QuartetFuzz introduces the Four Principles framework for harness correctness and deploys an autonomous LLM agent that produces verified harnesses, yielding 29 confirmed bugs across 23 projects and identifying violations in existing harnesses.
Towards reliable llm-driven fuzz testing: Vision and road ahead
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
MASFuzzer generates fuzz drivers via mined multidimensional API sequences and adaptive scheduling, delivering 8.54% higher code coverage and 16 new vulnerabilities across 12 libraries.
citing papers explorer
-
Quality-Assured Fuzz Harness Generation via the Four Principles Framework
QuartetFuzz introduces the Four Principles framework for harness correctness and deploys an autonomous LLM agent that produces verified harnesses, yielding 29 confirmed bugs across 23 projects and identifying violations in existing harnesses.
-
MASFuzzer: Fuzz Driver Generation and Adaptive Scheduling via Multidimensional API Sequences
MASFuzzer generates fuzz drivers via mined multidimensional API sequences and adaptive scheduling, delivering 8.54% higher code coverage and 16 new vulnerabilities across 12 libraries.