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Method for carrying out grouping fuzz testing on software

A technology of fuzz testing and software, which is applied in software testing/debugging, computer parts, character and pattern recognition, etc. It can solve the problems that seeds cannot reflect the similarity of seeds well, the growth of tree nodes, etc., and achieve efficient fuzz testing Effect

Pending Publication Date: 2022-04-05
HANGZHOU DIANZI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, given the exponential number of function combinations for example, this design could lead to an explosion of tree nodes
Also, the hierarchical division of seeds may not reflect the similarity of seeds well

Method used

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  • Method for carrying out grouping fuzz testing on software
  • Method for carrying out grouping fuzz testing on software

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Embodiment Construction

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all of them. Based on the embodiments of the present application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present application.

[0029] The present invention first needs to group seeds, and in this embodiment, grouping includes the following steps:

[0030] (1) First, the distance between two seeds is defined according to the seed similarity. the s i and s j The distance between two seeds is defined as d(s i ,s j ) = d v (s i ,s j )+d e (s i ,s j ), where dv and d e Represents byte value distance and execution path distance, respectively.

[0031] In this embodiment,...

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Abstract

The invention discloses a method for carrying out grouping fuzzy testing on software, which comprises the following steps of: firstly, calculating the distance between seeds through execution paths of the seeds, byte values of seed contents and the like, and then grouping by utilizing a clustering method. After grouping, firstly, distributing seed energy, namely fuzzy test times through adaptive value sharing, and secondly, learning and applying an optimal variation mode in each group, including learning and applying optimal variation operation selection probability distribution of each group and optimal variation position selection probability distribution of each group; and 3, performing deterministic variation on the seeds in each group for scheduling. According to the method, the seeds are grouped by using the similarity among the seeds, so that fuzzy test preference information of similar seeds can be learned more effectively, and fuzzy test can be guided more efficiently.

Description

technical field [0001] The present application relates to the field of software security, in particular to a method for performing group fuzz testing on software. Background technique [0002] Software has been used in all aspects of people's lives, so it is very important to ensure software security. On the one hand, it needs to be standardized in software design and development, and on the other hand, it is necessary to find and repair the loopholes in the software in time through testing. Automated fuzz testing is currently a popular method for discovering software vulnerabilities. It provides various inputs to the program and monitors the software status at the same time to find problems in the software. [0003] Coverage-guided Fuzzing (CGF, or coverage-based fuzzing), represented by AFL (American Fuzzy Lop), has become a very popular fuzzy test because of its high efficiency in discovering software vulnerabilities. Testing technology has had a great impact in both in...

Claims

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Application Information

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IPC IPC(8): G06F11/36G06K9/62
Inventor 曾英佩吴铤申延昭郑秋华
Owner HANGZHOU DIANZI UNIV