Code-Augur combines LLM-driven security specification inference with runtime falsification via guided fuzzing to improve vulnerability detection and reports finding 22 new vulnerabilities in open-source projects.
Donaldson, Guofei Gu, and Jeff Huang
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CR 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
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.
citing papers explorer
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Code-Augur: Agentic Vulnerability Detection via Specification Inference
Code-Augur combines LLM-driven security specification inference with runtime falsification via guided fuzzing to improve vulnerability detection and reports finding 22 new vulnerabilities in open-source projects.
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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.