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A fuzzy testing framework based on AFL

A framework and test case technology, applied in the field of information security, can solve problems such as the inability to generate effective test cases in a highly structured data format and the blindness of AFL tools, so as to improve efficiency and coverage, increase the probability of being mutated, and reduce The effect of wasting time and space

Active Publication Date: 2018-12-18
BEIJING INSTITUTE OF TECHNOLOGYGY
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AI Technical Summary

Problems solved by technology

[0011] In view of this, the present invention provides a fuzzy testing framework based on AFL, which mainly solves the blindness problem of the current AFL tool in the test case generation strategy, and the inability to generate effective test cases for highly structured data formats

Method used

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  • A fuzzy testing framework based on AFL
  • A fuzzy testing framework based on AFL
  • A fuzzy testing framework based on AFL

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Effect test

test Embodiment i

[0072] Define 5 bitmaps: set the symbol map to represent a bitmap, and maintain a bitmap for any test case in the test case queue, ie The inventive method maintains a bitmap for each test case, and is mainly used to record each branch triggered by test case i and the number of branch triggers; map(i) b ≠0 means that the test case i corresponding to the bitmap triggers branch b, that is and map(i) b The value of represents the number of times test case i triggers branch b.

[0073] The method of the present invention also maintains a global bitmap map, which satisfies formula 1, wherein map(i) represents the bitmap of test case i.

[0074] map=U i∈Q map(i) formula 1

[0075] Definition 6 path: set symbol P to represent path, path P contains many branches, and path P can be considered as a collection of specific branches. The path P represents the set of hit branches during the execution of the program under test, represents test case i execution path P, b∈P represents p...

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Abstract

The invention discloses a fuzzy test framework based on AFL, which comprises a test case preprocessing module and an AFL processing module. In the AFL processing module, the test case selection sub-module sequentially selects the next test case to be mutated from the test case queue; before selection, according to the historical variation of test cases, those test cases with greater probability tofind new paths are identified as privileged test cases, and are selected as test cases to be mutated first. The test case mutation quantity determining sub-module adjusts the energy allocated to eachtest case according to the historical mutation of the test case, and then adjusts the mutation quantity of the test case to be mutated. The test case mutation sub-module determines the mutation byteaccording to the valid byte in the test case. The mutation is then performed according to the number of mutations and the mutation bytes. The invention solves the blindness problem of the current AFLtool in the test case generation strategy, and the insufficiency that the effective test case cannot be generated according to the highly structured data format.

Description

technical field [0001] The invention relates to the technical field of information security, in particular to an AFL-based fuzz testing framework. Background technique [0002] Fuzz testing is a method of discovering software faults by constructing unexpected inputs and monitoring the abnormal results of the target software, which can detect errors early before they occur. Fuzz testing has become one of the most effective testing techniques to find bugs and security vulnerabilities in programs, and it has been successfully used in security testing and quality assurance by major software companies such as Microsoft and Google. Fuzz testing usually tests a program by generating random input data and executing the program under such input, with the goal of executing as many program paths as possible to catch errors such as assertion violations, program crashes, etc. Although fuzzing generates many invalid test cases, due to the lower computational overhead, fuzzing generates t...

Claims

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Application Information

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IPC IPC(8): G06F11/36
CPCG06F11/3672G06F11/3684
Inventor 胡昌振马锐王夏菁李斌斌任帅敏
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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