HomeArtificial IntelligenceKubernetes attacks are on the rise: Why real-time threat detection is the...

Kubernetes attacks are on the rise: Why real-time threat detection is the reply for businesses

Last 12 months 89% of organizations have been affected by at the least one container or Kubernetes security incident, making security a high priority for DevOps and security teams.

Although many DevOps teams imagine that Kubernetes isn’t secure, 92% of the container market. Gardener predicts that 95% of enterprises will probably be running containerized applications in production by 2029, up significantly from lower than 50% last 12 months.

While misconfigurations are liable for 40% of incidents and 26% said their organizations failed audits. However, the elemental vulnerabilities of Kubernetes security haven’t been fully addressed. One of probably the most pressing problems is deciphering the big variety of alerts generated and finding people who pose a reputable threat.

Kubernetes attacks are increasing

Attackers are finding Kubernetes environments a simple goal because the organizations that use them have an increasing number of misconfigurations and vulnerabilities that they don't fix quickly, if in any respect. Red Hat's latest Kubernetes Security Report found that 45% of DevOps teams experience security incidents during runtime where attackers exploit energetic vulnerabilities.

The Basics of Cloud Native Computing Kubernetes report found that 28% of organizations run over 90% of workloads in insecure Kubernetes configurations. More than 71% of workloads run with root access, increasing the likelihood of system compromise.

Traditional approaches to mitigating attacks cannot sustain. Attackers know they will act faster than organizations when a misconfiguration, vulnerability, or open service is discovered. Attackers exploit vulnerabilities and holes in Kubernetes security inside minutes, because it is notoriously a matter of minutes from initial intrusion to taking control of a container. Traditional security tools and platforms can take days to detect, remediate, and shut critical holes.

As attackers refine their methods and arsenal of tools, organizations need more real-time data to face a likelihood against Kubernetes attacks.

Why alarm-based systems aren’t enough

Almost all organizations which have standardized on Kubernetes as a part of their DevOps process depend on alert-based systems as the primary line of defense against container attacks. Aqua Security, Twistlock (now a part of Palo Alto Networks), Sysdig, and StackRox (Red Hat) offer Kubernetes solutions that provide threat detection, visibility, and vulnerability scanning. All offer container security solutions and have announced or are shipping AI-based automation and analytics tools to enhance threat detection and reduce response times in complex cloud-native environments.

Each of those attacks generates an exceptionally high variety of alerts that always require manual intervention, wasting helpful time for Security Operations Center (SOC) analysts. This typically results in alert fatigue amongst security teams as greater than 50% of security experts say they’re overwhelmed by the flood of notifications from such systems.

As Laurent Gil, co-founder and Chief Product Officer at Throw yourselftold VentureBeat, “If you employ traditional methods, you spend time responding to tons of of alerts, lots of which could also be false positives. That doesn't scale. Automation is essential – real-time detection and immediate remediation make all of the difference.”

The goal: Secure Kubernetes containers with real-time threat detection

Attackers relentlessly pursue the weakest attack surface of any attack vector, and with Kubernetes, container runtime becomes a preferred goal. That's because containers are energetic and processing workloads through the runtime phase, making it possible to take advantage of misconfigurations, privilege escalation, or unpatched vulnerabilities. This phase is especially attractive for crypto mining operations, where attackers hijack compute resources to mine cryptocurrencies. “One of our customers observed 42 attempts to launch crypto mining of their Kubernetes environment. Our system immediately identified and blocked all of them,” Gil told VentureBeat.

In addition, large-scale attacks similar to identity theft and data breaches often begin when attackers gain unauthorized access during runtime, using sensitive information and thus putting it at greater risk.

Based on the threats and attack attempts that CAST AI saw within the wild and amongst its customer base, they launched their Kubernetes Security Posture Management (KSPM) Solution this week.

What's notable about their approach is that DevOps operations can detect and robotically remediate security threats in real time. While competitor platforms offer high visibility and threat detection, CAST AI has developed real-time remediation that robotically fixes issues before they escalate.

Hugging faceknown for its Transformers library and contributions to AI research, faced significant challenges in managing runtime security in huge and sophisticated Kubernetes environments. Adrien Carreira, Head of Infrastructure at Hugging Face, notes, “CAST AI's KSPM product identifies and blocks 20x more runtime threats than some other security tool we use.”

To mitigate the specter of compromised Kubernetes containers, clusters must even be checked for misconfigurations, image vulnerabilities, and runtime anomalies. CAST AI has set this as a design goal in its KSPM solution by making automatic remediation, independent of human intervention, a core a part of the answer. Ivan Gusev, lead cloud architect at OpenXnoted, “This product was incredibly easy to make use of and delivered security insights in a rather more actionable format than our previous vendor. Continuous monitoring for runtime threats is now core to the environment.”​

Why real-time threat detection is so necessary

The real-time nature of any KSPM solution is crucial for combating Kubernetes attacks, especially during runtime. Jérémy Fridman, Head of Information Security at PlayPlayemphasized: “Since we introduced CAST AI for Kubernetes management, our security posture has change into significantly more robust. The automation features – each for cost optimization and security – embody the spirit of DevOps and make our work more efficient and secure.”

The CAST AI Security Dashboard below demonstrates how their system enables continuous scanning and real-time remediation. The dashboard monitors nodes, workloads, and image repositories for vulnerabilities, displays key insights, and provides immediate remediation.

Another good thing about integrating real-time detection into the core of any KSPM solution is the power to patch containers in real time. “Automation means your system is all the time running on the newest and most secure versions. We not only provide you with a warning to threats, but we fix them before your security team even takes motion,” said Gil.​

Increased Kubernetes security is a must in 2025

The bottom line is that Kubernetes containers are increasingly being attacked, especially at runtime, putting entire organizations in danger.

Runtime attacks have gotten increasingly epidemic as cryptocurrency values ​​soar in response to global economic and political uncertainty. Any organization using Kubernetes containers must be especially vigilant against crypto mining. For example, illegal crypto mining on AWS can quickly rack up huge bills as attackers exploit vulnerabilities to run sophisticated mining operations on EC2 instances that eat massive amounts of computing power. This highlights the necessity for real-time monitoring and robust security controls to forestall such costly breaches.

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