Papers by Michele Carminati

1 papers
AutoCVSS: Assessing the Performance of LLMs for Automated Software Vulnerability Scoring (2025.emnlp-industry)

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Challenge: Increasing number of daily disclosed software vulnerabilities imposes significant pressure on security analysts, extending the time between disclosure and exploitation.
Approach: They propose to use Large Language Models to automate vulnerability risk score prediction using the industrial CVSS standard.
Outcome: The proposed model complements baselines in data-scarce settings without annotated data, highlighting their value in improving vulnerability management.

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