In Security, a Missed Bug Beats a False Alarm Every Time: Appen’s Security Benchmark
See how 21 frontier AI models performed against 141 human-verified vulnerabilities and discover why recall matters most when evaluating AI for application security.
When evaluating AI for application security, not all mistakes carry the same cost. A false positive may slow developers down, but a missed vulnerability can have far greater consequences.
Appen’s Security Benchmark evaluates 21 frontier AI models against 141 human-verified vulnerabilities across 16 CWE families, providing a data-driven look at how today’s leading models perform in real-world vulnerability detection. Explore benchmark results, model performance, and key insights into the strengths, tradeoffs, and limitations of AI-assisted application security.
What You’ll Learn
- How 21 frontier AI models performed against real-world security vulnerabilities
- Why recall is a critical metric for evaluating AI-powered security tools
- Which vulnerability classes AI models identify well and where they continue to struggle
- Practical insights to help evaluate AI-assisted application security strategies
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