Okay, I will improve the K3s Project Design Document for Threat Modeling based on your feedback. Here is the improved version, focusing on clarity, conciseness, security focus, and actionable threat modeling guidance.
# K3s Project Design Document for Threat Modeling - Improved Version
**Project:** K3s - Lightweight Kubernetes
**Version:** Based on K3s v1.27 (as of October 26, 2023, adjust as needed)
**Document Version:** 1.1
**Date:** October 27, 2023
**Author:** Gemini (AI Expert)
## 1. Introduction
This document provides a security-focused design overview of K3s, a lightweight Kubernetes distribution, specifically for threat modeling. It details the system architecture, key components, data flow, and critical security aspects to facilitate threat identification and mitigation in K3s deployments.
K3s is engineered for resource-constrained environments like edge computing and CI/CD, offering a production-ready, certified Kubernetes experience in a single binary with simplified operations and standard Kubernetes API compatibility.
This document targets security professionals, developers, and operators requiring a deep understanding of K3s architecture for security analysis and proactive threat management. It will serve as the foundation for identifying potential vulnerabilities and developing effective security strategies.
## 2. System Overview
K3s streamlines Kubernetes by consolidating components and using lightweight alternatives, while adhering to core Kubernetes principles.
The architecture comprises:
* **Server Components (Control Plane):** Manage cluster state and operations.
* **Agent Components (Worker Nodes):** Execute workloads under control plane direction.
**Architectural Diagram:**
```mermaid
graph LR
subgraph "Server Node (Control Plane)"
direction TB
"API Server" --> "Scheduler"
"API Server" --> "Controller Manager"
"API Server" --> "etcd"
"Controller Manager" --> "etcd"
"Scheduler" --> "API Server"
"Kubelet (Server)" --> "API Server"
"Embedded Containerd" --> "Kubelet (Server)"
"Service LoadBalancer (Optional)" --> "API Server"
"Ingress Controller (Optional)" --> "API Server"
end
subgraph "Agent Node (Worker Node)"
direction TB
"Kubelet (Agent)" --> "API Server"
"Kube-proxy" --> "Kubelet (Agent)"
"Containerd" --> "Kubelet (Agent)"
end
"User (kubectl)" --> "API Server"
"External Services" --> "Service LoadBalancer (Optional)"
"Ingress" --> "Ingress Controller (Optional)"
classDef component fill:#f9f,stroke:#333,stroke-width:2px
class "API Server","Scheduler","Controller Manager","etcd","Kubelet (Server)","Embedded Containerd","Service LoadBalancer (Optional)","Ingress Controller (Optional)","Kubelet (Agent)","Kube-proxy","Containerd","User (kubectl)","External Services","Ingress" componentKey Components (Security Perspective):
- API Server: Central access point, enforces authentication and authorization. Security Critical: Vulnerable to authentication bypass, authorization flaws, API abuse.
- Scheduler: Pod placement based on policies. Security Relevant: Misconfiguration can lead to insecure pod placement, resource contention.
- Controller Manager: Automates cluster state management. Security Relevant: Controller logic flaws can cause unintended state changes, privilege escalation.
- etcd: Cluster data store. Security Critical: Data confidentiality and integrity are paramount. Vulnerable to data breaches, data corruption.
- Kubelet (Server & Agent): Node agent, manages pods. Security Critical: Node security depends on Kubelet security. Vulnerable to container escapes, node compromise.
- Containerd: Container runtime. Security Critical: Container isolation and image security are managed by containerd. Vulnerable to container breakouts, image vulnerabilities.
- Kube-proxy: Network proxy for Services. Security Relevant: Network policy enforcement depends on kube-proxy. Vulnerable to network policy bypass, service exposure.
- Service LoadBalancer (Optional): External service exposure. Security Relevant: External attack surface. Vulnerable to DDoS, unauthorized access.
- Ingress Controller (Optional): HTTP/HTTPS routing. Security Relevant: Web application security risks. Vulnerable to web application attacks, misconfiguration.
This section details each component with a focus on security implications and potential threat vectors.
- Functionality: Kubernetes API endpoint, authentication, authorization, request validation, cluster interaction.
- Security Focus: Central security enforcement point. Compromise impacts entire cluster.
- Security Mechanisms:
- Authentication: X.509 certificates, bearer tokens, OIDC, Webhook. Misconfiguration or weak credentials are major vulnerabilities.
- Authorization (RBAC): Controls API access. Insufficient or overly permissive RBAC policies lead to privilege escalation.
- TLS Encryption: Protects API communication. Missing or weak TLS exposes sensitive data in transit.
- Audit Logging: Tracks API activity. Disabled or insufficient logging hinders security monitoring and incident response.
- Rate Limiting: Mitigates DoS attacks. Insufficient rate limiting allows API abuse.
- Admission Controllers: Policy enforcement pre-persistence. Bypassed or misconfigured admission controllers weaken security posture.
- Threat Vectors:
- Authentication Bypass: Exploiting vulnerabilities to bypass authentication mechanisms.
- Authorization Flaws: Privilege escalation due to misconfigured RBAC.
- API Abuse: DoS attacks, resource exhaustion through excessive API requests.
- Data Exfiltration: Unauthorized access to cluster data via API.
- Man-in-the-Middle (MitM) Attacks: If TLS is not enforced or weak.
- Functionality: Pod placement onto nodes.
- Security Focus: Indirectly impacts security through node selection and resource management.
- Security Mechanisms:
- Node Selection Policies: Influence where pods run. Insecure policies can lead to pods on less secure nodes.
- Resource Quotas/Limits: Resource management. Insufficient quotas can lead to resource exhaustion and DoS.
- Pod Security Contexts: Scheduler respects pod security requests. Ignoring or misinterpreting security contexts weakens pod security.
- Threat Vectors:
- Insecure Pod Placement: Scheduling sensitive pods on compromised or less secure nodes.
- Resource Starvation: Scheduler misconfiguration leading to resource exhaustion and denial of service.
- Circumvention of Security Policies: Exploiting scheduler logic to bypass intended security constraints.
- Functionality: Cluster state automation (node, pod, service management).
- Security Focus: Critical for maintaining cluster integrity and security posture.
- Security Mechanisms:
- Controller Logic: Core automation logic. Vulnerabilities in controller logic can lead to widespread cluster compromise.
- Service Account Permissions: Access to API Server. Overly permissive service accounts grant excessive privileges.
- Resource Management: Manages critical resources. Mismanagement can lead to instability and DoS.
- Threat Vectors:
- Controller Logic Exploits: Exploiting vulnerabilities in controller code for malicious actions.
- Privilege Escalation via Service Accounts: Abusing overly permissive controller service accounts.
- Cluster-Wide DoS: Controller malfunctions leading to resource exhaustion or instability.
- Functionality: Kubernetes cluster data store.
- Security Focus: Confidentiality, integrity, and availability of cluster data. Compromise is catastrophic.
- Security Mechanisms:
- Encryption at Rest: Protects data at rest. Disabled encryption exposes sensitive data on disk.
- Access Control: Restricts access to etcd. Unrestricted access allows unauthorized data manipulation or breaches.
- TLS Encryption: Protects communication with API Server. Missing TLS exposes data in transit.
- Quorum & Consensus (Raft): Ensures data consistency and fault tolerance. Failure to maintain quorum impacts availability and data integrity.
- Backups: Disaster recovery. Lack of backups leads to data loss in case of failure.
- Threat Vectors:
- Data Breach: Unauthorized access to etcd data, exposing secrets and cluster configuration.
- Data Corruption: Malicious or accidental data modification leading to cluster instability.
- Denial of Service: Disrupting etcd availability, halting cluster operations.
- Data Loss: Failure to recover from etcd failures due to lack of backups or HA.
- Functionality: Node agent, pod and container management.
- Security Focus: Node-level security, container isolation. Compromise leads to node and potentially cluster compromise.
- Security Mechanisms:
- Node Security: OS and host security. Weak node security increases Kubelet vulnerability.
- Container Runtime Interface (CRI): Interface to containerd. CRI vulnerabilities can be exploited via Kubelet.
- Pod Security Contexts: Enforces pod security settings. Ignoring or misconfiguring security contexts weakens container security.
- Node Communication Security (TLS): Secure communication with API Server. Missing TLS exposes Kubelet communication.
- Credential Management: Manages image pull secrets. Insecure credential management exposes registry credentials.
- Threat Vectors:
- Container Escape: Exploiting vulnerabilities to break out of container isolation and compromise the node.
- Node Compromise: Exploiting Kubelet vulnerabilities to gain control of the node.
- Privilege Escalation: Escalating privileges within a container or on the node via Kubelet vulnerabilities.
- Data Exfiltration from Nodes: Accessing sensitive data on the node via compromised Kubelet or containers.
- Functionality: Container runtime, image management, container lifecycle.
- Security Focus: Container isolation, image security. Compromise leads to container breakouts, image-based attacks.
- Security Mechanisms:
- Container Image Security: Image scanning, registry authentication, provenance. Vulnerable images or compromised registries introduce malware.
- Container Isolation (namespaces, cgroups): Isolates containers. Weak isolation allows container breakouts.
- Runtime Security (Seccomp, AppArmor/SELinux): Restricts container capabilities. Missing or weak profiles increase container attack surface.
- Runtime Security Updates: Patching containerd vulnerabilities. Outdated runtime exposes known vulnerabilities.
- Threat Vectors:
- Container Breakout: Escaping container isolation to access the host system.
- Malicious Container Images: Deploying containers with malware or vulnerabilities.
- Supply Chain Attacks: Compromised container registries or image sources.
- Resource Abuse: Container runtime vulnerabilities leading to resource exhaustion.
- Functionality: Kubernetes Service proxy and load balancing.
- Security Focus: Network policy enforcement, service exposure control. Compromise leads to network policy bypass, unintended service exposure.
- Security Mechanisms:
- Network Policies: Enforces network segmentation. Misconfigured or missing policies allow unrestricted network traffic.
- Service Exposure Control: Manages service accessibility. Misconfiguration can expose services unintentionally.
- Threat Vectors:
- Network Policy Bypass: Exploiting kube-proxy vulnerabilities to circumvent network policies.
- Unintended Service Exposure: Misconfiguration leading to unauthorized access to services.
- Service Interception: Man-in-the-middle attacks on service traffic via kube-proxy vulnerabilities.
- Functionality: External load balancer for Services.
- Security Focus: External attack surface, service exposure control. Compromise leads to external service access, DoS.
- Security Mechanisms:
- Access Control: Restricts access to the load balancer. Unrestricted access allows unauthorized service access.
- DDoS Protection: Mitigates DoS attacks. Lack of DDoS protection makes services vulnerable.
- TLS Termination: Secure HTTPS termination. Misconfigured TLS exposes data in transit.
- Threat Vectors:
- External Service Access: Unauthorized access to services exposed via the load balancer.
- DDoS Attacks: Load balancer as a target for denial of service attacks.
- TLS Vulnerabilities: Weak TLS configuration leading to data interception.
- Functionality: HTTP/HTTPS routing, web application gateway.
- Security Focus: Web application security, external access control. Compromise leads to web application attacks, data breaches.
- Security Mechanisms:
- Web Application Security Best Practices: Input validation, output encoding, etc. Lack of web application security makes services vulnerable to common web attacks.
- TLS Configuration: Secure HTTPS termination. Weak TLS exposes data in transit.
- Authentication/Authorization: Protects web applications. Missing authentication allows unauthorized access.
- Rate Limiting & WAF: Mitigates web attacks. Lack of protection allows web attacks to succeed.
- Configuration Security: Secure Ingress configuration. Misconfiguration can expose vulnerabilities.
- Threat Vectors:
- Web Application Attacks: XSS, SQL Injection, CSRF, etc., targeting applications behind the Ingress.
- TLS Vulnerabilities: Weak TLS configuration leading to data interception.
- Unauthorized Access to Web Applications: Missing or weak authentication/authorization.
- Ingress Controller Exploits: Vulnerabilities in the Ingress controller itself.
Deployment models significantly impact security:
- Single-Server: Highest Risk. Single point of failure. Control plane and workloads on one node. Node compromise = cluster compromise. Not for production.
- Multi-Server (HA Control Plane): Recommended for Production. Control plane redundancy. Agent nodes isolated. Control plane compromise harder, but agent node compromise still possible. Requires secure server node communication.
- Agent-Only Nodes: Scalable and More Secure than Single-Server. Control plane isolated. Agent node compromise limited to worker node scope. Secure agent-server communication is crucial.
Deployment Security Best Practices:
- Network Segmentation: Isolate control plane, agent nodes, and external networks. Firewalls and Network Policies are essential.
- Node Hardening: Secure OS, minimize services, apply security benchmarks. Reduces node attack surface.
- Secure Boot: Prevent unauthorized bootloaders. Protects against boot-level attacks.
- Regular Security Updates: Patch OS, K3s, containerd, and all components. Mitigates known vulnerabilities.
K3s external interfaces are potential attack vectors:
- User (kubectl): Authentication and Authorization are Key. Compromised user credentials or overly permissive RBAC = cluster compromise. Enforce strong authentication, least privilege RBAC.
- Container Registries: Supply Chain Risk. Compromised registries or images = malware injection. Use trusted registries, scan images, verify provenance.
- External Services: Network Security and Authentication. Unsecured external service communication = data breaches. Enforce TLS, strong authentication for external service access.
- External Load Balancers/DNS: External Attack Surface. Misconfigured load balancers = service exposure, DoS. Secure load balancer configuration, DDoS protection, TLS termination.
- Monitoring/Logging Systems: Data Confidentiality and Integrity. Unsecured monitoring/logging = data breaches, log tampering. Secure transmission and storage of logs/metrics, access control.
The data flow diagram (section 2) highlights sensitive data paths. Security concerns include:
- Credential Transmission: User and service account credentials must be protected in transit (TLS).
- RBAC Policy Storage: RBAC policies in etcd must be protected from unauthorized access and modification.
- Pod Specification Confidentiality: Pod specs (secrets, env vars) in etcd and transit to Kubelet must be encrypted.
- Secret Management: Kubernetes Secrets require encryption at rest and secure access control.
- Container Image Security: Images pulled from registries must be scanned and verified to prevent malware.
To effectively threat model K3s, consider the following:
By Component:
- API Server: Focus on authentication, authorization, API abuse, and data exfiltration threats.
- etcd: Prioritize data confidentiality, integrity, and availability threats.
- Kubelet & Containerd: Analyze container escape, node compromise, and image security threats.
- Network Components (Kube-proxy, LoadBalancer, Ingress): Assess network policy bypass, service exposure, and web application attack threats.
By Attack Surface:
- External API Access (kubectl): Threats related to user authentication and authorization.
- External Network Exposure (LoadBalancer, Ingress): Threats from the internet, including web attacks and DoS.
- Node Level: Threats targeting individual nodes, including container escapes and node compromise.
- Control Plane: Threats targeting control plane components, leading to cluster-wide impact.
- Supply Chain (Container Images): Threats from compromised container images and registries.
Threat Modeling Activities:
- Identify Assets: Cluster data (secrets, configuration), workloads, control plane components, nodes.
- Identify Threats: Use STRIDE or similar frameworks, focusing on the threat vectors outlined in this document for each component and attack surface.
- Vulnerability Analysis: Assess K3s configuration, component versions, and deployment model for known vulnerabilities.
- Risk Assessment: Prioritize threats based on likelihood and impact.
- Mitigation Strategies: Develop and implement security controls to mitigate identified risks (e.g., RBAC hardening, network policies, image scanning, encryption).
This improved design document provides a robust foundation for threat modeling K3s deployments. By understanding the architecture, component-specific security considerations, and actionable threat modeling guidance, security professionals can proactively identify and mitigate potential threats. This document should be used as a living document, updated as K3s evolves and new threats emerge. Continuous security assessment and adaptation are crucial for maintaining a secure K3s environment.