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Implementing Microsegmentation with Guardicore

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Enhance network security through microsegmentation.

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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

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Inside SKILL.md

Written by mukul975

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" \
  -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

TermDefinition
MicrosegmentationNetwork security technique creating granular security zones around individual workloads or applications to control east-west traffic
Reveal ModeGuardicore's simulation mode that logs policy decisions without enforcing them, allowing validation before blocking
Ring-Fence PolicyIsolation policy that restricts all traffic into or out of a defined group of assets (e.g., PCI CDE)
Application Dependency MapVisual representation of discovered network communication patterns between workloads showing processes, ports, and protocols
East-West TrafficNetwork traffic flowing laterally between workloads within a data center, as opposed to north-south traffic crossing the perimeter
Process-Level VisibilityGuardicore'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:

  1. Deploy Guardicore agents on all 200 CDE servers and 300 non-CDE servers
  2. Run Reveal for 2 weeks to map all communication patterns into and out of the CDE
  3. Identify and remediate unexpected flows (e.g., dev servers connecting to production CDE)
  4. Create ring-fence policy blocking all non-CDE to CDE traffic by default
  5. Create explicit allow policies for validated CDE communication paths
  6. Test in Reveal mode for 1 week, validate no legitimate traffic blocked
  7. Switch to enforcement mode and monitor for violations
  8. 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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