network-appliance-offensive

network-appliance-offensive is a skill for Claude Code from transilienceai/communitytools. It costs 139 tokens per session (1,457 once invoked), scanned A, original, MIT.

A set of methods for safely examining perimeter network appliances and VPN encryption settings. It covers devices such as firewalls and VPN gateways, and observes or decodes their network behavior without exploiting them.

In plain words
What is it for?
Use it to inspect IKE and IPsec VPN settings, identify Check Point services, infer device versions, decode NTLM handshake details, and probe supported TLS versions.
Why use it?
It avoids rebuilding specialist network probes for every assessment and helps distinguish confirmed conditions from cases where the available evidence is insufficient. It also checks the conditions needed before associating a device with a known vulnerability.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the communitytools plugin — 48 skills, 5 commands, 9 agents, 1 hook shipped together

Good fit Use it to inspect IKE and IPsec VPN settings, identify Check Point services, infer device versions, decode NTLM handshake details, and probe supported TLS versions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/transilienceai/communitytools/network-appliance-offensive
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 transilienceai/communitytools --skill network-appliance-offensive
Clone the repo
git clone --depth 1 https://github.com/transilienceai/communitytools

Made for: Claude Code.

Or install communitytools, the plugin that ships this one along with the rest of its 48 skills, 5 commands, 9 agents, 1 hook.

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 network-appliance-offensive

README.md
[![agentmods](https://agentmods.dev/badge/skills/transilienceai/communitytools/network-appliance-offensive/github.svg)](https://agentmods.dev/skills/transilienceai/communitytools/network-appliance-offensive)
Your own site
<a href="https://agentmods.dev/skills/transilienceai/communitytools/network-appliance-offensive"><img src="https://agentmods.dev/badge/skills/transilienceai/communitytools/network-appliance-offensive/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 network-appliance-offensive

Your own site · 80×15
<a href="https://agentmods.dev/skills/transilienceai/communitytools/network-appliance-offensive"><img src="https://agentmods.dev/badge/skills/transilienceai/communitytools/network-appliance-offensive.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 139 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,457 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 $0.00139 $0.01457
Opus 5 $0.00069 $0.00728
Sonnet 5 $0.00028 $0.00291
Haiku 4.5 $0.00014 $0.00146

Measured 10d ago against content hash 9237b33a1def, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

network-appliance-offensive 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 10d 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/network-appliance-offensive/SKILL.md · 41 lines

How it starts

The opening of the file, as written. The whole thing — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Network-Appliance Offensive

firewall-review audits a config statically; infrastructure covers generic ports/DNS/SMB. Neither tests a live perimeter appliance or its VPN crypto — so IKE builders, SIC/OPSEC fingerprinting, and TTL discriminators were reinvented from raw sockets each engagement, often shallowly, and CVE applicability was left UNDETERMINED across whole estates. This skill provides the deterministic, tested tools and the precondition-gated methodology. Non-destructive only — every tool observes/decodes/infers; none fires an exploit, and CVE applicability is a precondition check, never a blind "vulnerable."

Tools

Tool Does Anti-footgun
tools/ike_enum.py IKEv1 aggressive-mode detection, IKEv1/IKEv2 transform + DH-group enum, NOTIFY / NAT-T decode (wraps ike-scan, raw ISAKMP SA_INIT builder fallback) Aggressive-mode support (PSK-hash leak) is the finding; enumerate, don't crack in-band
tools/checkpoint_sic_opsec.py Fingerprint SIC (18190/1), OPSEC LEA/ELA (18183/4), CA (18192/18210), FW1 (256/264), Gaia Portal; emit a CVE-precondition map incl. CVE-2024-24919 CVE-2024-24919 is applicable ONLY when the RA/Mobile-Access marker is observed — else undetermined
tools/appliance_version_infer.py Safe firmware/patch-level inference for FortiGate / PAN-OS / Cisco ASA / Citrix from headers, login markers, cert CN/serial → CVE applicability Never asserts applicable on a low-confidence / unknown version — returns undetermined
tools/tls_handshake_probe.py Which TLS versions are supported, by completed handshake per pinned protocol Fixes the openssl s_client exit/SECLEVEL false-positive — an aborted handshake ≠ support
tools/ntlm_decode.py Decode an NTLM Type-2 (CHALLENGE) AV_PAIR block → NetBIOS/DNS host, domain, forest, OS build Info-leak finding from an unauthenticated challenge; no auth attempted
tools/perimeter_forensics.py RST-TTL forgery discriminator (real host vs firewall forging a RST) + IKE NOTIFY decode Never asserts "internal host behind FW" on RSTs alone — a firewall forges RSTs indistinguishably at this layer; returns undetermined without an open-service TTL baseline

Read the full file on GitHub · 41 lines

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. 10d ago First seen · 41 lines · 139 tokens per session scan A 9237b33a1def

Subscribe to this mod's changes

network-appliance-offensive is a skill published in the GitHub repository transilienceai/communitytools (520 stars, last pushed 1mo ago), licensed MIT. It adds 139 tokens to every session and 1,457 once invoked, about $0.0007 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 2026-08-30.