Penetration Testing in Kubernetes Clusters

Container environments, especially in Kubernetes clusters, have become a critical frontier for cybersecurity professionals aiming to identify and mitigate identity-related risks. However, container security is often overlooked or underestimated, creating ripe conditions for penetration testers and malicious actors to exploit a range of vulnerabilities. These include exposed sensitive files, unpatched kernel vulnerabilities, insecure container configurations, and privileged service account tokens residing within container file systems.

One of the most significant insider threats within containers arises from the exposure of privileged service account tokens. Containers typically store these tokens inside the path /run/secrets/kubernetes.io/serviceaccount/token. An attacker who gains shell access to a container can retrieve this JSON Web Token (JWT) using a simple Linux command:

The retrieved JWT encodes vital information about the namespace, secret name, and service account. By decoding this token—using publicly available tools like jwt.io—an attacker obtains insights into the token’s privileges and scope. This enables further reconnaissance and attempts to escalate privileges or access sensitive data within the Kubernetes cluster.

To assess the level of access conferred by the service account token, penetration testers can make authenticated API calls to Kubernetes endpoints using curl commands. These commands target sensitive API resources to verify whether the token allows listing or modifying critical objects:

• List Pods:  

• List Secrets:  

• List Deployments:  

• List DaemonSets:  

Such queries reveal the token’s authorization scope and help penetration testers determine the potential for privilege escalation or data exposure. Tokens with wide permissions—such as the ability to list or modify secrets—can serve as gateways to further compromise the cluster.

Another critical container security weakness lies in kernel exploit vulnerabilities. Since containers share the host's kernel, outdated or unpatched kernels expose the entire Kubernetes infrastructure to risk. Exploiting a kernel vulnerability can enable an attacker to perform a container escape, compromising the underlying host and escalating privileges beyond the container boundary.

Penetration testers assess the kernel version inside containers by issuing commands such as:

Identifying known CVEs like CVE-2017-7308 assists in verifying whether kernel exploits are feasible. Container escapes leveraging kernel exploits can have severe consequences, making timely kernel updates and patches an essential security control.

Container security configurations also fundamentally determine the attack surface. Containers running with root privileges pose a drastically higher risk: if an attacker escapes the container, they inherit root-level access on the host. Therefore, best practices recommend running containers as non-root users wherever possible. Penetration testers validate this by checking the effective user inside the container—issuing whoami to confirm if root privileges are in use.

Additionally, certain Linux capabilities (e.g., cap_sys_admin, cap_sys_module, cap_sys_boot) granted within containers can be abused to escape confinement, escalate privileges, or manipulate kernel modules. The existence of these capabilities in container runtimes is a crucial factor for attackers seeking to bypass container isolation.

Lastly, the presence of sensitive files inside containers—such as passwords, SSH keys, certificates, or private keys—is a common yet often neglected risk. Misconfigured containers sometimes embed these critical assets in the file system, creating direct paths for attackers to harvest credentials or pivot within infrastructure. Penetration tests routinely include file system discovery to locate such secrets and evaluate their exposure risk.

Collectively, these insider container security threats underline the importance of continuous security validation and robust hardening practices. By simulating attacker techniques including service account token discovery, API authorization testing, kernel vulnerability assessment, and file system analysis, penetration testing professionals can uncover and remediate critical weaknesses before adversaries exploit them.

Kernel Exploit Vulnerabilities in Containers

Kernel exploit vulnerabilities present a critical threat within containerized environments due to the inherent architecture where containers share the host's kernel. Unlike traditional virtual machines that isolate kernels, containers rely on the single underlying host kernel, which means that a successful kernel exploit can enable an attacker to escape from the container sandbox to the host system itself. This privilege escalation drastically increases the attack surface and risk to the entire Kubernetes cluster or container orchestration platform.

Outdated and unpatched kernels are especially vulnerable to exploitation. Attackers often target publicly known kernel vulnerabilities to gain root-level access on the host, bypass container isolation, and potentially control other workloads running on the same host. For example, CVE-2017-7308 is a documented kernel vulnerability that has been leveraged for container escape attacks. This exploit allows malicious actors to execute arbitrary code in the kernel context, thereby breaking out of the container boundaries and compromising the underlying host.

Detecting kernel version and patch status is a fundamental step for penetration testers and security teams to assess exposure. Inside a container or on the host, commands such as:

reveal the kernel version and build information. By correlating this data with known vulnerabilities and CVE databases, teams can identify if a kernel is susceptible to exploitation.

Exploiting kernel vulnerabilities often requires sophisticated proof-of-concept or publicly available exploits which attackers use to escalate privileges or achieve container escape. Once a kernel exploit succeeds, the attacker gains the same level of control over the host as root, enabling them to manipulate containers, access sensitive data, and interfere with system operations across the infrastructure.

Due to the severe ramifications, maintaining an up-to-date kernel with timely patches is critical to container security hygiene. Security teams must incorporate regular kernel vulnerability assessments and patch management into their container lifecycle management to mitigate these risks. Failure to do so leaves Kubernetes clusters and containerized applications dangerously exposed to persistent and high-impact attacks.

Container Security Configuration Best Practices

Container security begins with properly configuring containers to minimize risk vectors that attackers can exploit. One of the most common and dangerous misconfigurations is running containers as the root user. When a container runs with root privileges, a container escape—where an attacker breaks out from the container isolation—leads to root access on the host system. This creates a critical security risk, as the attacker can then compromise the entire Kubernetes cluster or infrastructure.

To mitigate this risk, containers should follow the principle of least privilege by running under non-root users whenever possible. By restricting container processes to minimal privileges, organizations reduce the blast radius of any successful exploit. Penetration testers verify this setting by running simple commands such as whoami inside the container; identifying root privileges signals a high-severity issue.

Another subtle but impactful container security risk comes from granting extra Linux capabilities like cap_sys_admin, cap_sys_module, and cap_sys_boot. These capabilities allow privileged operations usually restricted to the kernel space, and their presence in a container can facilitate privilege escalation or container escape attacks. Containers should be deployed with a minimal capability set, removing all unnecessary permissions to reduce attack surfaces.

Pentesters assessing container security look specifically for these capabilities by inspecting container runtime configurations or security policies (e.g., seccomp profiles). Detection of such dangerous capabilities often leads to further exploration of container escape vectors.

Practical security best practices for container configuration include:

• Run containers as non-root users: Set user namespaces and avoid root UID/GID usage

• Drop all unnecessary Linux capabilities: Use capability bounding sets and seccomp profiles to restrict kernel interactions

• Employ read-only file systems: Limit write access inside the container to reduce tampering risks

• Mount sensitive files carefully: Avoid including secrets or host files unless absolutely necessary

• Use Pod Security Policies or OPA Gatekeeper: Enforce secure container configurations at deployment time

By applying these configuration best practices, security teams and pentesters can dramatically reduce the risk of privilege escalation and container escape attacks, hardening containerized environments against sophisticated threats.

Sensitive Files Inside Containers: Risks and Detection

Containers occasionally contain sensitive files such as password files, SSH private keys, certificates, and other cryptographic keys within their file systems. These files are often embedded inadvertently due to convenience during development or misconfigurations in container build processes. However, their presence inside containers creates significant security risks by exposing critical credentials to potential attackers.

If an attacker gains access to a container—via a compromised service account token, vulnerable application, or container escape—they can easily harvest these sensitive files. With stolen credentials or keys, attackers may pivot laterally within the Kubernetes cluster or cloud environment, escalate privileges, and access broader infrastructure components. For example, SSH keys or certificate files could allow direct logins to hosts or impersonation of services, while password files might be cracked offline to reveal user passwords.

Penetration testing routines therefore prioritize comprehensive file system scans inside container images and running containers to detect such sensitive artifacts. Techniques include searching for known filenames (e.g., id_rsa, *.pem, passwd), examining environment variables, and checking mounted volumes for secrets leakage. Identifying exposed secrets enables remediation actions like secret rotation, vault integration, or modifying container build pipelines to exclude sensitive files.

Recognizing the complexity and scale of this challenge, automated tools are under development to streamline sensitive file discovery and analysis within containers. These forthcoming solutions aim to provide continuous, scalable scanning across container registries and runtime environments—integrating with CI/CD pipelines and security operations. This automation will help organizations maintain container security hygiene by proactively detecting risks before deployment or exploitation.

Ultimately, preventing sensitive files from residing inside containers, combined with automated detection and remediation, is critical to reducing attack surfaces and protecting privileged credentials in modern containerized infrastructures.

Kubernetes Network Attack Vectors

The internal Kubernetes network architecture is composed of numerous interconnected services and applications that facilitate container orchestration, workload communication, and infrastructure management. These services, which each receive unique IP addresses within the cluster, act as proxies to route traffic to associated sets of pods. This dynamic service mesh enables scalability and resilience but also expands the attack surface exposed to potential adversaries.

For penetration testers, enumerating these services is a critical initial step when assessing cluster security. When valid Kubernetes API access exists—typical in grey-box testing scenarios—the command

can be used to list every service running across namespaces, along with their cluster IP addresses and ports. This comprehensive inventory provides a map of accessible endpoints and helps identify potentially vulnerable or misconfigured services within the cluster network.

One common example of a service often found in Kubernetes clusters is Prometheus, an open-source monitoring system extensively used for collecting metrics from pods and services. By default, Prometheus runs an HTTP interface that can expose detailed cluster information such as namespaces, pod names, and port configurations—valuable intelligence for an attacker.

To probe such a service, penetration testers typically use network scanning tools or direct HTTP queries. For example, scanning the Prometheus service IP and port with nmap or a simple curl command can reveal endpoints that disclose sensitive data:

This request may return a JSON payload detailing active pods, their namespaces, service kinds, and exposed ports. Such exposure can enable attackers to better understand the cluster layout, identify high-value targets, and craft targeted exploits.

Beyond Prometheus, enumeration and scanning should be expanded to all discovered services to uncover additional vulnerable applications or outdated versions subject to known exploits. Tools like nmap, combined with Kubernetes API queries, enable penetration testers to:

• Detect open ports and running services

• Identify protocols and software versions

• Enumerate service endpoints and APIs

• Collect metadata aiding further reconnaissance

The Kubernetes internal network often contains sensitive application endpoints and microservices communicating using HTTP, gRPC, or other protocols. Intercepting and analyzing this traffic may reveal unsecured communications, weak authentication, or misconfigured network policies that can be exploited.

In summary, understanding Kubernetes network attack vectors requires a combination of exhaustive service enumeration via the Kubernetes API, targeted scanning of identified services, and data discovery through HTTP requests such as those with curl. This methodology enables penetration testers to uncover misconfigurations and vulnerabilities that could compromise cluster confidentiality, integrity, or availability.

Network Traffic Sniffing in Kubernetes Clusters

Network traffic sniffing within Kubernetes clusters is a powerful technique for cybersecurity professionals and penetration testers seeking to gain deep insights into cluster communication patterns, exposed services, and potential security weaknesses. Tools like Wireshark and tcpdump enable the capture and detailed analysis of network packets traversing pod-to-pod, service, and external communications.

Sniffing is particularly valuable for identifying exposed IP addresses, open ports, and protocols used by services within the Kubernetes internal network. This visibility helps uncover insecure or legacy protocols such as HTTP, Telnet, or FTP that transmit sensitive data—including credentials or tokens—in clear text, making them susceptible to interception and exploitation.

tcpdump, a command-line utility widely available in Linux containers, allows operators to capture packets directly inside a container or node. For example, capturing traffic on the primary network interface with verbose output can be achieved using:

This command shows packet contents in both hex and ASCII, aiding identification of unencrypted data such as HTTP headers and payloads. Network sniffing with tcpdump supports filtering based on ports, protocols, or addresses (e.g., tcpdump -i eth0 port 80) to focus on relevant traffic.

Wireshark extends these capabilities with a graphical interface and advanced protocol dissectors, useful for offline analysis of captured .pcap files. By leveraging these tools, security teams can detect network misconfigurations, exposed sensitive endpoints, and unauthorized data flows. Identifying unencrypted data transmissions leads to remediation opportunities such as enforcing TLS, segmenting traffic, or restricting service access, strengthening overall cluster security posture.

In summary, network traffic sniffing complements other penetration testing methods by revealing hidden communication channels, uncovering improperly secured services, and exposing sensitive information, thereby enabling informed, targeted defenses in Kubernetes environments.

Discovery of Vulnerable Applications and Exploitation Techniques

Identifying vulnerable applications within Kubernetes clusters is a critical step for penetration testers aiming to uncover attack surfaces and exploit misconfigurations or software flaws. Running outdated or unpatched applications significantly raises the risk of compromise, as these often contain well-documented vulnerabilities that attackers can leverage for remote code execution or privilege escalation.

One effective technique to discover vulnerable applications is scanning internal Kubernetes services with Nmap combined with Nmap Scripting Engine (NSE) scripts. NSE scripts automate vulnerability detection for known software and expose weaknesses by probing HTTP services, web servers, and application endpoints with crafted requests that mimic known exploits.

A notable example is the detection of the Shellshock vulnerability (CVE-2014-6271), a critical remote code execution flaw in certain versions of the Bash shell. An attacker or tester can use NSE scripts or customized HTTP headers to determine if a service is exploitable and, subsequently, execute arbitrary commands remotely.

The following nmap command employs NSE to scan for Shellshock vulnerabilities on a target IP within the Kubernetes cluster:

If the service is vulnerable, nmap reports the presence of the flaw, enabling further exploitation steps. Exploiting this vulnerability typically involves sending a specially crafted HTTP header that injects malicious Bash commands.

For demonstration, the following curl command exploits the vulnerability by injecting a command to retrieve the contents of the /etc/passwd file:

A successful exploitation returns the contents of /etc/passwd, confirming remote code execution capabilities. This illustrates how exposed vulnerable services within Kubernetes clusters can lead to serious breaches.

Beyond Shellshock, penetration testers should employ a range of Nmap NSE scripts and vulnerability scanners to enumerate other known application flaws, such as outdated web interfaces, exposed debug consoles, or outdated application frameworks. Combining this discovery with service enumeration and API checking provides a comprehensive offensive view of the cluster's security posture.

Continuous discovery and patching of vulnerable applications are indispensable to maintaining Kubernetes security. Organizations should regularly scan services for vulnerabilities and update applications to the latest, patched versions to minimize risk and prevent attackers from exploiting known flaws.

Kubernetes Network Scanning Best Practices

Network scanning is a fundamental technique for penetration testers and security teams assessing Kubernetes cluster security. Due to the sprawling nature of Kubernetes networks—with multiple namespaces, dynamic pod IPs, and numerous services—effective scanning requires strategic approaches to efficiently enumerate services, identify open ports, and discover potential vulnerabilities.

A common practice in Kubernetes penetration testing is leveraging nmap for comprehensive port and service discovery. Scanning Kubernetes cluster IP ranges helps reveal exposed applications, misconfigured services, and outdated software versions that could be exploited by attackers.

Given the potential size of Kubernetes internal networks, manual scanning can be time-consuming. Automating this process with custom Bash scripts greatly enhances efficiency and repeatability. Below is an example script that installs nmap if needed and scans typical Kubernetes ports across a defined set of cluster IP ranges:

This script defines a function nmap-kube targeting ports commonly used by Kubernetes APIs, services, and monitoring components. The nmap-kube-discover function collects local IP ranges and predefined cluster subnet patterns to scan broadly within typical Kubernetes network boundaries.

The benefits of such tailored scanning include:

• Efficient enumeration: Focuses on relevant Kubernetes ports and ranges, minimizing extraneous scanning time.

• Comprehensive service discovery: Identifies running services (e.g., Kubernetes API server, Prometheus, etcd, metrics endpoints) that may expose sensitive data or vulnerable interfaces.

• Vulnerability mapping: Enables targeted follow-up tests such as version detection, script-based vulnerability checks, or brute force attempts on discovered services.

• Repeatable assessments: Automation via scripts standardizes workflows for routine pentesting or continuous red-teaming activity.

Ultimately, proactive network scanning in Kubernetes contexts is an indispensable step in uncovering the security posture of clusters. It provides visibility into the internal attack surface and helps identify potential entry points or misconfigurations that attackers could exploit, thereby formulating more effective defense and remediation strategies.

Cloud Credential Exposure Risks in Kubernetes

Kubernetes clusters hosted in public cloud environments such as AWS introduce significant risks related to the exposure of cloud credentials. A common and critical threat vector involves the unintended disclosure of AWS IAM secret keys through Kubernetes pods, which attackers can leverage to compromise cloud resources at scale.

Attackers who gain shell access to a containerized pod can attempt to retrieve cloud credentials by querying the cloud instance metadata endpoint. In AWS, the metadata service is accessible via the link-local address 169.254.169.254, allowing pods to access IAM role credentials associated with the underlying EC2 instance or container host.

For example, an attacker can list available IAM roles assigned to the instance by issuing the following curl command from within a compromised container:

This request returns the IAM role name(s) attached to the instance. With the role name, the attacker can then retrieve temporary credentials including the AccessKeyId, SecretAccessKey, and Token which provide programmatic access to AWS services:

These credentials may grant excessive permissions depending on their policy scope, enabling attackers to enumerate, modify, or delete cloud resources, exfiltrate data, or pivot to other infrastructure components. Such compromises can lead to full cloud account compromise, service disruption, or data breaches.

To assess and mitigate these risks, penetration testers and security teams can use specialized tools like SkyArk, which automate the discovery of excessive or exposed IAM permissions in cloud environments. SkyArk helps identify overly permissive policies and potential misconfigurations that increase the attack surface.

Key security practices to defend against cloud credential exposure in Kubernetes include:

• Strictly limiting IAM roles assigned to nodes or pods to follow the principle of least privilege

• Using Kubernetes pod security policies or admission controllers to restrict access to instance metadata endpoints

• Implementing robust secrets management instead of embedding cloud credentials inside containers

• Regularly auditing cloud permissions and monitoring for anomalous API activity

• Applying network policies that isolate workloads and restrict outbound access to metadata services

By understanding and addressing the risks associated with exposed cloud credentials in Kubernetes, organizations can significantly reduce the likelihood of cloud environment compromise and strengthen their overall cloud identity security posture.

Kubernetes Version and System Security Hygiene

Maintaining an updated Kubernetes system version is a critical security practice to mitigate exploitable vulnerabilities within clusters. Kubernetes frequently releases patches that address security flaws, fix bugs, and enhance system stability. Falling behind on version updates leaves clusters exposed to known weaknesses that attackers can leverage for privilege escalation, denial of service, or cluster compromise.

During grey-box penetration tests, verifying the Kubernetes version is a straightforward yet invaluable step to assess security posture. The standard command to check the installed Kubernetes version is:

This command provides concise output showing both the client and server versions, enabling testers and administrators to quickly identify outdated components. Knowing the exact version facilitates cross-referencing against vulnerability databases and advisories to determine the presence of relevant CVEs or security issues.

Beyond version checking, ongoing patch management constitutes a fundamental pillar of Kubernetes security hygiene. Organizations should establish automated update pipelines or scheduled maintenance windows to apply the latest stable Kubernetes releases and security patches. This process reduces the attack surface by closing vulnerabilities related to the API server, kubelet, scheduler, controller manager, and other core components.

In addition to Kubernetes itself, it is essential to keep underlying system components—such as the host OS kernel and container runtimes—current with security updates. Kernel vulnerabilities, in particular, can be exploited for container escapes and privilege escalation, further amplifying the importance of patch management.

In summary, integrating regular Kubernetes version checks and diligent patching routines into security operations is indispensable for maintaining resilient Kubernetes environments that withstand contemporary attack vectors.