An Evaluation of the Semantic Understanding Capabilities of Large Language Models for Web Attack Payloads

arXiv:2610.06507 · cs.CR · Submitted 2026-10-05 · Read on arXiv

cs.CR

Submitted: 2026-10-05

Updated: 2026-10-05

Comments: Accepted at the 6th International Conference on Computer Vision, Application and Algorithm (CVAA 2026). 16 pages

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Semantic Understanding — 1× in this paper · explained in 2 episodes

Sources

• GPT-4 Technical Report
• When LLMs Meet Cybersecurity: A Systematic Literature Review
• Large Language Models for Cyber Security: A Systematic Literature Review
• Explaining and Harnessing Adversarial Examples
• Exploring the Role of Large Language Models in Cybersecurity: A Systematic Survey
• HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs)
• CyberMetric: A Benchmark Dataset based on Retrieval-Augmented Generation for Evaluating LLMs in Cybersecurity Knowledge

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