SeedSmith: LLM-Driven Seed Synthesis for Directed Fuzzing

Jul 16, 2026

SeedSmith is an agentic LLM pipeline designed to generate initial seed inputs for directed fuzzing by emulating a security analyst's workflow. It iteratively explores codebases, resolves indirect calls, identifies crash preconditions, and synthesizes concrete inputs, serving as a fuzzer-agnostic seed generation front-end. In evaluations, SeedSmith enabled fuzzers to achieve crash-time speedups of 11.51x to 14.66x on Magma and to trigger 16 previously unreachable bugs across 10 projects with diverse input formats.

Why it matters: SeedSmith demonstrates a significant advance in automating and improving the efficiency of vulnerability discovery through LLM-driven seed generation for fuzzing.

Full story at: arXiv Software Engineering ↗