Firmware vulnerability discrimination method and system based on open source component version identification

Abstract

The embodiment of the invention provides a firmware vulnerability discrimination method and system based on open source component version identification, and the method comprises the steps: scanning afirmware decoding package library, and obtaining a first path list of a to-be-analyzed component; traversing the first path list of the to-be-analyzed component, and associating and verifying the to-be-analyzed component and the open source component string database to obtain a second path list of the to-be-analyzed component; carrying out the version identification on the to-be-analyzed component to obtain a firmware open source component version number corresponding to the to-be-analyzed component; traversing the open source component version vulnerability dictionary, and if a firmware opensource component version number exists in the open source component version vulnerability dictionary, judging and knowing that the to-be-analyzed component is a suspicious vulnerability component; performing vulnerability verification on the suspicious vulnerability component, and storing the to-be-analyzed component passing the vulnerability verification into a firmware vulnerability component library. According to the embodiment of the invention, suspicious vulnerabilities can be efficiently searched, the reliability of firmware security evaluation is high, and the vulnerability discovery efficiency and accuracy are improved.

Description

technical field [0001] The present invention relates to the technical fields of Internet of Things device firmware security, binary vulnerability discovery, and security emergency response, and in particular to a firmware vulnerability identification method and system based on open source component version identification. Background technique [0002] With the transformation of the Internet era, the rise of the Internet of Things industry and the steady advancement of the Industrial Internet, embedded system equipment is becoming more and more networked, and Internet of Things devices are widely used in people's production and life. Smart devices such as routers, switches, network cameras, drones, and robots, while bringing convenience and improving work efficiency to people, also pose unprecedented challenges to the security of smart device systems and even the entire cyberspace. Different from traditional PC systems, IoT device systems usually contain specific underlying s...

AI Technical Summary

Problems solved by technology

However, these security vulnerability correlation techniques for large-scale firmware have problems such as low correlation efficiency and high false positive rate of correlation results, which makes the security analysis technology for large-scale firmware vulnerabilities still in continuous exploration.

Images