SeedAIchemy: LLM-Driven Seed Corpus Generation for Fuzzing
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866908656769957888 |
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| author | Wen, Aidan Alzahrani, Norah A. Jiang, Jingzhi Joe, Andrew Shieh, Karen Zhang, Andy Alomair, Basel Wagner, David |
| author_facet | Wen, Aidan Alzahrani, Norah A. Jiang, Jingzhi Joe, Andrew Shieh, Karen Zhang, Andy Alomair, Basel Wagner, David |
| contents | We introduce SeedAIchemy, an automated LLM-driven corpus generation tool that makes it easier for developers to implement fuzzing effectively. SeedAIchemy consists of five modules which implement different approaches at collecting publicly available files from the internet. Four of the five modules use large language model (LLM) workflows to construct search terms designed to maximize corpus quality. Corpora generated by SeedAIchemy perform significantly better than a naive corpus and similarly to a manually-curated corpus on a diverse range of target programs and libraries. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_12448 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SeedAIchemy: LLM-Driven Seed Corpus Generation for Fuzzing Wen, Aidan Alzahrani, Norah A. Jiang, Jingzhi Joe, Andrew Shieh, Karen Zhang, Andy Alomair, Basel Wagner, David Cryptography and Security Artificial Intelligence We introduce SeedAIchemy, an automated LLM-driven corpus generation tool that makes it easier for developers to implement fuzzing effectively. SeedAIchemy consists of five modules which implement different approaches at collecting publicly available files from the internet. Four of the five modules use large language model (LLM) workflows to construct search terms designed to maximize corpus quality. Corpora generated by SeedAIchemy perform significantly better than a naive corpus and similarly to a manually-curated corpus on a diverse range of target programs and libraries. |
| title | SeedAIchemy: LLM-Driven Seed Corpus Generation for Fuzzing |
| topic | Cryptography and Security Artificial Intelligence |
| url | https://arxiv.org/abs/2511.12448 |