Malware, which is a malevolent software, mostly programmed by attackers for either disrupting the normal computer operation or gaining access to private computer systems. A malware detector determines the malicious intent of a program and thereafter, stops executing the program if the program is malicious. While a substantial number of various malware detection techniques based on static and dynamic analysis has been studied for decades, malware detection based on mining program graph features has attracted recent attention. It is commonly believed that graph based representation of a program is a natural way to understand its semantics and thereby, unveil its execution intent. This paper presents a state of the art survey on mining program-graph features for malware detection. We have also outlined the challenges of malware detection based on mining program graph features for its successful deployment, and opportunities that can be explored in the future.