With the popularization of social networks, as a low-cost, high-efficiency entail attack method, most of the attack vectors were embedded in email attachments, and exploited vulnerability on Adobe and Office software. Among which PDF-based exploit samples are the main ones. In this paper, we combine bioinformatics and genetics and propose the pdf exploitable malware gene to analyze whether the exploits are exploited in the pdf malware based on software genes. We construct the experiments on the dataset collected from Virus Total filtered by the labels of multiple antivirus software. With the evaluation experiments, the results demonstrate the effectiveness of the pdf exploitable malware gene to detection and classification.