Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add HermeticOrmus/LibreSecOps-Claude-Code --skill microsegmentation-patternsgit clone --depth 1 https://github.com/HermeticOrmus/LibreSecOps-Claude-CodeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hermeticormus/libresecops-claude-code/microsegmentation-patterns)<a href="https://agentmods.dev/skills/hermeticormus/libresecops-claude-code/microsegmentation-patterns"><img src="https://agentmods.dev/badge/skills/hermeticormus/libresecops-claude-code/microsegmentation-patterns/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hermeticormus/libresecops-claude-code/microsegmentation-patterns"><img src="https://agentmods.dev/badge/skills/hermeticormus/libresecops-claude-code/microsegmentation-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.02595 |
| Opus 5.5 | $0.00000 | $0.01038 |
| Sonnet 5.5 | $0.00000 | $0.00519 |
| Haiku 4.5 | $0.00000 | $0.00260 |
Grade A, and why
microsegmentation-patterns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 360 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Microsegmentation Patterns
Implementation approaches for network, application, and identity-based microsegmentation across on-premises and cloud environments.
Knowledge Base
Segmentation Levels
Microsegmentation operates at multiple layers, each providing different granularity and capabilities:
Layer 3/4 (Network): IP addresses, ports, protocols. The most basic form. Implemented via firewalls, security groups, VLANs, and Kubernetes NetworkPolicy. Limitation: IP addresses are not stable identities in dynamic environments (containers, autoscaling).
Layer 7 (Application): HTTP methods, paths, headers, gRPC services. Implemented via service mesh (Istio, Linkerd), application-aware firewalls, and API gateways. Provides much finer control but requires deeper infrastructure integration.
Identity-based: Cryptographic workload identity (SPIFFE/SPIRE, mTLS certificates). Communication is authorized based on verified identity, not network location. The most robust form -- works across clusters, clouds, and hybrid environments.
Default Deny vs. Default Allow
Default deny (target state): All traffic is blocked unless explicitly allowed. This is the zero trust ideal. In practice, it requires a complete communication matrix before enforcement.
Default allow with logging (starting state): All traffic is allowed but logged. Use this phase to discover communication patterns, build the allowlist, and then transition to default deny.
The transition process:
- Deploy in logging/audit mode (default allow, log everything)
- Analyze traffic patterns for 2-4 weeks
- Build communication matrix from observed traffic
- Create explicit allow policies for legitimate traffic
- Switch to default deny with allow policies
- Monitor for breakage, adjust policies
- Iterate per segment/namespace/tier
Patterns
Pattern 1: Kubernetes NetworkPolicy (L3/L4)
# Default deny all ingress and egress in a namespace
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: default-deny-all
namespace: production
spec:
podSelector: {} # Applies to all pods in namespace
policyTypes:
- Ingress
- Egress
---
# Allow frontend to talk to backend API on port 8080
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: allow-frontend-to-backend
namespace: production
spec:
podSelector:
matchLabels:
app: backend-api
policyTypes:
- Ingress
ingress:
- from:
- podSelector:
matchLabels:
app: frontend
ports:
- protocol: TCP
port: 8080
---
# Allow backend API to reach database on port 5432
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: allow-backend-to-database
namespace: production
spec:
podSelector:
matchLabels:
app: database
policyTypes:
- Ingress
ingress:
- from:
- podSelector:
matchLabels:
app: backend-api
ports:
- protocol: TCP
port: 5432
---
# Allow all pods to reach DNS (required for service discovery)
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: allow-dns
namespace: production
spec:
podSelector: {}
policyTypes:
- Egress
egress:
- to:
- namespaceSelector: {}
podSelector:
matchLabels:
k8s-app: kube-dns
ports:
- protocol: UDP
port: 53
- protocol: TCP
port: 53
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 360 lines · 0 tokens per session scan A cd454dd5d572
microsegmentation-patterns is a skill published in the GitHub repository HermeticOrmus/LibreSecOps-Claude-Code (4 stars, last pushed 6d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,595 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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