Focusing on the characteristics of Internet of Things (IoT) terminal devices

including their large quantity

complex protocol types

distributed operating environments

and relatively long security maintenance cycles

this paper analyzes the security risks arising from firmware defects

weak passwords

open ports

communication protocol anomalies

and component vulnerabilities. To address the problems existing in traditional vulnerability detection

such as incomplete asset identification

fragmented detection results

static risk classification

and delayed early warning

a vulnerability detection and risk early-warning framework covering the entire operational lifecycle of terminal devices is constructed.The study takes terminal asset information

network traffic

port services

firmware components

and behavioral logs as the main data sources

and establishes a workflow of "asset identification—vulnerability detection—risk quantification—dynamic early warning—response feedback." Particular attention is given to multi-source vulnerability identification

risk indicator calculation

early-warning threshold adjustment

and result feedback

so that vulnerability detection results can be correlated with device exposure

business importance

and attack activities. A simulated IoT network is further used to verify the effectiveness of the detection method

providing an actionable technical approach for the security management of IoT terminal devices.