claude-red is a library of structured skills that give Claude specialized offensive-security methods for areas such as web vulnerabilities, shellcode, exploit development, and identity systems. It is intended for authorized red-team work, bug-bounty triage, security research, CTF preparation, and operator training. Its catalogue contains the project's skills for loading these security specializations into Claude.
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.
npx skills add SnailSploit/Claude-Red --skill offensive-lorawan-sub-ghzgit clone --depth 1 https://github.com/SnailSploit/Claude-RedWrote 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.
[](https://agentmods.dev/skills/snailsploit/claude-red/offensive-lorawan-sub-ghz)<a href="https://agentmods.dev/skills/snailsploit/claude-red/offensive-lorawan-sub-ghz"><img src="https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-lorawan-sub-ghz/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.
<a href="https://agentmods.dev/skills/snailsploit/claude-red/offensive-lorawan-sub-ghz"><img src="https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-lorawan-sub-ghz.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Privilege Escalation · line 151 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00163 | $0.01790 |
| Opus 5.5 | $0.00065 | $0.00716 |
| Sonnet 5.5 | $0.00033 | $0.00358 |
| Haiku 4.5 | $0.00016 | $0.00179 |
Grade A, and why
offensive-lorawan-sub-ghz 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- offensive-lorawan-sub-ghz — 88% identical, 40 lines differ
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LoRaWAN & Sub-GHz Attacks
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.
Quick Workflow
- Identify the band + modulation (LoRa CSS vs. simple OOK/FSK)
- Capture transmissions with appropriate hardware (HackRF / RTL-SDR / Flipper Zero)
- For LoRaWAN: capture join + uplinks; analyze key derivation
- For proprietary sub-GHz: demodulate, identify packet format, replay or craft
Hardware
| 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
LoRaWAN is a MAC layer over LoRa physical (chirp spread spectrum). Devices either:
- OTAA (Over-the-Air Activation) — derive session keys at join
- ABP (Activation By Personalization) — pre-flashed keys
OTAA Join Capture
# 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):
- Decrypt Join-Accept → recover NwkSKey, AppSKey
- Subsequent traffic decryption + injection
ABP — Pre-Flashed Keys
ABP devices have NwkSKey + AppSKey flashed at manufacture. Common flaws:
- Same key across thousands of devices (vendor laziness)
- No frame counter rollover protection → replay any historical uplink
- DevAddr predictability (sequential allocation)
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.
- 1mo ago First seen · 183 lines · 163 tokens per session scan A 566cd87eb0b6
offensive-lorawan-sub-ghz is a skill published in the GitHub repository SnailSploit/Claude-Red (9,628 stars, last pushed 15d ago), licensed MIT. It adds 163 tokens to every session and 1,790 once invoked, about $0.0007 per session on Opus 5.5. 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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