Existing defenses are slow to detect zero day exploits and capture attack traffic targeting inadequately secured Customer Premise Equipment (CPE) and Internet of Things (IoT) devices. This means that attackers have considerable periods of time to find and compromise vulnerable devices before the attack vectors are well understood and mitigation is in place.
About a month ago we presented honware at eCrime 2019, a new honeypot framework that enables the rapid construction of honeypots for a wide range of CPE and IoT devices. The framework automatically processes a standard firmware image (as is commonly provided for updates) and runs the system with a special pre-built Linux kernel without needing custom hardware. It then logs attacker traffic and records which of their actions led to a compromise.
We provide an extensive evaluation and show that our framework is scalable and significantly better than existing emulation strategies in emulating the devices’ firmware applications. We were able to successfully process close to 2000 firmware images across a dozen brands (TP-Link, Netgear, D-Link…) and run them as honeypots. Also, as we use the original firmware images, the honeypots are not susceptible to fingerprinting attacks based on protocol deviations or self-revealing properties.
By simplifying the process of deploying realistic honeypots at Internet scale, honware supports the detection of malware types that often go unnoticed by users and manufactures. We hope that honware will be used at Internet scale by manufacturers setting up honeypots for all of their products and firmware versions or by researchers looking for new types of malware.
The paper is available here.
2 thoughts on “Honware: A Virtual Honeypot Framework for Capturing CPE and IoT Zero Days”
Looks like a useful approach.
A question on the practicality of fingerprint such honeypot. I’ve found it reasonably straightforward to distinguish VM guests from physical hosts by looking at TCP timestamp accuracy: the reported timestamps are non-linear for VMs if they’re swapped out. Is that a detection mechanism that was assessed?
It’s really working.. Thanks a lot, I have to try sign in first. Later I will tell you the answer. See you soon