LLMVD.js uses LLM agents to confirm 84% of taint-style vulnerabilities on public benchmarks (vs. <22% for prior tools) and generates validated exploits for 36 of 260 new packages (vs. ≤2 for traditional tools).
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6 Pith papers cite this work. Polarity classification is still indexing.
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GitHub Security Advisories follow two review-latency regimes—a fast path for repository advisories and a slow path for NVD-first advisories—explained by a queueing model of the processing pipeline.
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.
Machine learning models forecast future OpenSSF Maintained scores on PyPI-linked GitHub repos with accuracies above 0.95 for bucketed maintenance levels and 0.79 for trend categories.
PyPI metadata gaps arise mainly from oversight, skepticism, and platform preferences, as shown by surveys of 1,776 responses analyzed with a robust LLaMA-based topic model.
79.1% of PyPI libraries provide at least one valid email address, primarily from PyPI metadata, with high coverage extending to dependency chains.
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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.