P2C: Understanding Output Data Files via On-the-Fly Transformation from Producer to Consumer Executions
Author(s) -
Yonghwi Kwon,
Fei Peng,
Dohyeong Kim,
KyungTae Kim,
Xiangyu Zhang,
Dongyan Xu,
Vinod Yegneswaran,
John Qian
Publication year - 2015
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.14722/ndss.2015.23318
Subject(s) - transformation (genetics) , computer science , data transformation , on the fly , database , operating system , data warehouse , biochemistry , chemistry , gene
In cyber attack analysis, it is often highly desirable to understand the meaning of an unknown file or network message in the absence of their consumer (i.e. the program that parses and understands the file/message). For example, a malware may stealthily collect information from a victim machine, store them as a file and later send it to a remote server. P2C is a novel technique that can parse and understand unknown files and network messages. Given a file/message that was generated in the past without the presence of any monitoring techniques, and a set of potential producers of the file/message, P2C systematically explores the execution paths in the producers without requiring any inputs. In the mean time, it tries to transform a producer execution to a consumer execution that closely resembles the ideal consumer execution that can parse the given unknown file/message. In particular, when a write operation is encountered in the original execution, P2C performs the opposite read operation on the unknown file/message and patches the original execution with the loaded value. In order to handle correlations between data fields in the file/message, P2C follows a trial-and-error approach to look for the correct transformation until the file/message can be parsed and the meaning of their fields can be disclosed. Our experiments on a set of real world applications demonstrate P2C is highly effective.
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