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332 lines
12 KiB
Markdown
332 lines
12 KiB
Markdown
---
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name: implementing-microsegmentation-with-guardicore
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description: >
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Implementing microsegmentation using Akamai Guardicore Segmentation to map application
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dependencies, create granular network policies, visualize east-west traffic flows,
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and enforce least-privilege communication between workloads across data centers and cloud.
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domain: cybersecurity
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subdomain: zero-trust-architecture
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tags: [microsegmentation, guardicore, akamai, zero-trust, east-west-traffic, network-segmentation, lateral-movement]
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version: "1.0"
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author: mahipal
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license: Apache-2.0
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---
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# Implementing Microsegmentation with Guardicore
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## When to Use
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- When implementing east-west traffic controls to prevent lateral movement within data centers
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- When needing application-level visibility into network communication patterns before writing segmentation policies
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- When segmenting workloads across heterogeneous environments (VMs, containers, bare metal, cloud)
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- When compliance frameworks (PCI DSS, HIPAA) require network segmentation validation
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- When deploying zero trust at the network layer with process-level granularity
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**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.
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## Prerequisites
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- Akamai Guardicore Segmentation license (Enterprise or Premium)
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- Guardicore Management Server deployed (on-prem or SaaS)
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- Agent deployment access to target workloads (Linux, Windows, Kubernetes)
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- Network visibility: SPAN/TAP ports or VPC flow logs for agentless collection
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- Application owner engagement for dependency validation
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## Workflow
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### Step 1: Deploy Guardicore Agents on Workloads
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Install agents to collect process-level network communication data.
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```bash
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# Linux agent installation
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curl -sSL https://management.guardicore.com/api/v3.0/agents/download/linux \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-o gc-agent-installer.sh
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chmod +x gc-agent-installer.sh
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sudo ./gc-agent-installer.sh \
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--management-url=https://management.guardicore.com \
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--site-id=datacenter-east \
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--label="web-tier"
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# Windows agent installation (PowerShell)
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# Invoke-WebRequest -Uri "https://management.guardicore.com/api/v3.0/agents/download/windows" `
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# -Headers @{"Authorization"="Bearer $GC_API_TOKEN"} `
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# -OutFile gc-agent-installer.exe
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# Start-Process -FilePath .\gc-agent-installer.exe `
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# -ArgumentList "--management-url=https://management.guardicore.com","--site-id=datacenter-east" `
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# -Wait
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# Kubernetes DaemonSet deployment
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cat > gc-daemonset.yaml << 'EOF'
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apiVersion: apps/v1
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kind: DaemonSet
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metadata:
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name: guardicore-agent
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namespace: guardicore
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spec:
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selector:
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matchLabels:
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app: gc-agent
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template:
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metadata:
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labels:
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app: gc-agent
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spec:
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hostNetwork: true
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hostPID: true
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containers:
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- name: gc-agent
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image: guardicore/agent:latest
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securityContext:
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privileged: true
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env:
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- name: GC_MANAGEMENT_URL
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value: "https://management.guardicore.com"
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- name: GC_API_KEY
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valueFrom:
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secretKeyRef:
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name: gc-credentials
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key: api-key
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volumeMounts:
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- mountPath: /host
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name: host-root
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volumes:
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- name: host-root
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hostPath:
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path: /
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EOF
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kubectl apply -f gc-daemonset.yaml
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# Verify agent enrollment
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curl -s "https://management.guardicore.com/api/v3.0/agents?status=active" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" | python3 -m json.tool
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```
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### Step 2: Map Application Dependencies with Reveal
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Use Guardicore Reveal to discover and visualize application communication patterns.
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```bash
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# Query discovered application flows via API
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curl -s "https://management.guardicore.com/api/v3.0/connections" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-d '{
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"time_range": {"from": "2026-02-17T00:00:00Z", "to": "2026-02-24T00:00:00Z"},
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"filter": {
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"source_label": "web-tier",
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"destination_label": "app-tier"
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},
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"aggregation": "process",
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"limit": 1000
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}' | python3 -m json.tool
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# Export application dependency map
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curl -s "https://management.guardicore.com/api/v3.0/maps/export" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-d '{
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"format": "json",
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"labels": ["web-tier", "app-tier", "db-tier"],
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"time_range": "7d"
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}' -o app-dependency-map.json
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# Typical discovery findings:
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# web-tier -> app-tier: TCP 8080, 8443 (expected)
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# app-tier -> db-tier: TCP 5432, 3306 (expected)
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# web-tier -> db-tier: TCP 5432 (UNEXPECTED - should be blocked)
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# app-tier -> internet: TCP 443 (verify if needed)
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```
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### Step 3: Create Segmentation Labels and Policies
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Define labels and create ring-fence policies around applications.
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```bash
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# Create labels for application tiers
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curl -X POST "https://management.guardicore.com/api/v3.0/labels" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-H "Content-Type: application/json" \
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-d '{
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"name": "PCI-CDE",
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"description": "Cardholder Data Environment workloads",
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"criteria": {"ip_ranges": ["10.10.0.0/16"]},
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"color": "#FF0000"
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}'
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# Create segmentation policy: Allow web-to-app communication
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curl -X POST "https://management.guardicore.com/api/v3.0/policies" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-H "Content-Type: application/json" \
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-d '{
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"name": "Web-to-App Allowed",
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"action": "ALLOW",
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"priority": 100,
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"source": {"labels": ["web-tier"]},
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"destination": {"labels": ["app-tier"]},
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"services": [
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{"protocol": "TCP", "port": 8080},
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{"protocol": "TCP", "port": 8443}
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],
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"log": true,
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"enabled": true,
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"section": "application-segmentation"
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}'
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# Create deny policy: Block web-to-database direct access
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curl -X POST "https://management.guardicore.com/api/v3.0/policies" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-H "Content-Type: application/json" \
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-d '{
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"name": "Block Web-to-DB Direct",
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"action": "DENY",
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"priority": 200,
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"source": {"labels": ["web-tier"]},
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"destination": {"labels": ["db-tier"]},
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"services": [{"protocol": "TCP", "port_range": "1-65535"}],
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"log": true,
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"alert": true,
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"enabled": true
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}'
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# Create ring-fence policy for PCI CDE
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curl -X POST "https://management.guardicore.com/api/v3.0/policies" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-H "Content-Type: application/json" \
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-d '{
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"name": "PCI CDE Ring Fence",
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"action": "DENY",
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"priority": 50,
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"source": {"labels": ["!PCI-CDE"]},
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"destination": {"labels": ["PCI-CDE"]},
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"services": [{"protocol": "TCP", "port_range": "1-65535"}],
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"log": true,
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"alert": true,
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"enabled": true
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}'
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```
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### Step 4: Test Policies in Reveal Mode Before Enforcement
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Simulate policy enforcement without blocking traffic.
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```bash
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# Enable reveal mode (log-only) for new policies
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curl -X PATCH "https://management.guardicore.com/api/v3.0/policies/POLICY_ID" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-d '{"enforcement_mode": "REVEAL"}'
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# Check what would be blocked in reveal mode
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curl -s "https://management.guardicore.com/api/v3.0/violations" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-d '{
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"time_range": "24h",
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"policy_id": "POLICY_ID",
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"limit": 100
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}' | python3 -c "
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import json, sys
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data = json.load(sys.stdin)
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for v in data.get('violations', []):
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print(f\"{v['source_ip']}:{v['source_process']} -> {v['dest_ip']}:{v['dest_port']} [{v['action']}]\")
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"
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# After validation, switch to enforcement
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curl -X PATCH "https://management.guardicore.com/api/v3.0/policies/POLICY_ID" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-d '{"enforcement_mode": "ENFORCE"}'
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```
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### Step 5: Monitor and Respond to Policy Violations
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Set up alerting and continuous monitoring for segmentation violations.
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```bash
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# Configure SIEM integration for policy violations
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curl -X POST "https://management.guardicore.com/api/v3.0/integrations/syslog" \
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-H "Authorization: Bearer ${GC_API_TOKEN}" \
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-d '{
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"name": "Splunk SIEM",
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"host": "splunk-syslog.company.com",
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"port": 514,
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"protocol": "TCP",
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"format": "CEF",
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"events": ["policy_violation", "agent_status", "deception_alert"]
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}'
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# Splunk query for microsegmentation violations
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# index=guardicore sourcetype=guardicore:policy
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# | where action="DENY" AND enforcement_mode="ENFORCE"
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# | stats count by src_ip, dst_ip, dst_port, policy_name
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# | sort -count
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```
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## Key Concepts
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| Term | Definition |
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|------|------------|
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| Microsegmentation | Network security technique creating granular security zones around individual workloads or applications to control east-west traffic |
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| Reveal Mode | Guardicore's simulation mode that logs policy decisions without enforcing them, allowing validation before blocking |
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| Ring-Fence Policy | Isolation policy that restricts all traffic into or out of a defined group of assets (e.g., PCI CDE) |
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| Application Dependency Map | Visual representation of discovered network communication patterns between workloads showing processes, ports, and protocols |
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| East-West Traffic | Network traffic flowing laterally between workloads within a data center, as opposed to north-south traffic crossing the perimeter |
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| Process-Level Visibility | Guardicore's ability to identify which process on a workload initiated or received a network connection |
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## Tools & Systems
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- **Akamai Guardicore Segmentation**: Agent-based microsegmentation platform with application visualization and policy enforcement
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- **Guardicore Reveal**: Network visualization engine mapping application dependencies across hybrid environments
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- **Guardicore Centra**: Management console for policy creation, monitoring, and incident investigation
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- **Guardicore Agents**: Lightweight agents deployed on workloads collecting process-level network telemetry
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- **Guardicore Insight**: Analytics engine for compliance reporting and segmentation effectiveness measurement
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## Common Scenarios
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### Scenario: PCI DSS Microsegmentation for E-Commerce Platform
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**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.
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**Approach**:
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1. Deploy Guardicore agents on all 200 CDE servers and 300 non-CDE servers
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2. Run Reveal for 2 weeks to map all communication patterns into and out of the CDE
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3. Identify and remediate unexpected flows (e.g., dev servers connecting to production CDE)
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4. Create ring-fence policy blocking all non-CDE to CDE traffic by default
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5. Create explicit allow policies for validated CDE communication paths
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6. Test in Reveal mode for 1 week, validate no legitimate traffic blocked
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7. Switch to enforcement mode and monitor for violations
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8. Generate PCI DSS segmentation validation report showing enforced controls
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**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.
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## Output Format
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```
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Microsegmentation Deployment Report
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==================================================
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Organization: E-Commerce Corp
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Report Date: 2026-02-23
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AGENT DEPLOYMENT:
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Total workloads: 500
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Agents installed: 487 (97.4%)
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Agents active: 482 (98.9%)
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Agentless (flow logs): 13
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POLICY COVERAGE:
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Total policies: 45
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Allow rules: 38
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Deny rules: 7
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Reveal mode: 3
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Enforced: 42
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TRAFFIC ANALYSIS (7 days):
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Total flows observed: 2,456,789
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Flows matching allow: 2,441,234 (99.4%)
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Flows matching deny: 15,555 (0.6%)
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Unclassified flows: 0
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PCI CDE ISOLATION:
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CDE workloads: 200
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Ring-fence violations: 0 (last 30 days)
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Authorized CDE entry points: 4
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Lateral movement paths blocked: 95%
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```
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