| .. | ||
| README.md | ||
Wired Airwave 013
| Field | Value |
|---|---|
| Category | IoT |
| Difficulty | Medium |
| Points | 500 |
| Author | Eun0us |
| CTF | Espilon 2026 |
Description
Clinique Sainte-Mika uses a wireless maintenance channel for Room 013 monitors. The RF backend exposes raw baseband IQ over TCP.
Your objective:
- Decode the FSK bursts from the IQ stream.
- Recover the maintenance token hidden in service frames.
- Submit the token on the control console.
- IQ Stream:
tcp/<host>:9001 - Maintenance Console:
tcp/<host>:31337
Format: ESPILON{flag}
TL;DR
Capture the raw int8 IQ stream (interleaved I/Q). Implement differential FSK demodulation.
Locate frames using preamble + sync markers. XOR-deobfuscate with key WIREDMED13.
Verify CRC16-CCITT. Reassemble maintenance frame parts (P1:0BS3RV3 + P2:-L41N-868)
into token 0BS3RV3-L41N-868. Submit to the console.
Tools
| Tool | Purpose |
|---|---|
nc |
Capture IQ stream and connect to console |
| Python 3 + numpy | FSK demodulation and frame parsing |
| CRC16-CCITT library | Frame validation |
Solution
Step 1 — Capture the IQ stream
nc <host> 9001 > capture.raw
# Wait a few seconds, then Ctrl+C
The stream begins with a text banner:
IQ stream — int8 interleaved, samplerate=200000, encoding=2-FSK
After the banner, raw binary IQ data follows. Save after the newline.
📸
[screenshot: nc output showing the IQ stream banner before binary data]
Step 2 — Demodulate the 2-FSK signal
import numpy as np
with open("capture.raw", "rb") as f:
raw = np.frombuffer(f.read(), dtype=np.int8).astype(float)
# Reconstruct complex samples from interleaved I/Q
samples = raw[0::2] + 1j * raw[1::2]
# Differential FSK demodulation: sign of imag(s[n] * conj(s[n-1]))
diff = samples[1:] * np.conj(samples[:-1])
bits_raw = (np.imag(diff) > 0).astype(int)
# Symbol slicing at 40 samples per symbol
SAMPLES_PER_SYMBOL = 40
symbols = []
for i in range(0, len(bits_raw) - SAMPLES_PER_SYMBOL, SAMPLES_PER_SYMBOL):
chunk = bits_raw[i:i+SAMPLES_PER_SYMBOL]
symbols.append(int(np.mean(chunk) > 0.5))
Step 3 — Find and parse frames
Look for the preamble pattern (eight 1s then a sync marker).
Once found, read the 20-byte obfuscated payload.
📸
[screenshot: spectrogram of IQ data showing FSK burst patterns]
Step 4 — XOR-deobfuscate and verify CRC
import crcmod
crc16 = crcmod.predefined.mkCrcFun('crc-ccitt-false')
KEY = b"WIREDMED13"
for frame in detected_frames:
payload = bytes(frame[:20])
deobf = bytes(b ^ KEY[i % len(KEY)] for i, b in enumerate(payload))
frame_type = deobf[0]
counter = deobf[1]
data = deobf[2:18]
crc = (deobf[18] << 8) | deobf[19]
calculated = crc16(deobf[:18])
if calculated == crc:
print(f"type={frame_type:02x} data={data}")
Step 5 — Collect maintenance frame parts
Valid decoded maintenance frames produce:
type=0x10 data=P1:0BS3RV3
type=0x10 data=P2:-L41N-868
Telemetry frames (type=0x01) are noise for this challenge.
Token = 0BS3RV3-L41N-868
📸
[screenshot: decoded frame output showing the two token parts]
Step 6 — Submit to the console
nc <host> 31337
unlock 0BS3RV3-L41N-868
The server returns the flag.
📸
[screenshot: maintenance console returning the flag after unlock]
Flag
ESPILON{sdr_fsk_w1r3d_m3d_013}