external/anthropic-cybersecurity-skills/skills/conducting-wireless-network-penetration-test/SKILL.md
Conducts authorized wireless network penetration tests to assess the security of WiFi infrastructure by testing for weak encryption protocols, captive portal bypasses, evil twin attacks, WPA2/WPA3 handshake capture, rogue access point detection, and client-side attacks. The tester evaluates wireless authentication, network segmentation, and the effectiveness of wireless intrusion detection systems. Activates for requests involving wireless pentest, WiFi security assessment, WPA2/WPA3 testing, or rogue access point detection.
npx skillsauth add seikaikyo/dash-skills conducting-wireless-network-penetration-testInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Do not use against wireless networks without written authorization from the network owner, for jamming or denial-of-service attacks against wireless infrastructure unless explicitly authorized, or in environments where wireless disruption could affect life-safety systems.
Discover and map all wireless networks in the target environment:
airmon-ng start wlan0airodump-ng wlan0mon -w recon --output-format csv,pcap to discover all SSIDs, BSSIDs, channels, encryption types, and connected clientsairodump-ng wlan0mon --essid-regex ".*" -c <channel>For WPA2-PSK networks, capture the 4-way handshake and attempt offline cracking:
airodump-ng wlan0mon -c <channel> --bssid <bssid> -w captureaireplay-ng -0 5 -a <bssid> -c <client_mac> wlan0monaircrack-ng -w /usr/share/wordlists/rockyou.txt capture-01.caphashcat -m 22000 capture.hc22000 /usr/share/wordlists/rockyou.txthashcat -m 22000 capture.hc22000 wordlist.txt -r /usr/share/hashcat/rules/best64.rulehcxdumptool -i wlan0mon --enable_status=1 -o pmkid.pcapng --filtermode=2 --filterlist_ap=<bssid>For 802.1X/EAP networks, attempt credential capture through rogue RADIUS:
hostapd-mana with a rogue RADIUS serverasleap or convert to hashcat format: hashcat -m 5500 captured_ntlm.txt wordlist.txtDeploy a rogue access point to intercept client connections:
hostapd with the same SSID and channeldnsmasq for DHCP and DNS, and a web server presenting a fake login pageAfter gaining wireless network access, assess network segmentation:
nmap -sn <wireless_subnet>| Term | Definition | |------|------------| | Evil Twin | A rogue access point that mimics a legitimate SSID to trick clients into connecting, enabling man-in-the-middle attacks and credential capture | | 4-Way Handshake | The WPA2 authentication exchange between client and AP that establishes encryption keys; captured handshakes can be cracked offline | | WPA3-SAE | Simultaneous Authentication of Equals; WPA3's key exchange protocol that resists offline dictionary attacks and provides forward secrecy | | Transition Mode | WPA3 backward compatibility mode that supports both WPA2 and WPA3 clients, potentially vulnerable to downgrade attacks | | PMKID Attack | A clientless attack that captures the Pairwise Master Key Identifier from the AP's first EAPOL frame, allowing offline cracking without capturing a full handshake | | 802.1X/EAP | Enterprise wireless authentication using RADIUS and Extensible Authentication Protocol, providing per-user credentials instead of a shared pre-shared key | | Deauthentication Attack | Sending spoofed deauthentication frames to disconnect clients from an AP, forcing them to reconnect and enabling handshake capture or evil twin attacks |
Context: A financial services company has 3 SSIDs: CorpWiFi (WPA2-Enterprise for employees), GuestWiFi (captive portal), and IoT-Net (WPA2-PSK for printers and conferencing systems). The tester is authorized to test all three networks from the lobby and conference rooms.
Approach:
Pitfalls:
## Finding: Weak WPA2-PSK on IoT Network with Inadequate Segmentation
**ID**: WIFI-001
**Severity**: Critical (CVSS 9.4)
**Affected SSID**: IoT-Net (BSSID: AA:BB:CC:DD:EE:FF)
**Encryption**: WPA2-Personal (PSK)
**Description**:
The IoT wireless network uses a weak pre-shared key that was cracked in 3 minutes
using a standard dictionary attack. Once connected to IoT-Net, the tester discovered
that the wireless VLAN is not properly segmented from the internal corporate network,
providing unrestricted access to file servers, the Active Directory domain controller,
and the internal database server.
**Proof of Concept**:
1. Captured WPA2 handshake: airodump-ng wlan0mon -c 6 --bssid AA:BB:CC:DD:EE:FF -w iot
2. Cracked PSK in 3 minutes: aircrack-ng -w rockyou.txt iot-01.cap -> Key: Company2024!
3. Connected to IoT-Net and scanned: nmap -sn 10.20.0.0/24
4. Accessible from IoT-Net: DC01 (10.20.0.5:445), FILESVR (10.20.0.10:445), DBSVR (10.20.0.15:3306)
**Impact**:
An attacker within wireless range (tested from the public lobby) can join the IoT
network and gain direct network access to the corporate infrastructure, bypassing
the WPA2-Enterprise authentication required for employee access.
**Remediation**:
1. Implement a complex 20+ character PSK for IoT-Net, rotated quarterly
2. Deploy VLAN segmentation to isolate IoT-Net from the corporate network
3. Implement firewall rules allowing IoT devices to reach only their required services
4. Migrate IoT devices to 802.1X authentication with device certificates where supported
5. Deploy WIDS to detect deauthentication attacks and rogue access points
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.