CyberSecEval 4
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CyberSecEval 4 is an evaluation suite covering cybersecurity-related capabilities and risks of large language models. The insecure-code-generation tracks measure whether a model produces vulnerable code: the Instruct track presents coding requests designed to elicit known insecure patterns, while the Autocomplete track prompts the model with code context leading up to a known insecure pattern, with vulnerabilities detected via static analysis.
Methodology
Imported from llm-stats public benchmark metadata. Modality: text. Max score: 1. Categories: code, safety. Language: en. Verified by llm-stats: no.