
Implementing Microsegmentation with Guardicore
FreeEnhance network security through microsegmentation.
Free · Opens the source repo
What Implementing Microsegmentation with Guardicore does
This skill provides a framework for implementing microsegmentation using Akamai Guardicore Segmentation. It is designed to help organizations map application dependencies, visualize east-west traffic flows, and establish granular, least-privilege network policies across diverse environments, including virtual machines, containers, bare metal, and cloud infrastructures. The focus is on preventing lateral movement within data centers and ensuring compliance with regulations such as PCI DSS and HIPAA that mandate validated network segmentation.
The workflow begins with the deployment of Guardicore agents on target workloads to collect detailed process-level network communication data. This is followed by using Guardicore Reveal to discover and visualize application communication patterns, allowing users to understand how different components interact within their network. After mapping dependencies, users can create segmentation labels and policies to enforce strict communication rules, thereby enhancing security posture and reducing the attack surface.
This skill is particularly beneficial for security professionals and network administrators who are tasked with implementing zero trust architectures and need to manage complex network environments. By leveraging this skill, users can effectively block unauthorized lateral movement and ensure that only necessary traffic is permitted between application tiers, thus maintaining a robust security framework.
Overall, this skill is a valuable asset for organizations looking to strengthen their network security through effective microsegmentation practices, ensuring compliance with industry standards while maintaining operational efficiency.
When to use it
Use this skill when implementing east-west traffic controls, especially in environments requiring granular visibility and compliance with standards like PCI DSS or HIPAA.
When not to use it
This is not suitable for perimeter-only security needs or for smaller environments where simpler solutions like VLANs suffice.
What you can build with it
Deploying in a Data Center
Use this skill to implement east-west traffic controls in a data center, preventing unauthorized lateral movement.
Compliance with PCI DSS
Utilize this skill to ensure your network segmentation meets PCI DSS requirements for cardholder data environments.
Visualizing Application Dependencies
Leverage the skill to map and visualize application communication patterns before creating segmentation policies.
How to install Implementing Microsegmentation with Guardicore
View source1. Install with the skills CLI
npx skills add mukul975/anthropic-cybersecurity-skills/implementing-microsegmentation-with-guardicore --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by mukul975Implementing 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" \
-d '{
"name": "PCI-CDE",
"description": "Cardholder Data Environment workloads",
"criteria": {"ip_ranges": ["10.10.0.0/16"]},
"color": "#FF0000"
}'
# Create segmentation policy: Allow web-to-app communication
curl -X POST "https://management.guardicore.com/api/v3.0/policies" \
-H "Authorization: Bearer ${GC_API_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"name": "Web-to-App Allowed",
"action": "ALLOW",
"priority": 100,
"source": {"labels": ["web-tier"]},
"destination": {"labels": ["app-tier"]},
"services": [
{"protocol": "TCP", "port": 8080},
{"protocol": "TCP", "port": 8443}
],
"log": true,
"enabled": true,
"section": "application-segmentation"
}'
# Create deny policy: Block web-to-database direct access
curl -X POST "https://management.guardicore.com/api/v3.0/policies" \
-H "Authorization: Bearer ${GC_API_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"name": "Block Web-to-DB Direct",
"action": "DENY",
"priority": 200,
"source": {"labels": ["web-tier"]},
"destination": {"labels": ["db-tier"]},
"services": [{"protocol": "TCP", "port_range": "1-65535"}],
"log": true,
"alert": true,
"enabled": true
}'
# Create ring-fence policy for PCI CDE
curl -X POST "https://management.guardicore.com/api/v3.0/policies" \
-H "Authorization: Bearer ${GC_API_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"name": "PCI CDE Ring Fence",
"action": "DENY",
"priority": 50,
"source": {"labels": ["!PCI-CDE"]},
"destination": {"labels": ["PCI-CDE"]},
"services": [{"protocol": "TCP", "port_range": "1-65535"}],
"log": true,
"alert": true,
"enabled": true
}'
Step 4: Test Policies in Reveal Mode Before Enforcement
Simulate policy enforcement without blocking traffic.
# Enable reveal mode (log-only) for new policies
curl -X PATCH "https://management.guardicore.com/api/v3.0/policies/POLICY_ID" \
-H "Authorization: Bearer ${GC_API_TOKEN}" \
-d '{"enforcement_mode": "REVEAL"}'
# Check what would be blocked in reveal mode
curl -s "https://management.guardicore.com/api/v3.0/violations" \
-H "Authorization: Bearer ${GC_API_TOKEN}" \
-d '{
"time_range": "24h",
"policy_id": "POLICY_ID",
"limit": 100
}' | python3 -c "
import json, sys
data = json.load(sys.stdin)
for v in data.get('violations', []):
print(f\"{v['source_ip']}:{v['source_process']} -> {v['dest_ip']}:{v['dest_port']} [{v['action']}]\")
"
# After validation, switch to enforcement
curl -X PATCH "https://management.guardicore.com/api/v3.0/policies/POLICY_ID" \
-H "Authorization: Bearer ${GC_API_TOKEN}" \
-d '{"enforcement_mode": "ENFORCE"}'
Step 5: Monitor and Respond to Policy Violations
Set up alerting and continuous monitoring for segmentation violations.
# Configure SIEM integration for policy violations
curl -X POST "https://management.guardicore.com/api/v3.0/integrations/syslog" \
-H "Authorization: Bearer ${GC_API_TOKEN}" \
-d '{
"name": "Splunk SIEM",
"host": "splunk-syslog.company.com",
"port": 514,
"protocol": "TCP",
"format": "CEF",
"events": ["policy_violation", "agent_status", "deception_alert"]
}'
# Splunk query for microsegmentation violations
# index=guardicore sourcetype=guardicore:policy
# | where action="DENY" AND enforcement_mode="ENFORCE"
# | stats count by src_ip, dst_ip, dst_port, policy_name
# | sort -count
Key Concepts
| Term | Definition |
|---|---|
| Microsegmentation | Network security technique creating granular security zones around individual workloads or applications to control east-west traffic |
| Reveal Mode | Guardicore's simulation mode that logs policy decisions without enforcing them, allowing validation before blocking |
| Ring-Fence Policy | Isolation policy that restricts all traffic into or out of a defined group of assets (e.g., PCI CDE) |
| Application Dependency Map | Visual representation of discovered network communication patterns between workloads showing processes, ports, and protocols |
| East-West Traffic | Network traffic flowing laterally between workloads within a data center, as opposed to north-south traffic crossing the perimeter |
| Process-Level Visibility | Guardicore's ability to identify which process on a workload initiated or received a network connection |
Tools & Systems
- Akamai Guardicore Segmentation: Agent-based microsegmentation platform with application visualization and policy enforcement
- Guardicore Reveal: Network visualization engine mapping application dependencies across hybrid environments
- Guardicore Centra: Management console for policy creation, monitoring, and incident investigation
- Guardicore Agents: Lightweight agents deployed on workloads collecting process-level network telemetry
- Guardicore Insight: Analytics engine for compliance reporting and segmentation effectiveness measurement
Common Scenarios
Scenario: PCI DSS Microsegmentation for E-Commerce Platform
Context: An e-commerce company must isolate its Cardholder Data Environment (CDE) from the rest of the corporate network for PCI DSS compliance. The CDE spans 200 servers across on-prem and AWS.
Approach:
- Deploy Guardicore agents on all 200 CDE servers and 300 non-CDE servers
- Run Reveal for 2 weeks to map all communication patterns into and out of the CDE
- Identify and remediate unexpected flows (e.g., dev servers connecting to production CDE)
- Create ring-fence policy blocking all non-CDE to CDE traffic by default
- Create explicit allow policies for validated CDE communication paths
- Test in Reveal mode for 1 week, validate no legitimate traffic blocked
- Switch to enforcement mode and monitor for violations
- Generate PCI DSS segmentation validation report showing enforced controls
Pitfalls: Agent deployment on legacy systems (Windows Server 2012) may require manual installation. Ring-fence policies must account for management traffic (monitoring, patching, backup). Start with broad allow rules and progressively tighten. Application owners must validate dependency maps before enforcement.
Output Format
Microsegmentation Deployment Report
==================================================
Organization: E-Commerce Corp
Report Date: 2026-02-23
AGENT DEPLOYMENT:
Total workloads: 500
Agents installed: 487 (97.4%)
Agents active: 482 (98.9%)
Agentless (flow logs): 13
POLICY COVERAGE:
Total policies: 45
Allow rules: 38
Deny rules: 7
Reveal mode: 3
Enforced: 42
TRAFFIC ANALYSIS (7 days):
Total flows observed: 2,456,789
Flows matching allow: 2,441,234 (99.4%)
Flows matching deny: 15,555 (0.6%)
Unclassified flows: 0
PCI CDE ISOLATION:
CDE workloads: 200
Ring-fence violations: 0 (last 30 days)
Authorized CDE entry points: 4
Lateral movement paths blocked: 95%
Frequently asked questions about Implementing Microsegmentation with Guardicore
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