Defect detection method and system for cross-architecture firmware heap memory

Abstract

The embodiment of the invention provides a defect detection method and system for a cross-architecture firmware heap memory. The method comprises the steps: acquiring an application program in a simulator and firmware, and analyzing the application program in the simulator based on a binary translation technology, so as to enable the application program to be matched with a preset test environmentsystem architecture; and performing mapping to generate a shadow memory by traversing and executing the registered heap memory read-write hook function and the heap memory allocation hook function, and executing a preset memory defect detection algorithm based on the shadow memory to obtain a heap memory defect detection result. According to the embodiment of the invention, the cross-platform characteristic of the execution module is simulated; a detection tool does not need to be deployed into equipment where firmware is located, the unpractical requirement that a traditional memory detection tool needs to be deployed in the device is greatly overcome, the firmware test efficiency is improved, the problem that the storage space of the IoT device is limited is solved, and meanwhile, the memory defect detection module also provides an effective solution for detecting various heap memory defects in a cross-architecture firmware scene.

Description

technical field [0001] The invention relates to the technical field of defect detection, in particular to a defect detection method and system for a cross-architecture firmware heap memory. Background technique [0002] With the rapid growth of the number of IoT devices, the number of IoT devices is expected to reach 9.9 billion by the end of 2020. Today, the technical threshold for attacking is getting lower and lower, and IoT terminal devices have become new attack targets. Routers, cameras, refrigerators, sweeping robots, water meters, and smart street lights will all become potential attack targets. Kaspersky IoT Security Report "New trends in the world of IoT threats" pointed out that the number of IoT malicious samples captured has exploded in recent years. According to Gartner's forecast, by the end of 2020, more than 25% of cyber attacks detected by enterprises will involve IoT devices. [0003] Memory security flaws such as buffer overflows have always been the lo...

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Problems solved by technology

[0006] Embodiments of the present invention provide a defect detection method and system for cross-architecture firmware heap memory, which are used to solve the problems of insufficient processor architecture support, difficult implementation, and low efficiency after implementation in the cross-architecture firmware memory defect detection method in the prior art.

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