Google demonstrated a practical pipeline to migrate a legacy C library to memory-safe Rust using AI, validated with automated fuzzing to prove semantic equivalence, and clarified that this is not a hands-off process.

The automated pathway aimed to improve memory safety and remove the need for certain process isolation sandboxes by porting giflib to Rust with ABI compatibility.

Experts note that AI translation requires ongoing human oversight—upstream divergence, maintenance of FFI wrappers, and scalability concerns for larger codebases.

Differential testing ran for six days with hundreds of millions of iterations, including adversarial prompts, to detect behavioral drift and edge cases.

The validation pipeline decoded over 30 million real-world GIFs from both implementations to ensure bit-for-bit parity, while a six-day differential fuzzer uncovered an unhandled edge case in the LZW decompressor and an out-of-bounds write from a prior patch.

Comprehensive regression testing at scale was used to verify parity across the GIF assets between C and Rust implementations.

The migration followed three stages: translate the C code to Rust with Gemini, refine pointer ownership and lifetimes at the FFI boundary, and apply automated differential testing with feedback to align behavior.

This three-stage automated process began with Gemini translation, then careful manual refinement of ownership, and ended with automated testing to ensure safe FFI boundaries.

giflib, a ~3,000-line C library, was ported to Rust while preserving ABI compatibility by keeping original symbols and struct definitions.

The project delivered an ABI-compatible Rust drop-in to replace the C shared object, ensuring downstream callers faced no breakages.

External researchers later reported an out-of-bounds heap write in upstream giflib, while the Rust port remained structurally immune, illustrating early security benefits.

Telemetry showed the Rust binary achieved runtime parity with the C binary, and reducing certain sandboxes lowered p99 tail latency in production image decoding clusters.