LiveFuzz extends directed greybox fuzzing with abstract path mapping and risk-based mutation to expose library vulnerabilities from client programs on a 61-case dataset, reaching more target paths and triggering three vulnerabilities no baseline found.
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LLMs handle LTL syntax better than semantics, improve with detailed prompts, and perform substantially better when the task is reframed as Python code completion.
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Triggering and Detecting Exploitable Library Vulnerability from the Client by Directed Greybox Fuzzing
LiveFuzz extends directed greybox fuzzing with abstract path mapping and risk-based mutation to expose library vulnerabilities from client programs on a 61-case dataset, reaching more target paths and triggering three vulnerabilities no baseline found.
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Syntax Is Easy, Semantics Is Hard: Evaluating LLMs for LTL Translation
LLMs handle LTL syntax better than semantics, improve with detailed prompts, and perform substantially better when the task is reframed as Python code completion.