srx-autovpn-full-tunnel

srx-autovpn-full-tunnel is a skill for Codex from fastrevmd-lab/fwskillsshare. It costs 99 tokens per session (7,559 once invoked), scanned A, original, MIT.

A design and troubleshooting guide for Juniper SRX AutoVPN full-tunnel backhaul, where branch traffic that is not local is sent through an encrypted connection to a central hub. The hub can inspect, filter, log, and route internet or branch-to-branch traffic.

In plain words
What is it for?
Use it for full-tunnel hub-and-spoke VPNs involving group-based gateways, shared tunnel interfaces, anti-loop routes, source NAT, VPN hairpinning, NAT-T, or related Junos configuration errors.
Why use it?
It explains the routing, traffic selectors, NAT, and security rules needed to centralize branch internet access without creating loops or broken VPN paths.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: names the AskUserQuestion tool; mentions Codex.

Good fit Use it for full-tunnel hub-and-spoke VPNs involving group-based gateways, shared tunnel interfaces, anti-loop routes, source NAT, VPN hairpinning, NAT-T, or related Junos configuration errors.

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Install with agentmods
npx agentmods add skills/fastrevmd-lab/fwskillsshare/srx-autovpn-full-tunnel
Install

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.

Any agent
npx skills add fastrevmd-lab/fwskillsshare --skill srx-autovpn-full-tunnel
Clone the repo
git clone --depth 1 https://github.com/fastrevmd-lab/fwskillsshare

Made for: Codex.

Wrote 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.

agentmods badge for srx-autovpn-full-tunnel

README.md
[![agentmods](https://agentmods.dev/badge/skills/fastrevmd-lab/fwskillsshare/srx-autovpn-full-tunnel/github.svg)](https://agentmods.dev/skills/fastrevmd-lab/fwskillsshare/srx-autovpn-full-tunnel)
Your own site
<a href="https://agentmods.dev/skills/fastrevmd-lab/fwskillsshare/srx-autovpn-full-tunnel"><img src="https://agentmods.dev/badge/skills/fastrevmd-lab/fwskillsshare/srx-autovpn-full-tunnel/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.

agentmods 80×15 button for srx-autovpn-full-tunnel

Your own site · 80×15
<a href="https://agentmods.dev/skills/fastrevmd-lab/fwskillsshare/srx-autovpn-full-tunnel"><img src="https://agentmods.dev/badge/skills/fastrevmd-lab/fwskillsshare/srx-autovpn-full-tunnel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,559 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00099 $0.07559
Opus 5 $0.00049 $0.03779
Sonnet 5 $0.00020 $0.01512
Haiku 4.5 $0.00010 $0.00756

Measured 12d ago against content hash b7c1b6b6e62f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

srx-autovpn-full-tunnel 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 12d 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.

skills/srx-autovpn-full-tunnel/SKILL.md · 472 lines

How it starts

The opening of the file, as written. The whole thing — 472 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SRX AutoVPN Full-Tunnel Backhaul

Overview

AutoVPN lets one hub gateway accept IPsec connections from any number of spokes with no per-spoke hub configuration. Full-tunnel backhaul is the design choice to send everything a spoke does not own locally up the tunnel to the hub, instead of the conventional split tunnel (only hub-LAN traffic in the tunnel, internet broken out locally, no spoke-to-spoke).

Core principle: if traffic is not local to a spoke, it goes to the hub. The hub then source-NATs internet-bound traffic out its WAN and hairpins spoke-to-spoke traffic back out the tunnel un-NAT'd. The motivation is centralized egress — all internet traffic can be inspected, filtered, and logged at one point (UTM/IDP on the hub).

The full-tunnel changes are confined to four things: the traffic selector scope, spoke routing, hub egress routing/NAT, and two added hub security policies. Everything else — IKE/IPsec parameters and the AutoVPN dynamic-gateway mechanics — is standard AutoVPN.

Attribution. The reference topology, full-tunnel backhaul approach, and the validated set-format configuration this skill summarizes come from Jason Anderson's lab srx-autovpn-backhaul-public (https://github.com/anderson-jason573/srx-autovpn-backhaul-public), built and validated on four vSRX (Junos OS 23.2R2.21) plus a Cisco IOS-XE WAN transit router. See references/source-design-summary.md.

Runtime intake

Before starting the workflow, inspect the request, supplied artifacts, and available approved read-only evidence. If unresolved facts could materially change safety, scope, correctness, confidence, or the requested output, read references/runtime-intake.md.

For each unresolved material fact whose catalog condition is true, invoke Claude AskUserQuestion or Codex request_user_input before continuing or issuing an open-ended request. Ask at most three single-select catalog questions per round. After each response, ask another round whenever any unresolved material catalog condition remains true; continue only when none remain. Do not repeat answered questions or show the full catalog. Without a native tool, present each selected catalog question with its 2-3 labeled choices and a free-text Other path in concise plain text; do not substitute a generic checklist.

Read the full file on GitHub · 472 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 12d ago First seen · 472 lines · 99 tokens per session scan A b7c1b6b6e62f

Subscribe to this mod's changes

srx-autovpn-full-tunnel is a skill published in the GitHub repository fastrevmd-lab/fwskillsshare (9 stars, last pushed today), licensed MIT. It adds 99 tokens to every session and 7,559 once invoked, about $0.0005 per session on Opus 5. 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 2026-08-31.

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