Researchers have created the first scalable, open-source benchmark dataset specifically designed to evaluate how Large Language Models perform in cybersecurity Capture-the-Flag (CTF) challenges.

Key Innovations:

• Developed a specialized database of diverse CTF challenges with metadata for comprehensive LLM testing
• Created a systematic evaluation framework to assess LLM capabilities in offensive security scenarios
• Established a scalable methodology that can grow with emerging cybersecurity challenges
• Enables more robust security testing of AI systems for vulnerability detection

This research addresses a critical gap in LLM evaluation, providing security professionals with standardized tools to assess AI capabilities in identifying and exploiting vulnerabilities before deployment in sensitive environments.

NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security