As increasing reporting and disclosure of vulnerability code samples and extensive applications of machine learning methods, software vulnerability analysis methods based on machine learning have become a hot research direction in information security. After analysis of existing research work, we propose a software vulnerability analysis framework based on machine learning. We then review and classify existing machine learning based vulnerability methods, and conduct comparative analysis. We briefly analyze the challenges for machine learning based software vulnerability analysis methods, and discuss future research trends.