Skip to content
Skillpedia
Deploy & cloud (DevOps)35k · #5909

implementing-microsegmentation-with-guardicore

Implements microsegmentation with Akamai Guardicore. Maps dependencies, visualizes traffic, and creates granular network policies for VMs and containers.

What it does

This tool helps secure your network by controlling exactly what communication is allowed between your servers and applications. It maps how they talk to each other and creates security rules to block unwanted traffic, especially to prevent attacks from spreading.

When to use it

  • ✓To stop attacks from spreading within your data center.
  • ✓When you need to understand how your applications communicate before setting security rules.
  • ✓To meet security regulations like PCI DSS or HIPAA that require network segmentation.

Example of what to ask your AI

“Set up microsegmentation to protect the customer data environment.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/mukul975/Anthropic-Cybersecurity-Skills/blob/main/skills/implementing-microsegmentation-with-guardicore/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/mukul975/Anthropic-Cybersecurity-Skills/blob/main/skills/implementing-microsegmentation-with-guardicore/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

First, you install a small program (agent) on your servers. Then, you use a tool to visualize all network traffic between your applications. Finally, you create rules to only allow necessary communication and block the rest.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-microsegmentation-with-guardicore

Or download just the file:

curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/implementing-microsegmentation-with-guardicore/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Implementing Microsegmentation with Guardicore

When to Use

  • When implementing east-west traffic controls to prevent lateral movement within data centers
  • When needing application-level visibility into network communication patterns before writing segmentation policies
  • When segmenting workloads across heterogeneous environments (VMs, containers, bare metal, cloud)
  • When compliance frameworks (PCI DSS, HIPAA) require network segmentation validation
  • When deploying zero trust at the network layer with process-level granularity

Do not use for perimeter-only security (use traditional firewalls), for environments with fewer than 50 workloads where VLANs/security groups suffice, or when network team lacks capacity for ongoing policy management.

Prerequisites

  • Akamai Guardicore Segmentation license (Enterprise or Premium)
  • Guardicore Management Server deployed (on-prem or SaaS)
  • Agent deployment access to target workloads (Linux, Windows, Kubernetes)
  • Network visibility: SPAN/TAP ports or VPC flow logs for agentless collection
  • Application owner engagement for dependency validation

Workflow

Step 1: Deploy Guardicore Agents on Workloads

Install agents to collect process-level network communication data.

# Linux agent installation
curl -sSL https://management.guardicore.com/api/v3.0/agents/download/linux \
  -H "Authorization: Bearer ${GC_API_TOKEN}" \
  -o gc-agent-installer.sh
chmod +x gc-agent-installer.sh
sudo ./gc-agent-installer.sh \
  --management-url=https://management.guardicore.com \
  --site-id=datacenter-east \
  --label="web-tier"

# Windows agent installation (PowerShell)
# Invoke-WebRequest -Uri "https://management.guardicore.com/api/v3.0/agents/download/windows" `
#   -Headers @{"Authorization"="Bearer $GC_API_TOKEN"} `
#   -OutFile gc-agent-installer.exe
# Start-Process -FilePath .\gc-agent-installer.exe `
#   -ArgumentList "--management-url=https://management.guardicore.com","--site-id=datacenter-east" `
#   -Wait

# Kubernetes DaemonSet deployment
cat > gc-daemonset.yaml << 'EOF'
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: guardicore-agent
  namespace: guardicore
spec:
  selector:
    matchLabels:
      app: gc-agent
  template:
    metadata:
      labels:
        app: gc-agent
    spec:
      hostNetwork: true
      hostPID: true
      containers:
      - name: gc-agent
        image: guardicore/agent:latest
        securityContext:
          privileged: true
        env:
        - name: GC_MANAGEMENT_URL
          value: "https://management.guardicore.com"
        - name: GC_API_KEY
          valueFrom:
            secretKeyRef:
              name: gc-credentials
              key: api-key
        volumeMounts:
        - mountPath: /host
          name: host-root
      volumes:
      - name: host-root
        hostPath:
          path: /
EOF
kubectl apply -f gc-daemonset.yaml

# Verify agent enrollment
curl -s "https://management.guardicore.com/api/v3.0/agents?status=active" \
  -H "Authorization: Bearer ${GC_API_TOKEN}" | python3 -m json.tool

Step 2: Map Application Dependencies with Reveal

Use Guardicore Reveal to discover and visualize application communication patterns.

# Query discovered application flows via API
curl -s "https://management.guardicore.com/api/v3.0/connections" \
  -H "Authorization: Bearer ${GC_API_TOKEN}" \
  -d '{
    "time_range": {"from": "2026-02-17T00:00:00Z", "to": "2026-02-24T00:00:00Z"},
    "filter": {
      "source_label": "web-tier",
      "destination_label": "app-tier"
    },
    "aggregation": "process",
    "limit": 1000
  }' | python3 -m json.tool

# Export application dependency map
curl -s "https://management.guardicore.com/api/v3.0/maps/export" \
  -H "Authorization: Bearer ${GC_API_TOKEN}" \
  -d '{
    "format": "json",
    "labels": ["web-tier", "app-tier", "db-tier"],
    "time_range": "7d"
  }' -o app-dependency-map.json

# Typical discovery findings:
# web-tier -> app-tier: TCP 8080, 8443 (expected)
# app-tier -> db-tier: TCP 5432, 3306 (expected)
# web-tier -> db-tier: TCP 5432 (UNEXPECTED - should be blocked)
# app-tier -> internet: TCP 443 (verify if needed)

Step 3: Create Segmentation Labels and Policies

Define labels and create ring-fence policies around applications.

# Create labels for application tiers
curl -X POST "https://management.guardicore.com/api/v3.0/labels" \
  -H "Authorization: Bearer ${GC_API_TOKEN}" \
  -H "Content-Type: application/json" \

…
FAQ

What is microsegmentation?

It's a security technique that divides the network into small secure zones, controlling traffic between them to limit the damage from an attack.

What is east-west traffic?

It's network traffic that occurs between servers within the same data center, as opposed to traffic entering or leaving the network (north-south).

Do I need a special license?

Yes, an Akamai Guardicore Segmentation license (Enterprise or Premium) is required.

Details

Original description by the author

Implements microsegmentation with Akamai Guardicore Segmentation to map application dependencies, visualize east-west traffic flows, and create granular, least-privilege network policies across VMs, containers, bare metal, and cloud. Use when blocking lateral movement in a data center or when PCI DSS/HIPAA compliance requires validated network segmentation. '

repo: mukul975/Anthropic-Cybersecurity-Skills

Popularity

GitHub stars
35k
Ranking position
#5909
License
Apache-2.0
Updated
8/31/2026

Is this skill useful?

0

Sign in to vote.

Comments

  • …

More skills from this repository

Similar skills