingly push vulnerable code into production regularly. With a heavy reliance on open source software to build applications, patching a myriad of vulnerabilities has become an extremely hard and time-consuming task. It’s not always possible, …

While Docker has become synonymous with containers, various container tools and platforms have emerged to make the process of developing and running containers more efficient. Still, a lot of the same principles around Docker security apply for protecting container-based applications built with other tools as well. We compiled 20 essential Docker security best practices into …

In my previous post, I covered how you can secure your CI/CD pipeline with Tracee from potentially malicious code executions. We’re now releasing Tracee GitHub Action, which makes using Tracee a plug-n-play experience and doesn’t require any prior knowledge of eBPF or Docker. We’re also introducing a new capability to profile the normal behavior of …

Tracee is an open source runtime security and forensics tool for Linux, built to address common Linux security issues. By leveraging the advantages of Linux extended Berkeley Packet Filter (eBPF) technology to trace systems and applications at runtime, Tracee analyzes collected events to detect suspicious behavioral patterns. In this blog, I’ll share the lessons we …

Drift prevention is the cloud native answer to malware, worms and zero-day exploits. It’s also one of the best things to happen to security since the firewall, and finally a departure from the defeatist “we can’t really stop attacks so let’s not try” approach that’s been plaguing the mindset of security professionals in recent years …

Infrastructure protection, sandboxed containers, MicroVM hypervisors– these are interchangeable terms describing emerging technologies to isolate micro-services from their underlying infrastructure. These isolation technologies aim to protect the underlying host that runs containers and functions against malicious escape and breakout attempts into other targets on the same host or on the shared infrastructure. They attempt to provide VM-level isolation …

Earlier this week, a severe vulnerability in Kubernetes (CVE-2018-1002105) was disclosed that allows an unauthenticated user to perform privilege escalation and gain full admin privileges on a cluster. The CVE was given the high severity score of 9.8 (out of 10) and it affects all Kubernetes versions from 1.0 onwards, but fixes are available for recent versions.