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University of Notre Dame Notre Dame
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Overconfidence in LLM-generated code is rampant, with models often misjudging the security of their outputs, raising significant concerns for software safety.
Only 1% of CVE texts capture the configuration options needed to understand vulnerabilities, highlighting a critical gap in security documentation that PatchLens addresses.
