Least-Privilege Network Access for Apps, Users & Workloads
Microsegmentation prevents lateral movement by enforcing least-privilege network policyβbetween users β apps, workload β workload, tier β tier, and device β serviceβon premises, in cloud, and across Kubernetes.
SolveForce designs microsegmentation thatβs identity-aware, posture-aware, and auditableβintegrated with ZTNA/SASE, NAC, EDR/XDR, and SIEM/SOARβso you can contain breaches, pass audits, and ship changes safely.
- π (888) 765-8301
- βοΈ contact@solveforce.com
Where this fits in our model:
π Security (Semantics) β Cybersecurity β’ π Per-Session Access β ZTNA / SASE
π€ Identity/Posture β IAM / SSO / MFA β’ MDM / UEM β’ EDR / MDR / XDR
π§ Fabric β Networks & Data Centers β’ π Transport β SD-WAN β’ πͺ Edge β NAC
π Evidence & Automation β SIEM / SOAR β’ π§ EastβWest Detection β NDR
π― Outcomes (Why Microsegmentation)
- Containment by default β block lateral movement; allow only required flows.
- Identity- & posture-aware β rules bind to user/group, workload/service, and device health.
- Uniform model β one least-privilege approach across DC, cloud, K8s, campus, and remote.
- Audit-ready β policy as code, change diffs, enforcement logs to SIEM.
- Safer changes β staged rollouts, simulation/dry-run, automatic rollback via SOAR.
π§ Scope (What We Segment)
- User β App (Access Edge) β staff/contractors to specific apps only, never to subnets. β ZTNA β’ SASE
- Workload β Workload (EastβWest) β app tiers (webβappβDB), microservices, API backends.
- Zone β Zone (Macro) β PCI/PHI/CUI zones, admin/privileged networks, OT/IT boundaries.
- Device Classes β corp laptops vs BYOD; IoT/OT (cameras, printers, POS, sensors) isolated by purpose. β NAC
π§± Building Blocks (Spelled Out)
- Policy Abstractions β define intentions as Service β Service, Role β App, Label β Label, not IPs.
- Identity Signals β user/group (IdP), device posture (UEM/EDR), service identity (mTLS cert/SPIFFE). β IAM / SSO / MFA β’ MDM / UEM β’ EDR / MDR / XDR β’ PKI
- Enforcement Planes
- Host-based (agent/EBPF) β kernel firewall rules by process/service identity.
- Overlay (service mesh) β sidecar/intent (L7/K8s).
- Network (fabric/SGT/VLAN/ACL/VXLAN) β fabric tags & ACLs for macro + IoT/OT.
- Edge (ZTNA/SASE) β per-session allow to a single app.
- Visibility & Evidence β flow maps from NDR/NetFlow; change/effect logs to SIEM/SOAR. β NDR β’ SIEM / SOAR
π§ Policy Model (Identity β Device β App β Data β Context)
A rule compiles from intent to controls using five lenses:
- Identity β user/service role (group, SPIFFE ID, certificate SAN).
- Device posture β EDR/UEM healthy, encryption on, OS β₯ min.
- Application β target service/API/port/protocol with L7 awareness.
- Data sensitivity β stricter controls for PCI/PHI/CUI; log & watermark on egress. β DLP
- Context β site/region/ASN, time window, ticket/change ID, session risk.
Decision outcomes: allow (least-privilege) β step-up (MFA/approval) β isolate (quarantine/read-only) β deny.
π§ Controls (Concrete & Enforceable)
- Allow-list by default β explicit intents only; no βany anyβ.
- Service Identity β mTLS between services; L7 policy (HTTP method, path, GraphQL schema). β Encryption β’ PKI
- Host Enforcement β per-process rules (linux eBPF, Windows Filtering Platform); block inter-tier except declared.
- Fabric Tags β SGT/labels mapped to ACLs across WAN/DC; carry identity through SD-WAN. β SD-WAN
- IoT/OT Isolation β profile β tag β minimal allow; deny east-west; mgmt only from jump hosts.
- Quarantine β NAC/SD-WAN reclassify on risk; ZTNA cuts user session; EDR isolates host. β NAC β’ ZTNA β’ EDR / MDR / XDR
βοΈ Cloud & Kubernetes Patterns
- Cloud VPC/VNet β security groups + NACLs compiled from labels (env:prod, tier:api, data:restricted).
- Kubernetes β NetworkPolicies + service mesh policies; SPIFFE/SVID identity; sidecar mTLS; deny pod-to-pod except intent.
- Hybrid β unify labels/IDs across DC and cloud; publish the same intents to multiple enforcement backends. β Cloud β’ Networks & Data Centers
π Visibility & Assurance
- Flow Discovery β learn current comms via NDR/flow; generate candidate intents from observed safe flows. β NDR
- Simulation / Dry-Run β evaluate proposed policies in observe-only; compare allowed/blocked deltas.
- Change as Code β policies in git; CI tests (reachability/unit tests) before push.
- Evidence β enforcement hits, denies, CoA/quarantine, and rule versions stream to SIEM; SOAR captures approvals & rollback.
π SLO Guardrails (Experience & Safety You Can Measure)
SLO / KPI | Target (Recommended) | Notes |
---|---|---|
Policy compile β push (p95) | β€ 60β120 s | From PR approve to enforcement live |
Simulation coverage | β₯ 95% of flows in dry-run | Before enforce |
False-deny rate (after enforce) | β€ 1β2% | Post-tuning target |
Containment (host quarantine) | β€ 2β5 min from alert | EDR/NAC/ZTNA action |
Evidence completeness | 100% policy versions & hits | Logs to SIEM/SOAR |
Platform availability | β₯ 99.95β99.99% | Controllers/agents |
SLO breaches trigger SOAR auto-rollback or relaxation of the impacted rules. β SIEM / SOAR
π οΈ Implementation Blueprint (No-Surprise Rollout)
- Inventory & Label β apps/services, tiers, environments, data classes; assign labels (env/tier/data/role).
- Baseline Flows β capture with NDR/NetFlow; map required comms; flag risky unknown flows. β NDR
- Write Intents β βrole X β service Y on port/protocol Zβ; βservice A β service B (L7 path/verb)β.
- Simulate β run in observe-only; reconcile denies; commit policy as code with approvals.
- Enforce (Rings) β canary services/sites β region rings β global; monitor SLOs; auto-rollback on regression.
- Edge & User β pair with ZTNA/SASE to keep users on app-only paths; deny subnet access. β ZTNA β’ SASE
- Operate & Tune β weekly review of denies/allow drift; retire legacy βany anyβ; publish diffs/RCAs.
π§ Reference Patterns (By Outcome)
A) PCI Cardholder Data Environment (CDE)
- Macro isolate CDE; micro-allow only appβDB; tokenization for PAN; ZTNA for admin consoles; logs to SIEM for PCI DSS 10. β DLP
B) PHI / Clinical Apps
- WebβappβDB only; break-glass paths with PAM approval + recording; immutable logs for HIPAA. β PAM
C) Dev/Test vs Prod
- Deny devβprod; allow CI/CD only via signer/proxy; mTLS service identity; short-lived certs. β PKI
D) IoT/OT Edge
- Function-based tags; mgmt-only ACLs; no east-west; NDR watch; NAC quarantine on anomaly. β NAC
π Compliance Mapping (Examples)
- PCI DSS β segmentation of CDE, least-privilege, access & log evidence.
- HIPAA β minimum-necessary network access, audit controls.
- ISO 27001 β A.13 network security; A.12 operations; A.16 incident mgmt.
- NIST 800-53/171 β AC/SC families (least privilege, boundary protection).
- CMMC β CUI enclave segmentation, auditing of allows/denies.
All enforcement events & changes stream to SIEM; SOAR automates rollback and containment.
π Where Microsegmentation Fits (Recursive View)
1) Grammar β flows traverse Connectivity & Networks & Data Centers.
2) Syntax β deployment patterns in Cloud & K8s drive enforcement choices.
3) Semantics β Cybersecurity preserves truth; microsegmentation proves least privilege.
4) Pragmatics β SolveForce AI predicts risky flows and suggests policy diffs.
5) Foundation β consistent terms via Primacy of Language.
6) Map β indexed across the SolveForce Codex & Knowledge Hub.
π Deploy Microsegmentation Thatβs Safe, Measurable & Auditable
- π (888) 765-8301
- βοΈ contact@solveforce.com
Related pages:
Cybersecurity β’ ZTNA β’ SASE β’ NAC β’ SD-WAN β’ NDR β’ EDR / MDR / XDR β’ SIEM / SOAR β’ Cloud β’ Networks & Data Centers β’ Knowledge Hub