skills/configuring-microsegmentation-for-zero-trust/SKILL.md
Configures microsegmentation policies to enforce least-privilege workload-to-workload access using tools such as VMware NSX, Illumio, and Calico, preventing lateral movement in zero trust architectures. Use when designing or implementing network microsegmentation as part of a zero trust architecture aligned with NIST SP 800-207.
npx skillsauth add mukul975/cyber-skills configuring-microsegmentation-for-zero-trustInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Microsegmentation divides a network into granular security zones, enforcing least-privilege access between workloads at the application layer rather than relying on traditional VLAN-based segmentation. In a zero trust architecture, microsegmentation eliminates implicit trust between workloads within the same network segment, preventing lateral movement even after an attacker gains initial access.
This skill covers designing microsegmentation policies using workload identity, implementing host-based and network-based enforcement, and validating segmentation effectiveness with tools like Illumio Core and VMware NSX.
Traditional Segmentation Microsegmentation
┌─────────────────┐ ┌──────────────────────┐
│ VLAN 10 │ │ Workload A ←policy→ │
│ ┌───┐ ┌───┐ │ │ Workload B ←policy→ │
│ │ A │ │ B │ │ │ Workload C ←policy→ │
│ └───┘ └───┘ │ │ Workload D ←policy→ │
│ (trust each │ │ (zero trust between │
│ other) │ │ every pair) │
└─────────────────┘ └──────────────────────┘
Before creating segmentation policies, discover actual communication flows between workloads using traffic telemetry. Tools like Illumio, Guardicore, and AppDynamics provide application dependency maps showing which workloads communicate, over which ports, and how frequently.
Draft policies in monitor/visibility mode before enforcement. This allows validation that proposed rules will not break legitimate traffic while identifying unnecessary or risky communication paths.
Modern microsegmentation uses labels (role, application, environment, location) instead of IP-based rules. Label-based policies are portable across environments and survive IP changes during migrations.
Isolate critical applications (PCI cardholder data environment, SWIFT financial systems, healthcare PHI) with strict allow-list policies that deny all traffic not explicitly permitted.
Deploy Visibility Agents
Build Application Dependency Map
Assign Labels
Define Segmentation Zones
Create Allow-List Policies
Model Policies in Test Mode
Enforce Incrementally
Validate Segmentation
development
Detect Pass-the-Hash (T1550.002) attacks by analyzing NTLM authentication patterns, flagging Type 3 logons using NTLM where Kerberos would be expected, and correlating with credential-dumping indicators. Use when threat hunting for lateral movement via stolen NTLM hashes, triaging EDR/SIEM alerts on suspicious NTLM logons, scoping compromise during incident response, or validating detection coverage in a purple team exercise.
testing
Detect and respond to OAuth token theft and replay in Microsoft Entra ID (Azure AD), covering access token theft, refresh token replay, Primary Refresh Token (PRT) abuse, pass-the-cookie attacks, and Token Protection conditional access policies. Use for impossible-travel or anomalous token-usage alerts, suspected session hijacking, sign-in log analysis, or configuring token-binding defenses in Azure/M365.
development
Detect NTLM relay attacks (T1557.001) by correlating Windows Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB/LDAP signing, and flagging NTLMv2-to-NTLMv1 downgrades. Use for hunting credential relay in NTLM-enabled AD, investigating auth-source anomalies, building SIEM correlation rules, or responding to PetitPotam/DFSCoerce/PrinterBug alerts.
data-ai
Detect network reconnaissance and port scanning using Suricata and Snort IDS signatures, threshold-based detection rules, and traffic anomaly analysis to identify Nmap, Masscan, and custom scanning activity.