Teams that use Kubernetes face complex security challenges and need help securing their clusters, identifying potential vulnerabilities, and dealing with threats. The Shadowserver Foundation uncovered over 380,000 open Kubernetes API servers on the Internet, a staggering 84% of all worldwide Kubernetes API instances that allow some form of access.
The disparity between the emerging demands of Kubernetes environments and traditional cloud security practices calls for a better approach. Kubernetes Security Posture Management (KSPM) tools capable of automating threat remediation are the solution. They bridge the resource gap to enhance an organization’s security posture and security team efficiency.
Keep reading to learn why automation is a game-changer for managing Kubernetes security posture and how our new solution can help.
What is Kubernetes Security Posture Management?
Instead of adding to the different variations of what KSPM is, let’s turn to our friend (Gen AI) to define what it means.
Here’s what we get:
Kubernetes Security Posture Management (KSPM) refers to the continuous process of assessing, monitoring, and improving the security configurations and practices within Kubernetes environments.
As Kubernetes has become a dominant platform for container orchestration, ensuring its security is paramount to protect applications, data, and infrastructure from threats and vulnerabilities.
In many aspects, KSPM is comparable to Cloud Security Posture Management (CSPM). However, while CSPM manages an enterprise’s cloud infrastructure, KSPM concentrates on K8s clusters and workloads.
Why isn’t CSPM enough for Kubernetes clusters?
Cloud Security Posture Management (CSPM) solutions monitor and manage the security of cloud computing environments to ensure they are safe and following applicable security legislation and standards.
A CSPM solution addresses every security area, including identity and access management (IAM), data protection, network security, and threat detection and response.
Because the goals and aims of CSPM and KSPM differ, neither can replace the other.
Here are the major differences between CSPM and KSPM:
- CSPM can give a complete picture of an organization’s cloud security posture. Still, it may not include the tools and processes needed to manage the security posture of a Kubernetes cluster.
- KSPM focuses on the security of a Kubernetes deployment, but it doesn’t provide a complete picture of the organization’s cloud computing environment.
This is why organizations often use both CSPM and KSPM to ensure the security of their cloud computing environments, including Kubernetes deployments.
Why do you need KSPM?
As part of a larger Kubernetes security strategy, KSPM addresses several significant security concerns.
Ensuring Kubernetes compliance
Since KSPM employs frameworks to analyze and detect misconfigurations, it’s well-suited to circumstances in which organizations must fulfill specific compliance standards.
For example, you can automate compliance management inside K8s clusters by establishing policies that guarantee that any data handled or accessed by Kubernetes is stored in line with standards such as HIPAA or the GDPR.
Detecting human errors and oversights
No matter how hard engineers strive to ensure that the settings they generate are safe by default, human mistakes or oversight can always result in misconfigurations. KSPM assists teams in identifying and correcting errors before they cause breaches.
Validating third-party configurations
Kubernetes is an ecosystem in which teams frequently borrow or import resources from upstream. For example, you can retrieve container images from a public Docker Hub registry or use a GitHub deployment file.
These third-party developers that build such resources may or may not adhere to the same security standards as your team.
KSPM provides a method of scanning third-party resources for potential security vulnerabilities. As a result, you can take advantage of the Kubernetes community’s extensive resources while minimizing the related security concerns.
Why is an automated KSPM a better solution?
While building this Kubernetes security solution alongside CAST AI’s cost optimization tool, one thing we always kept in mind was to reduce DevOps toil.
A KSPM system should support every level of the application lifecycle, providing complete visibility and context throughout the whole container environment. To this end, a KSPM solution should include the following features while adhering to DevOps automation fundamentals – which is why we call our solution automated KSPM.
Real-time cluster security reporting
A good KSPM solution will come with a dashboard where users can see their current security status at a glance. The dashboard provides a single view of the organization’s Kubernetes cluster’s security posture, making it easy for teams to monitor and manage overall security.
Example of a security dashboard
Risk identification and assessment
KSPM tools examine the gathered data to identify possible security risks, misconfigurations, and vulnerabilities in the Kubernetes infrastructure by comparing configurations in line with security best practices.
This is an example of the Vulnerabilities dashboard showing the analysis of cluster vulnerabilities with detailed insights into CVEs and where the vulnerabilities are within an image:
Example of vulnerabilities dashboard
Remediation and recommendations
The hallmark of a good security tool is measured by how easy it is for the user to quickly resolve the issue by either working with other teams or remediating the vulnerability on their own. The trend with cloud-native security tools has been to provide a good amount of information to the user on the vulnerability and less information on how to resolve it.
CAST AI is at the forefront of automating the security process, and one of the easiest ways to reduce your vulnerabilities is through our base image recommendation. To speed up your prioritization, the suggestion is to jump to our ‘attack path’ visualization section to fix the most vulnerable workloads and tackle the less risky ones.
Example of recommendations for base image versions
Attack path visualization
Attack paths show critical image vulnerabilities exposed to the internet, helping users prioritize image vulnerability fixes over vulnerabilities not exposed to the Internet. The former are directly accessible to potential attackers.
KSPM users can also decide to stop exposing some workloads to the internet to reduce the chance of someone exploiting vulnerabilities. In this case, an attack path displays how a particular workload is exposed, making it easier to change the configuration.
The CAST AI attack path shows not only the vulnerabilities in the image on the far right; it tracks every misconfiguration part of a service or a deployment on the path to public-facing networks.
Compliance monitoring
One of the core tenets of using a security tool as a business running cloud-native applications is adhering to compliance standards. This allows you to be accountable for protecting sensitive data for your customers and your organization.
CAST AI uses the most up-to-date CIS benchmarks for the respective cloud provider’s managed Kubernetes platforms.
Example of identified compliance issues that can be filtered by level of severity.
What about zero-day attacks on containers?
With the launch of the automated KSPM solution, we didn’t stop with known threat vectors. Any suspicious activity within containers is instantly detected by leveraging a lightweight eBPF agent that constantly monitors for anomalies in the environment. Users can selectively enable specific rules depending on their applications.
Common crypto miners that are behind most attacks targeting Kubernetes clusters can be detected and blocked without the need to analyze at network levels or write complex rules.
Example anomaly detection dashboard
Node OS updates
The fact that CAST AI typically manages the entire Kubernetes infrastructure means that nodes running outdated, insecure operating system software are automatically updated.
You don’t need to worry about a cluster that hasn’t been audited for security. This is highly beneficial if you are running multi-cloud clusters and allows you to generate reports for compliance needs.
Example of node OS updating dashboard
Try our new KPSM solution built and partnered with Hugging Face, OpenX, and PlayPlay
Automation is critical due to the gap between traditional cloud security practices and the demands of Kubernetes applications.
What is unique about our new KSPM solution is that it automatically remediates threats in real-time, helping organizations move from passive monitoring to active defense.
Our KSPM solution automatically:
- Assesses an organization’s Kubernetes clusters for misconfigurations, vulnerabilities, threats, and compliance issues,
- Provides remediation recommendations,
- Detects threats.
This product’s development was heavily influenced by CAST AI’s partnerships with some of the world’s largest Kubernetes users, among them Hugging Face.
We required a robust security posture for our Kubernetes applications, particularly in detecting runtime threats. While some agentless tools were effective in identifying vulnerabilities, they fell short in detecting runtime threats. We’ve been using CAST AI’s KSPM product for several months, and it identifies and automatically blocks 20 times more runtime anomalies than other security tools.
Adrien Carreira, Head of Infrastructure at Hugging Face
