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CTHFM: Kubernetes
  • Welcome
  • Kubernetes Fundamentals
    • Kubernetes Components
      • Kubernetes Master Node
      • Worker Nodes
      • Pods
      • Service
      • ConfigMaps and Secrets
      • Namespaces
      • Deployments
      • ReplicaSets
      • Jobs and CronJobs
      • Horizontal Pod Autoscaler (HPA)
      • Kubernetes Ports and Protocols
    • Kubectl
      • Installation and Setup
      • Basic Kubectl
      • Working With Pods
      • Deployments and ReplicaSets
      • Services and Networking
      • ConfigMaps and Secrets
      • YAML Manifest Management
      • Debugging and Troubleshooting
      • Kubectl Scripting: Security
      • Customizing Kubectl
      • Security Best Practices
      • Common Issues
      • Reading YAML Files
    • MiniKube
      • Intro
      • Prerequisites
      • Installation MiniKube
      • Starting MiniKube
      • Deploy a Sample Application
      • Managing Kubernetes Resources
      • Configuring MiniKube
      • Persistent Storage in Minikube
      • Using Minikube for Local Development
      • Common Pitfalls
      • Best Practices
  • Kubernetes Logging
    • Kubernetes Logging Overview
    • Audit Logs
    • Node Logs
    • Pod Logs
    • Application Logs
    • Importance of Logging
    • Types of Logs
    • Collecting and Aggregating Logs
    • Monitoring and Alerting
    • Log Parsing and Enrichment
    • Security Considerations in Logging
    • Best Practices
    • Kubernetes Logging Architecture
  • Threat Hunting
    • Threat Hunting Introduction
    • What Makes Kubernetes Threat Hunting Unique
    • Threat Hunting Process
      • Hypothesis Generation
      • Investigation
      • Identification
      • Resolution & Follow Up
    • Pyramid of Pain
    • Threat Frameworks
      • MITRE Containers Matrix
        • MITRE Att&ck Concepts
        • MITRE Att&ck Data Sources
        • MITRE ATT&CK Mitigations
        • MITRE Att&ck Containers Matrix
      • Microsoft Threat for Kubernetes
    • Kubernetes Behavioral Analysis and Anomaly Detection
    • Threat Hunting Ideas
    • Threat Hunting Labs
  • Security Tools
    • Falco
      • Falco Overview
      • Falco's Architecture
      • Runtime Security Explained
      • Installation and Setup
      • Falco Rules
      • Tuning Falco Rules
      • Integrating Falco with Kubernetes
      • Detecting Common Threats with Falco
      • Integrating Falco with Other Security Tools
      • Automating Incident Response with Falco
      • Managing Falco Performance and Scalability
      • Updating and Maintaining Falco
      • Real-World Case Studies and Lessons Learned
      • Labs
        • Deploying Falco on a Kubernetes Cluster
        • Writing and Testing Custom Falco Rules
        • Integrating Falco with a SIEM System
        • Automating Responses to Falco Alerts
    • Open Policy Agent (OPA)
      • Introduction to Open Policy Agent (OPA)
      • Getting Started with OPA
      • Rego
      • Advanced Rego Concepts
      • Integrating OPA with Kubernetes
      • OPA Gatekeeper
      • Policy Enforcement in Microservices
      • OPA API Gateways
      • Introduction to CI/CD Pipelines and Policy Enforcement
      • External Data in OPA
      • Introduction to Decision Logging
      • OPA Performance Monitoring
      • OPA Implementation Best Practices
      • OPA Case Studies
      • OPA Ecosystem
    • Kube-Bench
    • Kube-Hunter
    • Trivy
    • Security Best Practices and Documentation
      • RBAC Good Practices
      • Official CVE Feed
      • Kubernetes Security Checklist
      • Securing a Cluster
      • OWASP
  • Open Source Tools
    • Cloud Native Computing Foundation (CNCF)
      • Security Projects
  • Infrastructure as Code
    • Kubernetes and Terraform
      • Key Focus Areas for Threat Hunters
      • Infastructure As Code: Kubernetes
      • Infrastructure as Code (IaC) Basics
      • Infastructure As Code Essential Commands
      • Terraform for Container Orchestration
      • Network and Load Balancing
      • Secrets Management
      • State Management
      • CI/CD
      • Security Considerations
      • Monitoring and Logging
      • Scaling and High Availability
      • Backup and Disaster Recovery
    • Helm
      • What is Helm?
      • Helm Architecture
      • Write Helm Charts
      • Using Helm Charts
      • Customizing Helm Charts
      • Customizing Helm Charts
      • Building Your Own Helm Chart
      • Advanced Helm Chart Customization
      • Helm Repositories
      • Helm Best Practices
      • Helmfile and Continuous Integration
      • Managing Secrets with Helm and Helm Secrets
      • Troubleshooting and Debugging Helm
      • Production Deployments
      • Helm Case Studies
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On this page
  • Installing and Setting Up Falco
  • Step 1: Prerequisites
  • Step 2: Add the Falco Helm Repository
  • Step 3: Install Falco Using Helm
  • Step 4: Verify the Installation
  • Step 5: Testing Falco
  • Step 6: Basic Troubleshooting
  1. Security Tools
  2. Falco

Installation and Setup

Installing and Setting Up Falco

Overview: In this lesson, we will walk through the process of installing and setting up Falco in a Kubernetes environment. Falco can be deployed using various methods, but in this lesson, we’ll focus on deploying Falco using Helm, a popular package manager for Kubernetes. By the end of this lesson, you will have a working installation of Falco monitoring your Kubernetes cluster.

Step 1: Prerequisites

Before you begin installing Falco, ensure that your environment meets the following prerequisites:

  • Kubernetes Cluster: You need a running Kubernetes cluster. This can be a local development cluster (e.g., Minikube or kind) or a cloud-based cluster (e.g., GKE, EKS, AKS).

  • Kubectl Installed: Kubectl, the Kubernetes command-line tool, should be installed and configured to interact with your cluster.

  • Helm Installed: Helm should be installed and configured. If you haven’t installed Helm, you can follow the official Helm installation guide.

Step 2: Add the Falco Helm Repository

Falco is available as a Helm chart, making installation straightforward. The first step is to add the official Falco Helm repository to your Helm configuration:

helm repo add falcosecurity https://falcosecurity.github.io/charts
helm repo update

This command adds the Falco Helm repository and updates your local Helm chart repository index.

Step 3: Install Falco Using Helm

With the Falco Helm repository added, you can now install Falco into your Kubernetes cluster. The installation process is simple and involves running the following command:

helm install falco falcosecurity/falco --namespace falco --create-namespace

This command installs Falco in a namespace called falco. The --create-namespace flag ensures that the namespace is created if it doesn’t already exist.

Optional Customization: You can customize the installation by providing additional configuration options. For example, you might want to enable specific output channels or adjust resource limits. To do this, create a custom values file and pass it to the Helm install command:

helm install falco falcosecurity/falco --namespace falco --values my-falco-values.yaml

Step 4: Verify the Installation

After installing Falco, it’s important to verify that it is running correctly and monitoring your cluster. You can do this by checking the status of the Falco pods:

kubectl get pods -n falco

You should see the Falco pod(s) running. The output will look something like this:

NAME                    READY   STATUS    RESTARTS   AGE
falco-xxxxxxx-yyyyy     1/1     Running   0          5m

Ensure that the pod is labeled correctly before checking the logs:

kubectl get pods --all-namespaces
kubectl label pod faclo-<uniquestring> -n falco app=falco

Next, check the Falco logs to ensure that it is working as expected:

kubectl logs -n falco -l app=falco

The logs should show that Falco is actively monitoring system calls and looking for rule violations. You might see output similar to this:

Starting Falco engine
Loading rules from file /etc/falco/falco_rules.yaml:
Loading rules from file /etc/falco/falco_rules.local.yaml:
Starting internal webserver, listening on port 8765

Step 5: Testing Falco

To ensure that Falco is properly set up and detecting events, you can perform a simple test by running a command that violates one of Falco’s default rules. For example, you can attempt to create a shell inside a container:

  1. Start a pod with a shell:

    kubectl run -it --rm test-shell --image=busybox -- sh
  2. In the shell, try to list the contents of the root directory:

    ls /
  3. Exit the shell.

Falco should detect this action and log a rule violation. You can check the Falco logs again to see the alert:

kubectl logs -n falco -l app=falco

You should see an alert similar to the following:

17:32:12.123456789: Warning A shell was spawned in a container with an attached terminal (user=root command=sh parent=<NA> container_id=abc123...)

This confirms that Falco is correctly monitoring your Kubernetes environment and generating alerts for rule violations.

Step 6: Basic Troubleshooting

If Falco is not working as expected, here are a few troubleshooting steps:

  • Pod Not Running: If the Falco pod is not running, check the pod events for any errors:

    kubectl describe pod <falco-pod-name> -n falco
  • No Alerts: If Falco is running but not generating any alerts, verify that it is monitoring the correct system calls and that the rules are properly loaded. You can also try adjusting the verbosity level in the Falco configuration.

  • High Resource Usage: If Falco is consuming more resources than expected, you might need to adjust the resource limits in the Helm values file or investigate which rules or system calls are causing the high usage.

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Last updated 9 months ago