Multi-representational learning models for static analysis of source code

A method, comprising:

• storing on a networked device a set comprising one or more multi-representation learning (MRL) models for static analysis of source code;
• performing a static analysis of source code associated with a sample received at the network device, wherein performing the static analysis includes using at least one stored MRL model;
• and
• determining that the sample is malicious based at least in part on the static analysis of the source code associated with the received sample, and in response to determining that the sample is malicious, perform an action based on a security policy.

A computer program product embodied in a tangible computer readable storage medium and comprising computer instructions for:

• storing on a networked device a set comprising one or more multi-representation learning to (MRL) models for static analysis of source code;
• performing a static analysis of source code associated with a sample received at the network device, wherein performing the static analysis includes using at least one stored MRL model;
• and
• determining that the sample is malicious based at least in part on the static analysis of the is source code associated with the received sample, and in response to determining that the sample is malicious, perform an action based on a security policy.