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In this paper we provide an implementation, evaluation, and analysis of PowerHammer, a malware (bridgeware [1]) that uses power lines to exfiltrate data from air-gapped computers. In this case, a malicious code running on a compromised computer can control the power consumption of the system by intentionally regulating the CPU utilization. Data is modulated, encoded, and transmitted on top of the current flow fluctuations, and then it is conducted and propagated through the power lines. This phenomena is known as a 'conducted emission'. We present two versions of the attack. Line level powerhammering: In this attack, the attacker taps the in-home power lines 1 that are directly attached to the electrical outlet. Phase level power-hammering: In this attack, the attacker taps the power lines at the phase level, in the main electrical service panel. In both versions of the attack, the attacker measures the emission conducted and then decodes the exfiltrated data. We describe the adversarial attack model and present modulations and encoding schemes along with a transmission protocol. We evaluate the covert channel in different scenarios and discuss signal-to-noise (SNR), signal processing, and forms of interference. We also present a set of defensive countermeasures. Our results show that binary data can be covertly exfiltrated from air-gapped computers through the power lines at bit rates of 1000 bit/sec for the line level power-hammering attack and 10 bit/sec for the phase level power-hammering attack. Power stationStep up transformerStep down transformerStep down transformer Residential building 22kV output 400 kV 132 kV 11 kV Fig. 1: A (simplified) schematic diagram of the electricity network C. Exfiltration through Power LinesIn this paper, we present a new type of electric (current flow) covert channel. The method, dubbed PowerHammer, enables attackers to exfiltrate information from air-gapped networks through AC power lines. We show that a malware running on a computer can regulate the power consumption of the system by controlling the workload of the CPU. Binary data can be modulated on the changes of the current flow, propagated through the power lines, and intercepted by an attacker. We present two versions of the attack. In line level power-hammering the adversary taps the power cables feeding the transmitting computer. In phase level power-hammering the adversary taps the power lines at the phase level, in the main electrical service panel. Using a non-invasive tap, the attacker measures the emission conducted on the power cables. Based on the signal received, the transmitted data is demodulated and decoded back to a binary form.

In this paper we show how attackers can covertly leak data (e.g., encryption keys, passwords and files) from highly secure or air-gapped networks via the row of status LEDs that exists in networking equipment such as LAN switches and routers. Although it is known that some network equipment emanates optical signals correlated with the information being processed by the device ('side-channel'), intentionally controlling the status LEDs to carry any type of data ('covert-channel') has never studied before. A malicious code is executed on the LAN switch or router, allowing full control of the status LEDs. Sensitive data can be encoded and modulated over the blinking of the LEDs. The generated signals can then be recorded by various types of remote cameras and optical sensors. We provide the technical background on the internal architecture of switches and routers (at both the hardware and software level) which enables this type of attack. We also present amplitude and frequency based modulation and encoding schemas, along with a simple transmission protocol. We implement a prototype of an exfiltration malware and discuss its design and implementation. We evaluate this method with a few routers and different types of LEDs. In addition, we tested various receivers including remote cameras, security cameras, smartphone cameras, and optical sensors, and also discuss different detection and prevention countermeasures. Our experiment shows that sensitive data can be covertly leaked via the status LEDs of switches and routers at a bit rates of 10 bit/sec to more than 1Kbit/sec per LED.

Air-gapped computers are computers which are kept isolated from the Internet, because they store and process sensitive information. When highly sensitive data is involved, an air-gapped computer might also be kept secluded in a Faraday cage. The Faraday cage prevents the leakage of electromagnetic signals emanating from various computer parts, which may be picked up by an eavesdropping adversary remotely. The air-gap separation, coupled with the Faraday shield, provides a high level of isolation, preventing the potential leakage of sensitive data from the system. In this paper, we show how attackers can bypass Faraday cages and air-gaps in order to leak data from highly secure computers. Our method is based on an exploitation of the magnetic field generated by the computer's CPU. Unlike electromagnetic radiation (EMR), low frequency magnetic radiation propagates though the air, penetrating metal shielding such as Faraday cages (e.g., compass still works inside Faraday cages). Since the CPU is an essential part of any computer, our covert channel is relevant to virtually any device with a CPU: desktop PCs, servers, laptops, embedded systems and Internet of Things (IoT) devices. We introduce a malware code-named 'ODINI' that can control the low frequency magnetic fields emitted from the infected computer by regulating the load of the CPU cores. Arbitrary data can be modulated and transmitted on top of the magnetic emission and received by a magnetic receiver ('bug') placed nearby. We provide technical background and examine the characteristics of the magnetic fields. We implement a malware prototype and discuss the design considerations along with the implementation details. We also show that the malicious code does not require special privileges (e.g., root) and can successfully operate from within isolated virtual machines (VMs) as well. We present signal generation, transmission algorithms, and discuss data encoding and modulation schemes. We analyze the covert channel and evaluate it on various types of computers. Finally, we propose different types of defensive countermeasures such as signal detection and signal jamming to cope with this type of threat.

Converse magnetoelectric effect in ferromagnetic shape memory alloy/piezoelectric laminate Appl. Phys. Lett. 95, 022501 (2009)