English

Rethinking CyberSecEval: An LLM-Aided Approach to Evaluation Critique

Artificial Intelligence 2024-11-14 v1

Abstract

A key development in the cybersecurity evaluations space is the work carried out by Meta, through their CyberSecEval approach. While this work is undoubtedly a useful contribution to a nascent field, there are notable features that limit its utility. Key drawbacks focus on the insecure code detection part of Meta's methodology. We explore these limitations, and use our exploration as a test case for LLM-assisted benchmark analysis.

Keywords

Cite

@article{arxiv.2411.08813,
  title  = {Rethinking CyberSecEval: An LLM-Aided Approach to Evaluation Critique},
  author = {Suhas Hariharan and Zainab Ali Majid and Jaime Raldua Veuthey and Jacob Haimes},
  journal= {arXiv preprint arXiv:2411.08813},
  year   = {2024}
}

Comments

NeurIPS 2024, 2 pages