implementing-ebpf-security-monitoring

# Implementing eBPF Security Monitoring ## When to Use - When deploying kernel-level runtime security monitoring on Linux hosts or Kubernetes clusters - When you need sub-millisecond visibility into process execution, network connections, and file access - When traditional userspace monitoring tools introduce unacceptable performance overhead - When building detection pipelines that require in-kernel filtering before events reach userspace - When enforcing runtime security policies (kill process, send signal) at the kernel level ## Prerequisites - Linux kernel 5.3+ with BTF (BPF Type Format) support enabled - Kubernetes 1.24+ cluster (for Kubernetes deployment) or standalone Linux host - Helm 3.x installed (for Kubernetes deployment) - `kubectl` configured with cluster access - `tetra` CLI installed for local event streaming - Python 3.8+ with `requests`, `kubernetes`, `pyyaml` dependencies - Root or CAP_BPF/CAP_SYS_ADMIN capabilities for eBPF program loading ## Instructions ### 1. Install Tetragon on Kubernetes Deploy Tetragon via Helm to get default process lifecycle observability: ```bash helm repo add cilium https://helm.cilium.io helm repo update helm install tetragon cilium/tetragon -n kube-system \ --set tetragon.enableProcessCred=true \ --set tetragon.enableProcessNs=true ``` Verify the installation: ```bash kubectl get pods -n kube-system -l app.kubernetes.io/name=tetragon kubectl logs -n kube-system -l app.kubernetes.io/name=tetragon -c export-stdout -...