The author acquired a Plustek 8200i negative scanner, expecting Linux support, but found the chipset had changed and was no longer compatible. Attempts to create a SANE driver manually were unsuccessful, leading to a temporary abandonment of the project.
A post on X by Tom Crider (Glorious Eggroll) detailing the use of AI to fix a mouse driver inspired a new approach. Crider's method involved giving an AI agent control of a Windows instance to capture necessary data for driver repair. This technique was then adapted for the scanner issue.
The author used Claude to set up a Windows virtual machine to capture USB data while the scanner operated under Windows. This data, combined with improvements in Claude's code generation capabilities, allowed the AI to produce a working Linux driver for the scanner within hours. Although initial scans had quality issues, they were recognizable, and a near-perfect driver with infrared support was developed shortly after.
Following the scanner's success, the same AI-assisted method was applied to resolve issues with MIPI camera support on a laptop. Claude reused the established data capture and analysis framework to generate patches for both the kernel driver and libcamera, significantly improving the camera's functionality.
The successful use of AI for reverse engineering hardware drivers suggests a new approach for developers facing similar compatibility challenges. The author plans to generalize and document the AI harness created, making the methodology accessible for others to use in their own hardware support efforts.
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A Red Hat engineering director developed an open-source tool, hw-harness, that uses an AI agent to create Linux drivers by analyzing Windows driver behavior. This method allowed him to create a working Linux driver for a previously unsupported scanner by comparing USB traffic from Windows and Linux implementations.
A developer successfully used an AI assistant, Claude, to reverse engineer hardware drivers for a Plustek 8200i scanner and a MIPI camera to enable Linux support. The process involved setting up a Windows virtual machine to capture USB data during hardware operation, which the AI then analyzed to generate driver code and patches. This method allowed for the creation of functional, albeit initially imperfect, drivers and kernel patches.