Democratizing Laser Fault Injection: Building Your Own RayV Rig

TLDR: Laser fault injection (LFI) and laser logic state imaging (LLSI) have historically been restricted to well-funded labs due to the prohibitive cost of precision optical equipment. This research demonstrates how to construct a functional, 3D-printed LFI/LLSI platform for under $320 using off-the-shelf components. By leveraging the photoelectric effect in transistors, researchers can now perform advanced side-channel analysis and security bypasses on embedded microcontrollers at a fraction of the traditional cost.

Hardware security research often hits a wall when the barrier to entry is a five-figure price tag for optical benches and precision stages. Most of us have been told that if we want to perform laser fault injection, we need a dedicated lab, a YAG laser, and a specialized microscope. That narrative is officially dead. The recent work presented at Black Hat 2024 on the RayV platform proves that you can achieve high-precision fault injection and state imaging using a 3D-printed OpenFlexure microscope body and a $6 laser pointer.

The Mechanics of Low-Cost LFI

Fault injection is about forcing a processor to skip instructions or corrupt data at a critical moment, such as during a secure boot check or a cryptographic operation. While voltage glitching is the standard entry point for most researchers, it is often noisy and destructive. Laser fault injection offers a cleaner, more surgical approach.

Every transistor on a chip is essentially a poor-quality photodiode. When you hit a transistor with a laser, you inject charge into the silicon. If you time that pulse correctly, you can flip a bit or force a branch instruction to resolve in your favor. The traditional approach uses high-power lasers to deliver massive energy in nanoseconds. However, the research shows that you do not need a sledgehammer to crack a nut. By using a lower-power laser over a slightly longer duration—roughly 25 nanoseconds—you can accumulate the same charge required to induce a fault without physically damaging the target.

From Imaging to Extraction

The most impressive part of this research is the transition from simple fault injection to Laser Logic State Imaging (LLSI). If you can see the state of the transistors, you can read the memory directly from the silicon.

The team utilized the photoelectric effect to map the state of SRAM cells. When a transistor is active, its optical properties change slightly. By scanning the chip with a laser and measuring the reflected light, you can build a map of the logic states. The challenge is that every chip has a unique layout, and the signal-to-noise ratio is abysmal.

To solve this, the researchers used a clever differential imaging technique. By capturing an LLSI image of a known state and subtracting it from an unknown state, they isolated the bits that had changed. This differential image acts as a fingerprint for the data stored in memory. Once you have a clean image, you can use a Convolutional Neural Network (CNN) to automate the classification of these bit patterns, effectively turning a raw optical scan into a readable memory dump.

Practical Implementation for Pentesters

If you are performing a hardware assessment on an embedded device, you no longer need to ship the target to a specialized lab. The RayV platform allows you to bring the lab to the target. During an engagement, you would first perform chemical decapsulation or mechanical thinning to expose the die. Once the silicon is accessible, the RayV rig provides the nano-positioning required to target specific regions of interest, such as the memory controller or the instruction decoder.

The use of 1300nm lasers is a critical detail here. At this wavelength, silicon is largely transparent, allowing you to image and inject faults through the backside of the chip. This is a massive advantage because it avoids the need to remove complex top-layer metal shielding that often protects the logic.

Defensive Considerations

Defending against LFI is difficult because it targets the physical properties of the silicon itself. If you are designing hardware, the most effective mitigations are physical. Light-shielding layers, active metal meshes that trigger a tamper response when broken, and redundant logic paths are the only real ways to stop a determined researcher. From a firmware perspective, you can implement sensor-based detection to monitor for unexpected power fluctuations or timing anomalies, but these are often bypassable if the attacker has direct access to the die.

What Comes Next

The release of the RayV design files is a call to action for the hardware security community. We are moving into an era where advanced side-channel analysis is becoming a commodity tool in the pentester’s kit. If you have a 3D printer and a few hundred dollars, you can now replicate research that was previously the domain of nation-state actors and high-end security firms.

The next frontier is not just building the hardware, but refining the signal processing. The current model relies on training sets, but as more researchers contribute their own chip fingerprints to the open-source community, we will likely see a library of "known-good" chip layouts emerge. Start by printing the OpenFlexure components and sourcing the laser diodes. The hardware is ready; the only question is what you plan to target first.