Systems and methods for detecting vulnerablities in internet-of-things (iot) devices

A system for detecting vulnerabilities in devices within a network, comprising:

• a memory;
• and
• a hardware processor communicatively coupled with the memory and configured to:
• intercept a plurality of packets being transmitted in a network with a plurality of devices;
• identify, from the plurality of packets, a subset of packets corresponding to a first device of the network;
• extract a plurality of features representing device behavior from the subset of packets;
• embed the plurality of features into an input vector;
• execute a machine learning algorithm that receives the input vector and outputs a device type of the first device, wherein the machine learning algorithm is trained using a training dataset comprising network traffic information for a subset of all device types, the subset being labelled with device types, and a list of attributes of each respective device type of all device types;
• perform, for the first device, a security scan specific to the device type to detect vulnerabilities in the first device;
• and
• in response to detecting a vulnerability based on the security scan, generate a vulnerability assessment report for the first device.

A non-transitory computer readable medium storing thereon computer executable instructions for detecting vulnerabilities in devices within a network, including instructions for:

• intercepting a plurality of packets being transmitted in a network with a plurality of devices;
• identifying, from the plurality of packets, a subset of packets corresponding to a first device of the network;
• extracting a plurality of features representing device behavior from the subset of packets;
• embedding the plurality of features into an input vector;
• executing a machine learning algorithm that receives the input vector and outputs a device type of the first device, wherein the machine learning algorithm is trained using a training dataset comprising network traffic information labelled with device types and a list of attributes of each respective device type;
• performing, for the first device, a security scan specific to the device type to detect vulnerabilities in the first device;
• and
• in response to detecting a vulnerability based on the security scan, generating a vulnerability assessment report for the first device.