AI is changing the world. Don't stay behind. Clear summaries, community insight, delivered without the noise. Subscribe to never miss a beat.

N-Day-Bench – Can LLMs find real vulnerabilities in real codebases?

ndaybench.winfunc.com

April 13, 2026

1 min read

🔥🔥🔥🔥🔥

49/100

Summary

N-Day-Bench evaluates the ability of frontier language models to identify real-world vulnerabilities disclosed after their knowledge cut-off dates. The benchmark features a standardized testing environment and monthly updates to test cases, focusing on the vulnerability discovery capabilities of large language models.

Key Takeaways

N-Day-Bench evaluates the ability of language models to discover real-world vulnerabilities disclosed after their knowledge cut-off dates.
The benchmark is adaptive, with test cases updated monthly and models upgraded to their latest versions.
OpenAI's GPT-5 achieved the highest average score of 83.93 in the latest benchmark run.
All benchmark traces are publicly accessible for review.

Read original article

Community Sentiment

Mixed

Positives

The N-Day-Bench offers an innovative approach to evaluating LLMs in real-world scenarios, which could enhance the security landscape by identifying vulnerabilities effectively.
Incorporating false-positive rates into the evaluation rubric is crucial, as it addresses a significant concern in model reliability and accuracy.
The benchmark design and results are seen as interesting and valuable, suggesting a positive reception among those familiar with application security.

Concerns

The complexity of the evaluation process, including terms like 'Curator' and 'Finder', may alienate those not well-versed in the methodology, highlighting a communication gap.
There are concerns about the high false-positive rates of the models, which could undermine trust in their effectiveness for real-world applications.