Hardware Support to Improve Fuzzing Performance and Precision
PaperFirst seen 7/5/2026
Last seen 7/5/2026
Evidence 8 chunks
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15 connectionsThe paper evaluates SNAP's performance and precision benefits for fuzzing.
The paper provides detailed analysis of AFL's tracing overhead as a motivating example.
The paper focuses on improving coverage-guided fuzzing through hardware support.
The paper proposes SNAP, a customized hardware platform implementing hardware primitives for coverage-guided fuzzing.
Wen Xu is listed as a co-author of the paper.
Gururaj Saileshwar is listed as a co-author of the paper.
Taesoo Kim is listed as a co-author of the paper.
All authors are affiliated with Georgia Institute of Technology.
Hardware-assisted fuzzing is the key concept and keyword of the paper.
The paper compares SNAP's approach to Intel PT's hardware tracing, noting that Intel PT is not tailored for fuzzing.
The paper mentions RetroWrite as a binary rewriting approach with constraints compared to SNAP.
The paper mentions traditional dynamic taint analysis as an expensive existing technique.
Ren Ding is listed as a co-first author of the paper.
Yonghae Kim is listed as a co-first author of the paper.
Fan Sang is listed as a co-author of the paper.