What is attacking-wireless-networks?

A wireless-network security-testing guide for Wi-Fi discovery, WPA/WPA2/WPA3 password testing, WPS weaknesses, rogue access points, and forced client disconnections. An Evil Twin is a fake Wi-Fi network made to resemble a real one.

Use it for authorized Wi-Fi assessments, including network reconnaissance, captured-handshake analysis, WPS testing, rogue access-point checks, and wireless traffic inspection.

It helps find weak wireless passwords, unsafe setup choices, and ways users or devices could be tricked into joining an attacker-controlled network.

attacking-wireless-networks — Skill for Claude Code by trilwu

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 trilwu/secskills --skill attacking-wireless-networks

Clone the repo

git clone --depth 1 https://github.com/trilwu/secskills

Made for: Claude Code.

Or install secskills-offense, the plugin that ships this one along with the rest of its 40 skills.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/trilwu/secskills/attacking-wireless-networks/github.svg)](https://agentmods.dev/skills/trilwu/secskills/attacking-wireless-networks)

Your own site

<a href="https://agentmods.dev/skills/trilwu/secskills/attacking-wireless-networks"><img src="https://agentmods.dev/badge/skills/trilwu/secskills/attacking-wireless-networks/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/trilwu/secskills/attacking-wireless-networks"><img src="https://agentmods.dev/badge/skills/trilwu/secskills/attacking-wireless-networks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,689 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 warn 7 Sept 2026

SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

high YARA Match · line 124
YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).

Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
high Prompt Injection · line 392
Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.

Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00046	$0.02689
Opus 5	$0.00023	$0.01345
Sonnet 5	$0.00009	$0.00538
Haiku 4.5	$0.00005	$0.00269

Measured 5d ago against content hash 98aa6551c1de, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

attacking-wireless-networks 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 5d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

attacking-wireless-networks — 95% identical, 5 lines differ

secskills-offense/skills/attacking-wireless-networks/SKILL.md · 415 lines

How it starts

The opening of the file, as written. The whole thing — 415 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Attacking Wireless Networks

When to Use

WiFi penetration testing
Wireless network security assessment
WPA/WPA2/WPA3 cracking
Evil Twin and rogue AP attacks
Wireless reconnaissance

When NOT to Use

Wired network attacks — use enumerating-network-services
Cracking the captured handshake — use cracking-passwords
Bluetooth (Classic/BLE) or NFC — use attacking-bluetooth-nfc for GATT enumeration, card cloning, and RF sniffing; this skill is Wi-Fi only
Zigbee or general SDR work beyond Wi-Fi — outside this skill's scope
Post-access network exploitation — move to performing-reconnaissance once you are on the network

Setup and Tools

Enable Monitor Mode:

# Check wireless interface
iwconfig
iw dev

# Enable monitor mode
airmon-ng start wlan0
# Creates wlan0mon

# Or manually
ip link set wlan0 down
iw wlan0 set monitor none
ip link set wlan0 up

# Disable interfering processes
airmon-ng check kill

Essential Tools:

aircrack-ng suite
Wireshark
Kismet
Reaver/Bully (WPS)
Wifite (automated)
hcxtools/hcxdumptool
Fluxion (Evil Twin)

WiFi Reconnaissance

Network Discovery:

# Scan for networks
airodump-ng wlan0mon

# Scan specific channel
airodump-ng -c 6 wlan0mon

# Scan and save to file
airodump-ng -w capture wlan0mon

# Filter by BSSID
airodump-ng --bssid AA:BB:CC:DD:EE:FF -c 6 -w capture wlan0mon

Kismet:

# Start Kismet
kismet

# Command line
kismet_server
kismet_client

# View in web UI
http://localhost:2501

WPA/WPA2 Attacks

Capture Handshake

# Method 1: Wait for client connection
airodump-ng -c 6 --bssid AA:BB:CC:DD:EE:FF -w capture wlan0mon

# Method 2: Deauth clients to force reconnect
# In another terminal
aireplay-ng --deauth 10 -a AA:BB:CC:DD:EE:FF wlan0mon

# Or target specific client
aireplay-ng --deauth 10 -a AA:BB:CC:DD:EE:FF -c CLIENT:MAC wlan0mon

# Verify handshake captured
aircrack-ng capture-01.cap
# Look for "1 handshake"

Read the full file on GitHub · 415 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.

5d ago First seen · 415 lines · 46 tokens per session scan A 98aa6551c1de

Subscribe to this mod's changes

attacking-wireless-networks is a skill published in the GitHub repository trilwu/secskills (137 stars, last pushed 4d ago), licensed MIT. It adds 46 tokens to every session and 2,689 once invoked, about $0.0002 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 2026-09-03.

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