implementing-runtime-security-with-tetragon▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Implement eBPF-based runtime security observability and enforcement in Kubernetes clusters using Cilium Tetragon for kernel-level threat detection and policy enforcement.
| 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:
- Sigkill: Immediately terminate the offending process
- Signal: Send a configurable signal to the process
- 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
| Metric | Description | Alert Threshold |
|---|---|---|
tetragon_events_total | Total security events observed | Spike > 3x baseline |
tetragon_policy_events_total | Events matching TracingPolicies | Any Sigkill action |
tetragon_process_exec_total | Process executions tracked | Anomalous new binaries |
tetragon_missed_events_total | Dropped events due to buffer overflow | > 0 sustained |
References
How to use implementing-runtime-security-with-tetragon on Cursor
AI-first code editor with Composer
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
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches implementing-runtime-security-with-tetragon from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
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.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
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.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 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▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★53 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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