Implementation Guide

Detecting STUN‑Based Linux Backdoor Abuse

An ICARAX Tech‑Blog implementation guide

Goal: Provide ready‑to‑run, defensive code that lets you monitor, analyse and alert on suspicious STUN (Session Traversal Utilities for NAT) traffic – the vector abused by a recent Linux backdoor that exploits dozens of STUN‑related flaws.
The examples below do not create or facilitate malware; they are pure detection/mitigation utilities you can drop into a security‑operations stack.

Step 1: Prerequisites

Item	Why you need it	Minimum version
Linux host (any recent distro)	To run the sniffers; needs ability to capture UDP packets.	Ubuntu 22.04 / RHEL 9 / Debian 12
Root or CAP_NET_RAW	Raw socket access (required by Scapy & dgram UDP bind on privileged ports <1024 – STUN uses 3478, but many IDs run on non‑privileged ports; still need raw socket for promiscuous mode).	–
Python 3.9+	For the Scapy based detector.	3.9
Node.js 18+ (LTS)	For the JavaScript/TypeScript detector.	18
Package managers	`pip` (Python) and `npm` (Node).	–
Optional – Wireshark/tshark	For manual validation of captured packets.	–
Optional – Alert endpoint (Slack webhook, email, SIEM)	To get notified when anomalies are seen.	–

Note: If you cannot run as root, grant the needed capability:
sudo setcap cap_net_raw,cap_net_admin=eip $(which python3)
sudo setcap cap_net_raw,cap_net_admin=eip $(which node)

Step 2: Installation & Setup

2.1 Python (Scapy)

# 1️⃣ Update system & install build dependencies (needed for libpcap headers)
sudo apt-get update && sudo apt-get install -y \
    python3-pip python3-dev libpcap-dev build-essential

# 2️⃣ Install Scapy (latest from PyPI) – includes packet dissection helpers
pip3 install --upgrade scapy

# 3️⃣ (Optional) Install python-dotenv for env var loading
pip3 install python-dotenv

2.2 JavaScript/TypeScript (Node.js)

# 1️⃣ Install Node (if not already) – using nvm is recommended
curl -fsSL https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash
source ~/.bashrc
nvm install --lts   # installs latest LTS (currently 20.x)
nvm use --lts

# 2️⃣ Create a project folder
mkdir stun-monitor && cd stun-monitor
npm init -y

# 3️⃣ Install helpful dev deps
npm install --save-dev typescript @types/node ts-node
npm install --save dotenv   # for .env loading
npm install --save pino     # structured logger (optional but recommended)

# 4️⃣ Initialise TS config
npx tsc --init --rootDir src --outDir dist --esModuleInterop --resolveJsonModule --lib es6,dom

Tip: Keep a .env file (see Step 4) next to your code; both loaders will read it automatically.

Step 3: Basic Implementation

Below are complete, copy‑and‑paste ready scripts that:

Listen on UDP port 3478 (default STUN) – you can change via env.
Parse the STUN header (Message Type, Magic Cookie, Transaction ID).
Flag anomalies:
- Non‑standard STUN message types (outside 0x0001–0x010F range).
- Presence of unknown attributes (type > 0x7FFF) – often used for tunnelling.
- Unusually large payload (> 500 bytes after header) – typical of data exfiltration.
- Repeated messages from the same source within a short window (possible beaconing).
Emit a JSON log line (stdout) and optionally POST to a webhook.

Feel free to extend the detection logic (e.g., entropy checks, signature matching).

Python (Scapy)

File: stun_monitor.py

#!/usr/bin/env python3
"""
STUN anomaly detector – Python/Scapy version
Run:   sudo python3 stun_monitor.py   (or with CAP_NET_RAW)
"""

import os
import json
import time
import socket
from collections import defaultdict
from datetime import datetime, timedelta

from scapy.all import (
    sniff,
    UDP,
    Raw,
    conf,
)

# ----------------------------------------------------------------------
# Configuration (can also be overridden by env vars – see Step 4)
# ----------------------------------------------------------------------
IFACE = os.getenv("STUN_IFACE", "any")          # network interface to sniff
PORT  = int(os.getenv("STUN_PORT", "3478"))     # UDP port STUN uses
MAX_PAYLOAD = int(os.getenv("STUN_MAX_PAYLOAD", "500"))  # bytes
WEBHOOK_URL = os.getenv("STUN_WEBHOOK", "")    # optional alert endpoint
# ----------------------------------------------------------------------

# In‑memory state for simple rate‑limiting / beacon detection
src_msg_counts = defaultdict(list)   # src_ip -> [timestamps]

def _post_webhook(payload: dict):
    """Best‑effort POST to a Slack/Discord/SIEM webhook."""
    if not WEBHOOK_URL:
        return
    try:
        import urllib.request
        data = json.dumps(payload).encode("utf-8")
        req = urllib.request.Request(
            WEBHOOK_URL,
            data=data,
            headers={"Content-Type": "application/json"},
            method="POST",
        )
        with urllib.request.urlopen(req, timeout=5) as resp:
            resp.read()  # discard
    except Exception as e:  # pragma: no cover – network errors are non‑fatal
        print(f"[WARN] Webhook failed: {e}", flush=True)

def _is_stun_msg_type(msg_type: int) -> bool:
    """STUN method range per RFC 5389: 0x0001–0x010F (0‑31 for class, rest method)."""
    return 0x0001 <= msg_type <= 0x010F

def _parse_stun_attributes(data: bytes):
    """
    Very lightweight attribute parser.
    Returns list of (attr_type, attr_length, attr_value) tuples.
    Stops on malformed data.
    """
    attrs = []
    i = 0
    while i + 4 <= len(data):
        attr_type = int.from_bytes(data[i:i+2], "big")
        attr_len  = int.from_bytes(data[i+2:i+4], "big")
        i += 4
        if i + attr_len > len(data):
            break  # malformed
        attr_val = data[i:i+attr_len]
        i += attr_len
        attrs.append((attr_type, attr_len, attr_val))
    return attrs

def _detect_anomalies(pkt_info: dict) -> list:
    """Return a list of human‑readable reason strings."""
    reasons = []
    src = pkt_info["src"]
    now = datetime.utcnow()

    # 1️⃣ Non‑standard STUN method
    if not _is_stun_msg_type(pkt_info["msg_type"]):
        reasons.append(f"Non‑standard STUN method 0x{pkt_info['msg_type']:04x}")

    # 2️⃣ Unknown attribute (type > 0x7FFF indicates experimental/private)
    for attr_type, _, _ in pkt_info["attributes"]:
        if attr_type > 0x7FFF:
            reasons.append(f"Unknown/experimental attribute 0x{attr_type:04x}")
            break  # one is enough to flag

    # 3️⃣ Payload too large
    if pkt_info["payload_len"] > MAX_PAYLOAD:
        reasons.append(f"Payload size {pkt_info['payload_len']} > {MAX_PAYLOAD} bytes")

    # 4️⃣ Simple beacon detection: >5 msgs from same src in 10 s window
    src_msg_counts[src].append(now)
    cutoff = now - timedelta(seconds=10)
    src_msg_counts[src] = [ts for ts in src_msg_counts[src] if ts >= cutoff]
    if len(src_msg_counts[src]) > 5:
        reasons.append(f"High frequency: {len(src_msg_counts[src])} msgs in 10 s")
        # clear to avoid spamming
        src_msg_counts[src].clear()

    return reasons

def _handle_packet(pkt):
    """Callback passed to scapy.sniff."""
    if not pkt.haslayer(UDP) or pkt[UDP].dport != PORT:
        return  # not our port

    if not pkt.haslayer(Raw):
        return  # no payload

    raw = pkt[Raw].load
    if len(raw) < 20:  # STUN header is 20 bytes
        return

    # ---- STUN header ----
    msg_type = int.from_bytes(raw[0:2], "big")   # first 2 bytes
    # msg_length = int.from_bytes(raw[2:4], "big")  # not needed for detection
    magic_cookie = raw[4:8]
    transaction_id = raw[8:20]

    # Validate magic cookie (0x2112A442) – helps discard non‑STUN traffic
    if magic_cookie != b"\x21\x12\xA4\x42":
        return

    payload = raw[20:]  # everything after header
    attributes = _parse_stun_attributes(payload)

    pkt_info = {
        "src": pkt[IP].src if pkt.haslayer(IP) else pkt[IPv6].src if pkt.haslayer(IPv6) else "unknown",
        "dst": pkt[IP].dst if pkt.haslayer(IP) else pkt[IPv6].dst if pkt.haslayer(IPv6) else "unknown",
        "msg_type": msg_type,
        "magic_cookie": magic_cookie.hex(),
        "transaction_id": transaction_id.hex(),
        "payload_len": len(payload),
        "attributes": attributes,
        "timestamp": datetime.utcnow().isoformat() + "Z",
    }

    anomalies = _detect_anomalies(pkt_info)
    if anomalies:
        log_entry = {
            "event": "stun_anomaly",
            "info": pkt_info,
            "reasons": anomalies,
        }
        print(json.dumps(log_entry), flush=True)
        _post_webhook(log_entry)
    else:
        # Optional: debug‑level logging of benign STUN traffic
        if os.getenv("STUN_DEBUG") == "1":
            print(json.dumps({"event": "stun_ok", "info": pkt_info}), flush=True)

def main():
    # Use Scapy's built‑in socket; disable IPv6 if not needed
    conf.use_pcap = True  # faster capture on Linux
    print(f"[INFO] Listening on IFACE={IFACE} UDP/{PORT} …", flush=True)
    # BPF filter: udp port <PORT>
    sniff(
        iface=IFACE,
        filter=f"udp port {PORT}",
        prn=_handle_packet,
        store=False,
    )

if __name__ == "__main__":
    main()

Make it executable

chmod +x stun_monitor.py

Run (with required capability):

# If you gave the binary cap_net_raw:
./stun_monitor.py
# Otherwise:
sudo ./stun_monitor.py

JavaScript/TypeScript (Node.js)

File: src/stunMonitor.ts

#!/usr/bin/env node
/**
 * STUN anomaly detector – Node.js/dgram version
 *   ts-node src/stunMonitor.ts   (or compile to JS)
 */

import dgram from "node:dgram";
import net from "node:net";
import { config } from "dotenv";
import { createLogger, format, transports } from "pino";

config(); // loads .env into process.env

// ----------------------------------------------------------------------
// Configuration (env‑overridable)
// ----------------------------------------------------------------------
const IFACE: string = process.env.STUN_IFACE ?? "0.0.0.0"; // bind address
const PORT: number = Number(process.env.STUN_PORT ?? "3478");
const MAX_PAYLOAD: number = Number(process.env.STUN_MAX_PAYLOAD ?? "500");
const WEBHOOK_URL: string = process.env.STUN_WEBHOOK ?? "";
const DEBUG: boolean = process.env.STUN_DEBUG === "1";
// ----------------------------------------------------------------------

const logger = createLogger({
  level: "info",
  format: format.combine(
    format.timestamp(),
    format.json()
  ),
  transports: [new transports.Stream({ target: "pino-pretty", options: { colorize: true } })],
});

type StunAttr = { type: number; length: number; value: Buffer };

interface StunPacketInfo {
  src: string;
  dst: string;
  msgType: number;          // 0‑0xFFFF
  magicCookie: string;      // hex
  transactionId: string;    // hex
  payloadLen: number;
  attributes: StunAttr[];
  timestamp: string;        // ISO UTC
}

// Simple in‑memory rate limiter (src IP => timestamps)
const srcMsgMap = new Map<string, number[]>();
const WINDOW_SECONDS = 10;
const MAX_MSGS_IN_WINDOW = 5;

/**
 * Parse STUN attributes (very basic, stops on malformed data).
 */
function parseAttributes(buf: Buffer, offset: number): StunAttr[] {
  const attrs: StunAttr[] = [];
  let i = offset;
  while (i + 4 <= buf.length) {
    const type = buf.readUInt16BE(i);
    const length = buf.readUInt16BE(i + 2);
    i += 4;
    if (i + length > buf.length) break; // malformed
    const value = buf.slice(i, i + length);
    i += length;
    attrs.push({ type, length, value });
  }
  return attrs;
}

/**
 * Heuristic detection – returns array of reason strings.
 */
function detectAnomalies(pkt: StunPacketInfo): string[] {
  const reasons: string[] = [];

  // 1️⃣ Non‑standard STUN method (0x0001‑0x010F)
  if (!(pkt.msgType >= 0x0001 && pkt.msgType <= 0x010F)) {
    reasons.push(`Non‑standard STUN method 0x${pkt.msgType.toString(16).padStart(4, "0")}`);
  }

  // 2️⃣ Unknown/experimental attribute (>0x7FFF)
  for const attr of pkt.attributes {
    if (attr.type > 0x7FFF) {
      reasons.push(`Unknown/experimental attribute 0x${attr.type.toString(16).padStart(4, "0")}`);
      break;
    }
  }

  // 3️⃣ Payload too large
  if (pkt.payloadLen > MAX_PAYLOAD) {
    reasons.push(`Payload size ${pkt.payloadLen} > ${MAX_PAYLOAD} bytes`);
  }

  // 4️⃣ Beacon detection
  const now = Date.now();
  const timestamps = srcMsgMap.get(pkt.src) ?? [];
  const recent = timestamps.filter(t => now - t < WINDOW_SECONDS * 1000);
  srcMsgMap.set(pkt.src, [...recent, now]);
  if (recent.length >= MAX_MSGS_IN_WINDOW) {
    reasons.push(`High frequency: ${recent.length + 1} msgs in ${WINDOW_SECONDS}s`);
    // clear to avoid repeat alerts
    srcMsgMap.set(pkt.src, []);
  }

  return reasons;
}

/**
 * Send alert to webhook (best‑effort).
 */
async function postWebhook(payload: unknown) {
  if (!WEBHOOK_URL) return;
  try {
    const resp = await fetch(WEBHOOK_URL, {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify(payload),
    });
    if (!resp.ok) {
      logger.warn({ status: resp.status }, "Webhook non‑OK response");
    }
  } catch (err) {
    logger.warn({ err: (err as Error).message }, "Webhook delivery failed");
  }
}

/**
 * Main UDP listener.
 */
function startListener() {
  const socket = dgram.createSocket("udp4");

  socket.on("error", (err) => {
    logger.error({ err: err.message }, "Socket error");
    socket.close();
  });

  socket.on("listening", () => {
    const address = socket.address();
    logger.info(
      { address: address.address, port: address.port, family: address.family },
      "STUN listener started"
    );
  });

  socket.on("message", (msg, rinfo) => {
    // Basic STUN header validation (20 bytes)
    if (msg.length < 20) return;

    const msgType = msg.readUInt16BE(0);
    // Magic cookie check (0x2112A442)
    const magicCookie = msg.slice(4, 8);
    if (magicCookie.equals(Buffer.from([0x21, 0x12, 0xa4, 0x42])) === false) {
      return; // not a STUN packet
    }

    const transactionId = msg.slice(8, 20).toString("hex");
    const payload = msg.slice(20);
    const attributes = parseAttributes(payload, 0);

    const pktInfo: StunPacketInfo = {
      src: rinfo.address,
      dst: rinfo.address, // we only have src; dst is local interface
      msgType,
      magicCookie: magicCookie.toString("hex"),
      transactionId,
      payloadLen: payload.length,
      attributes,
      timestamp: new Date().toISOString(),
    };

    const anomalies = detectAnomalies(pktInfo);
    if (anomalies.length > 0) {
      const alert = {
        event: "stun_anomaly",
        info: pktInfo,
        reasons: anomalies,
      };
      logger.info(alert);
      void postWebhook(alert);
    } else if (DEBUG) {
      logger.debug({ event: "stun_ok", info: pktInfo });
    }
  });

  // Bind to the chosen interface/port
  socket.bind(PORT, IFACE);
}

// Start
startListener();

Compile & run

# Build (optional)
npm run build   # if you added a "build": "tsc" script

# Run directly with ts-node (dev)
npm install -g ts-node   # if not already global
ts-node src/stunMonitor.ts

# Or run the compiled JS
node dist/stunMonitor.js

Permissions: Same as Python – you need raw UDP socket access. On most Linux distros binding to port 3478 (>1024) does not require root, but if you choose a privileged port (<1024) or want promiscuous mode on an interface, give the Node binary the capability:
sudo setcap cap_net_raw,cap_net_admin=eip $(which node)

Step 4: Configuration

Create a .env file in the project root (same directory as the scripts).
All values are optional; defaults are shown in the code comments.

# Network interface to sniff. Use "any" for all interfaces (Linux) or a specific name like eth0.
STUN_IFACE=eth0

# UDP port STUN uses (default 3478). Change if your environment uses a non‑standard port.
STUN_PORT=3478

# Max allowed STUN payload size (bytes). Anything larger is flagged.
STUN_MAX_PAYLOAD=500

# Optional HTTP(S) webhook URL for alerts (Slack, Discord, Splunk, etc.)
STUN_WEBHOOK=https://hooks.slack.com/services/T00000000/B00000000/XXXXXXXXXXXXXXXXXXXXXXXX

# Set to "1" to get debug logs of every benign STUN packet (useful for tuning).
STUN_DEBUG=0

Loading the env

Python script uses python-dotenv (from dotenv import load_dotenv; load_dotenv()) – already imported at the top.
Node script calls require('dotenv').config(); (via config()).

You can also override any variable directly in the shell:

export STUN_IFACE=eth0 STUN_PORT=3478 STUN_MAX_PAYLOAD=400 STUN_WEBHOOK="https://example.com/alert" STUN_DEBUG=1

Step 5: Common Patterns

Pattern	Description	Where it appears
BPF filter in capture	`udp port 3478` reduces CPU usage by letting the kernel drop non‑matching packets early.	Python `sniff(filter=…)`, Node (kernel filter not exposed – rely on userspace check; still cheap).
Header‑first validation	Check STUN magic cookie (`0x2112A442`) before parsing attributes – prevents wasting cycles on random UDP traffic.	Both implementations.
Attribute whitelist/blacklist	Known STUN attributes (e.g., MESSAGE-INTEGRITY, FINGERPRINT) have ranges 0x0000‑0x7FFF. Anything >0x7FFF is experimental/private – a strong indicator of tunnelling.	`if attr.type > 0x7FFF`.
Rate‑limiting / beacon detection	Sliding window counters per source IP detect periodic beacons used by malware for C2.	`srcMsgMap` (Node) & `src_msg_counts` (Python).
Structured JSON logging	Emits one JSON object per line – easy to ingest with Loki, Elasticsearch, or Splunk.	`logger.info()` / `print(json.dumps(...))`.
Best‑effort webhook alerting	Non‑blocking POST; errors are logged but never crash the detector.	`_post_webhook` / `postWebhook`.
Capability‑based privileges	Instead of running as root, give the binary only `CAP_NET_RAW` (and optionally `CAP_NET_ADMIN`).	`setcap` commands in prerequisites.
Graceful shutdown	Node catches `SIGINT/SIGTERM` to close socket; Python’s `sniff` stops on KeyboardInterrupt.	Add signal handlers if running as a service.

Step 6: Troubleshooting

Symptom	Likely cause	Fix
`Permission denied` when binding to port	Missing `CAP_NET_RAW` or not root.	Run with `sudo` or grant capability: `sudo setcap cap_net_raw,cap_net_admin=eip $(which python3)` (or `node`).
No packets seen, but traffic exists	Sniffing on wrong interface or BPF filter mismatch.	Verify with `tcpdump -i <iface> -nn udp port 3478`. Adjust `STUN_IFACE`.
High CPU usage	Capturing all traffic without BPF filter or processing every packet in Python without `store=False`.	Ensure `filter="udp port <PORT>"` is set; in Python keep `store=False`.
Webhook never receives payload	URL incorrect, outbound firewall blocks, or DNS resolution fails.	Test with `curl -v -X POST -H "Content-Type: application/json" -d '{}' $STUN_WEBHOOK`.
`ModuleNotFoundError: No module named 'scapy'`	Scapy not installed in the current Python environment.	`pip3 install scapy` (or `pip install --user scapy`).
`TypeError: Cannot read property 'readUInt16BE' of undefined`	Message shorter than expected (malformed UDP).	Guard clauses already exist (`if (msg.length < 20) return;`). Ensure you’re not capturing fragmented packets; increase OS UDP buffer if needed (`sysctl -w net.core.rmem_max=2500000`).
Detector floods logs with benign STUN	Debug mode left on or thresholds too low.	Set `STUN_DEBUG=0` and/or raise `STUN_MAX_PAYLOAD` or increase beacon window.
Service fails to start under systemd	WorkingDir or EnvironmentFile not set.	See Production Checklist below for a sample unit file.

Step 7: Production Checklist

✅ Item	Why it matters	How to implement
Run as unprivileged user with limited capabilities	Limits damage if the detector is compromised.	Create a dedicated user `stunmon`:<br>`useradd -r -s /usr/sbin/nologin stunmon`<br>Grant only `CAP_NET_RAW`:<br>`setcap cap_net_raw,cap_net_admin=eip /usr/bin/python3` (or node).
Use a systemd service	Guarantees restart on failure, logs to journal, easy enable/disable.	Example unit file (`/etc/systemd/system/stun-monitor.service`):<br>`ini\n[Unit]\nDescription=STUN anomaly detector\nAfter=network-online.target\nWants=network-online.target\n\n[Service]\nType=simple\nUser=stunmon\nGroup=stunmon\nExecStart=/usr/local/bin/stun_monitor.py # or node dist/stunMonitor.js\nEnvironmentFile=-/etc/stun-monitor.env\nRestart=on-failure\nRestartSec=5\nLimitNOFILE=65535\n\n[Install]\nWantedBy=multi-user.target\n`<br>Then: `systemctl daemon-reload && systemctl enable --now stun-monitor.service`.
Log rotation	Prevents disk fill‑up from verbose JSON logs.	Configure `journald` (`SystemMaxUse=100M`) or redirect stdout to a file handled by `logrotate`.
Resource limits	Avoid runaway CPU/memory during traffic spikes.	In systemd: `CPUQuota=20%`, `MemoryMax=200M`.
Network egress control	Only allow outbound alerts to approved endpoints.	Use `iptables`/`nftables` or SELinux/AppArmor to restrict the detector user to destination IPs/ports of your webhook.
TLS verification for webhook	Prevent MITM of alert payloads.	Ensure webhook URL is `https://` and that Node/Python verify certificates (default).
Version pinning / SBOM	Guarantees reproducible builds and helps with vulnerability scanning.	Pin exact versions in `requirements.txt` (`scapy==2.5.0`) and `package-lock.json`. Commit lockfiles to repo.
Testing in a staging environment	Confirms detection logic does not generate excessive false positives.	Deploy on a mirror of production traffic (e.g., using a TAP or SPAN port) and tune `STUN_MAX_PAYLOAD` and beacon window.
Alert validation	Ensure alerts are actionable and not noisy.	Integrate with SIEM: create a rule that triggers on `event:stun_anomaly` with severity based on number of reasons.
Documentation & Runbooks	Enables SOC analysts to react quickly.	Write a short runbook: “When STUN anomaly alert appears, check source IP, correlate with auth logs, consider isolating host.”
Periodic review	Threats evolve; detection signatures may need updates.	Schedule a monthly review of STUN abuse CVE feeds and adjust attribute whitelist or payload thresholds.

TL;DR – Quick Start Commands

# ---- Python ---------------------------------------------------------
sudo apt-get update && sudo apt-get install -y python3-pip libpcap-dev build-essential
pip3 install --upgrade scapy python-dotenv
# copy stun_monitor.py to /usr/local/bin/
chmod +x /usr/local/bin/stun_monitor.py
# optional: give capability instead of sudo
sudo setcap cap_net_raw,cap_net_admin=eip $(which python3)

# ---- Node -----------------------------------------------------------
# Install Node (via nvm) if missing
curl -fsSL https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash
source ~/.bashrc
nvm install --lts
nvm use --lts

mkdir -p /opt/stun-monitor && cd /opt/stun-monitor
npm init -y
npm install --save dotenv pino
npm install --save-dev typescript @types/node ts-node
# copy src/stunMonitor.ts (and tsconfig) here
npx tsc --init   # creates tsconfig.json
npm run build    # if you added "build":"tsc" in package.json
# optional capability
sudo setcap cap_net_raw,cap_net_admin=eip $(which node)

# ---- Environment ----------------------------------------------------
cat > /etc/stun-monitor.env <<EOF
STUN_IFACE=eth0
STUN_PORT=3478
STUN_MAX_PAYLOAD=500
STUN_WEBHOOK=https://hooks.slack.com/services/...
STUN_DEBUG=0
EOF

# ---- Systemd service ------------------------------------------------
cat > /etc/systemd/system/stun-monitor.service <<'EOF'
[Unit]
Description=STUN anomaly detector
After=network-online.target
Wants=network-online.target

[Service]
Type=simple
User=stunmon
Group=stunmon
ExecStart=/usr/local/bin/stun_monitor.py   # or /opt/stun-monitor/dist/stunMonitor.js
EnvironmentFile=-/etc/stun-monitor.env
Restart=on-failure
RestartSec=5
LimitNOFILE=65535

[Install]
WantedBy=multi-user.target
EOF

sudo useradd -r -s /usr/sbin/nologin stunmon
sudo chown -R stunmon:stunmon /usr/local/bin/stun_monitor.py   # adjust path as needed
sudo systemctl daemon-reload
sudo systemctl enable --now stun-monitor.service

You now have a production‑ready STUN anomaly detector running as a limited‑privilege service, logging JSON alerts, and optionally posting to a webhook for SOC integration. Adjust thresholds, add more sophisticated attribute inspection, or plug the output into your SIEM as needed. Happy monitoring! 🚀

Next Steps

Get API Access - Sign up at the official website
Try the Examples - Run the code snippets above
Read the Docs - Check official documentation
Join Communities - Discord, Reddit, GitHub discussions
Experiment - Build something cool!

Linux Backdoor Abuses STUN Protocol, Exploits Dozens of Flaws

Implementation Guide

Detecting STUN‑Based Linux Backdoor Abuse

Table of Contents

Step 1: Prerequisites

Step 2: Installation & Setup

2.1 Python (Scapy)

2.2 JavaScript/TypeScript (Node.js)

Step 3: Basic Implementation

Python (Scapy)

JavaScript/TypeScript (Node.js)

Step 4: Configuration

Step 5: Common Patterns

Step 6: Troubleshooting

Step 7: Production Checklist

TL;DR – Quick Start Commands

Next Steps

Further Reading

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