implementing-runtime-security-with-tetragon

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-runtime-security-with-tetragon
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summary

Implement eBPF-based runtime security observability and enforcement in Kubernetes clusters using Cilium Tetragon for kernel-level threat detection and policy enforcement.

skill.md
name
implementing-runtime-security-with-tetragon
description
Implement eBPF-based runtime security observability and enforcement in Kubernetes clusters using Cilium Tetragon for kernel-level threat detection and policy enforcement.
domain
cybersecurity
subdomain
container-security
tags
- tetragon - ebpf - runtime-security - kubernetes - cilium - container-security - observability - kernel-security - cncf
version
'1.0'
author
mahipal
license
Apache-2.0
nist_ai_rmf
- MEASURE-2.7 - MAP-5.1 - MANAGE-2.4
atlas_techniques
- AML.T0070 - AML.T0066 - AML.T0082
nist_csf
- PR.PS-01 - PR.IR-01 - ID.AM-08 - DE.CM-01

Implementing Runtime Security with Tetragon

Overview

Tetragon is a CNCF project under Cilium that provides flexible Kubernetes-aware security observability and runtime enforcement using eBPF. By operating at the Linux kernel level, Tetragon can monitor and enforce policies on process execution, file access, network connections, and system calls with less than 1% performance overhead -- far more efficient than traditional user-space security agents.

When to Use

  • When deploying or configuring implementing runtime security with tetragon capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Kubernetes cluster v1.24+ with Helm 3.x installed
  • Linux kernel 5.4+ (5.10+ recommended for full eBPF feature support)
  • kubectl access with cluster-admin privileges
  • Familiarity with eBPF concepts and Kubernetes security primitives

Core Concepts

eBPF-Based Security

Tetragon attaches eBPF programs directly to kernel functions, enabling:

  • Process lifecycle tracking: Monitor every process creation, execution, and termination across all pods
  • File integrity monitoring: Detect unauthorized reads/writes to sensitive files
  • Network observability: Track all TCP/UDP connections with full pod context
  • System call filtering: Enforce policies on dangerous syscalls like ptrace, mount, or unshare

TracingPolicy Custom Resources

Tetragon uses TracingPolicy CRDs to define what kernel events to observe and what actions to take:

apiVersion: cilium.io/v1alpha1
kind: TracingPolicy
metadata:
  name: detect-privilege-escalation
spec:
  kprobes:
    - call: "security_bprm_check"
      syscall: false
      args:
        - index: 0
          type: "linux_binprm"
      selectors:
        - matchBinaries:
            - operator: "In"
              values:
                - "/bin/su"
                - "/usr/bin/sudo"
                - "/usr/bin/passwd"
          matchNamespaces:
            - namespace: Pid
              operator: NotIn
              values:
                - "host_ns"
          matchActions:
            - action: Post

Enforcement Actions

Tetragon can take three types of actions directly in the kernel:

  1. Sigkill: Immediately terminate the offending process
  2. Signal: Send a configurable signal to the process
  3. Override: Override the return value of a kernel function to deny an operation

Installation and Configuration

Step 1: Install Tetragon with Helm

helm repo add cilium https://helm.cilium.io
helm repo update

helm install tetragon cilium/tetragon \
  --namespace kube-system \
  --set tetragon.enableProcessCred=true \
  --set tetragon.enableProcessNs=true \
  --set tetragon.grpc.address="localhost:54321"

Step 2: Install the Tetragon CLI

GOOS=$(go env GOOS)
GOARCH=$(go env GOARCH)
curl -L --remote-name-all \
  https://github.com/cilium/tetragon/releases/latest/download/tetra-${GOOS}-${GOARCH}.tar.gz
tar -xzvf tetra-${GOOS}-${GOARCH}.tar.gz
sudo install tetra /usr/local/bin/

Step 3: Verify Installation

kubectl get pods -n kube-system -l app.kubernetes.io/name=tetragon
tetra status

Practical Implementation

Detecting Container Escape Attempts

Create a TracingPolicy to detect processes attempting to escape container namespaces:

apiVersion: cilium.io/v1alpha1
kind: TracingPolicy
metadata:
  name: detect-container-escape
spec:
  kprobes:
    - call: "__x64_sys_setns"
      syscall: true
      args:
        - index: 0
          type: "int"
        - index: 1
          type: "int"
      selectors:
        - matchNamespaces:
            - namespace: Pid
              operator: NotIn
              values:
                - "host_ns"
          matchActions:
            - action: Sigkill

Monitoring Sensitive File Access

Detect reads of sensitive credentials:

apiVersion: cilium.io/v1alpha1
kind: TracingPolicy
metadata:
  name: monitor-sensitive-files
spec:
  kprobes:
    - call: "security_file_open"
      syscall: false
      args:
        - index: 0
          type: "file"
      selectors:
        - matchArgs:
            - index: 0
              operator: "Prefix"
              values:
                - "/etc/shadow"
                - "/etc/kubernetes/pki"
                - "/var/run/secrets/kubernetes.io"
          matchActions:
            - action: Post

Blocking Crypto-Miner Execution

Prevent known crypto-mining binaries from executing:

apiVersion: cilium.io/v1alpha1
kind: TracingPolicy
metadata:
  name: block-cryptominers
spec:
  kprobes:
    - call: "security_bprm_check"
      syscall: false
      args:
        - index: 0
          type: "linux_binprm"
      selectors:
        - matchBinaries:
            - operator: "In"
              values:
                - "/usr/bin/xmrig"
                - "/tmp/xmrig"
                - "/usr/bin/minerd"
          matchActions:
            - action: Sigkill

Observing Events with Tetra CLI

Stream runtime events in real-time:

# Watch all process execution events
kubectl exec -n kube-system ds/tetragon -c tetragon -- \
  tetra getevents -o compact --process-only

# Filter events for a specific namespace
kubectl exec -n kube-system ds/tetragon -c tetragon -- \
  tetra getevents -o compact --namespace production

# Export events in JSON for SIEM integration
kubectl exec -n kube-system ds/tetragon -c tetragon -- \
  tetra getevents -o json | tee /var/log/tetragon-events.json

Integration with SIEM and Alerting

Export to Elasticsearch

# tetragon-helm-values.yaml
export:
  stdout:
    enabledCommand: true
    enabledArgs: true
  filenames:
    - /var/log/tetragon/tetragon.log
  elasticsearch:
    enabled: true
    url: "https://elasticsearch.monitoring:9200"
    index: "tetragon-events"

Prometheus Metrics

Tetragon exposes metrics at :2112/metrics:

apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: tetragon-metrics
  namespace: kube-system
spec:
  selector:
    matchLabels:
      app.kubernetes.io/name: tetragon
  endpoints:
    - port: metrics
      interval: 15s

Key Metrics and Alerts

MetricDescriptionAlert Threshold
tetragon_events_totalTotal security events observedSpike > 3x baseline
tetragon_policy_events_totalEvents matching TracingPoliciesAny Sigkill action
tetragon_process_exec_totalProcess executions trackedAnomalous new binaries
tetragon_missed_events_totalDropped events due to buffer overflow> 0 sustained

References

how to use implementing-runtime-security-with-tetragon

How to use implementing-runtime-security-with-tetragon on Cursor

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1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add implementing-runtime-security-with-tetragon
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-runtime-security-with-tetragon

The skills CLI fetches implementing-runtime-security-with-tetragon from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/implementing-runtime-security-with-tetragon

Reload or restart Cursor to activate implementing-runtime-security-with-tetragon. Access the skill through slash commands (e.g., /implementing-runtime-security-with-tetragon) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.653 reviews
  • Omar Bhatia· Dec 24, 2024

    implementing-runtime-security-with-tetragon is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Jin Jackson· Dec 20, 2024

    implementing-runtime-security-with-tetragon has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Noah Martin· Dec 16, 2024

    implementing-runtime-security-with-tetragon reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Noor Jackson· Dec 4, 2024

    Solid pick for teams standardizing on skills: implementing-runtime-security-with-tetragon is focused, and the summary matches what you get after install.

  • Jin Robinson· Nov 27, 2024

    Solid pick for teams standardizing on skills: implementing-runtime-security-with-tetragon is focused, and the summary matches what you get after install.

  • Soo Rahman· Nov 15, 2024

    implementing-runtime-security-with-tetragon fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Mateo White· Nov 7, 2024

    I recommend implementing-runtime-security-with-tetragon for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Min Chawla· Nov 7, 2024

    Useful defaults in implementing-runtime-security-with-tetragon — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Mateo Srinivasan· Oct 26, 2024

    Useful defaults in implementing-runtime-security-with-tetragon — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Noah Chen· Oct 26, 2024

    implementing-runtime-security-with-tetragon reduced setup friction for our internal harness; good balance of opinion and flexibility.

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