NDLI: A taint based approach for automatic reverse engineering of gray-box file formats

Content Provider	Springer Nature Link
Author	Cui, Baojiang Wang, Fuwei Hao, Yongle Wang, Lingyu
Copyright Year	2015
Abstract	File format vulnerabilities have been highlighted in recent years, and the performance of fuzzing tests relies heavily on the knowledge of target formats. In this paper, we present systematic algorithms and methods to automatically reverse engineer input file formats. The methodology employs dynamic taint analysis to reveal implicit relational information between input file and binary procedures, which is used for the measurement of correlations among data bytes, format segmentation and data type inference. We have implemented a prototype, and its general tests on 10 well-published binary formats yielded an average of over 85 % successful identification rate, while more detailed structural information was unveiled beyond coarse granular format analysis. Besides, a practical pseudo-fuzzing evaluation method is discussed in accordance with real-world demands on security analysis, and the evaluation results demonstrated the practical effectiveness of our system.
Starting Page	3563
Ending Page	3578
Page Count	16
File Format	PDF
ISSN	14327643
Journal	Soft Computing
Volume Number	20
Issue Number	9
e-ISSN	14337479
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-05-23
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Format reverse engineering Program semantics Dynamic taint analysis Fuzzing tests Computational Intelligence Artificial Intelligence (incl. Robotics) Mathematical Logic and Foundations Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Software Geometry and Topology

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