Polyglot: automatic extraction of protocol message format using dynamic binary analysis

By Juan Caballero, Heng Yin, Zhenkai Liang, Dawn Song. Conference on Computer and Communications Security, 2007

436 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/f095d26c79d76c119cf0d65759c9dfb6693ddc35

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Citations in the corpus

All You Ever Wanted to Know about Dynamic Taint Analysis and Forward Symbolic Execution (but Might Have Been Afraid to Ask) (2010, methodology): “taint analysis has been used to automatically understand the behavior of network protocols [15, 62] when given an implementation of the protocol.”
Large Language Model guided Protocol Fuzzing (2024, neutral): “To reduce the reliance on prior knowledge and manual work before fuzzing, several existing works have been proposed to dynamically infer message structures, including blackbox fuzzers [22], [35] and whitebox fuzzers [13], [16], [30].”
Ether: malware analysis via hardware virtualization extensions (2008, methodology): “Examples include systems derived from the BitBlaze project [3] (e.g., Polyglot [23] and Panorama [48]), Siren [22] and others.”
Taint-based directed whitebox fuzzing (2009, background): “Protocol Induction: The goal of automatic protocol induction or protocol reverse engineering is to automatically infer the ﬁle format or the grammar for valid inputs of a given program [6, 24, 15].”
Prospex: Protocol Specification Extraction (2009, methodology): “To address the limited precision of techniques that operate directly on the network traces, a number of systems [ 15 ]–[18] were introduced that focus on the (server) application.”
The Art, Science, and Engineering of Fuzzing: A Survey (2018, background): “topic of automated input format and protocol reverse engineering [69], [48], [146], [66], [31], only a few fuzzers leverage these techniques.”
AVATAR: A Framework to Support Dynamic Security Analysis of Embedded Systems' Firmwares (2014, background): “We believe that Avatar represents a flexible solution to provide a symbolic analysis environment which can greatly speed-up such blackbox analysis cases, aiming at automatically reverse engineer input formats [21], [9] and detect hidden data structures [53].”
AFLNET: A Greybox Fuzzer for Network Protocols (2020, methodology): “For instance, Polyglot [21] uses dynamic analysis techniques, such as tainting and symbolic execution to extract the message format from the protocol implementation.”
BitBlaze: A New Approach to Computer Security via Binary Analysis (2008, methodology): “We have proposed that binary program analysis can be used to aid automatic protocol reverse engineering [15].”
Scalable, Behavior-Based Malware Clustering (2009, methodology): “Recently, dynamic taint analysis has been also used for the automatic analysis of network protocols [18, 43].”
TaintScope: A Checksum-Aware Directed Fuzzing Tool for Automatic Software Vulnerability Detection (2010, background): “However, current symbolic execution engines and constraint solvers still cannot accurately generate and solve the constraints that describe the complete process of complex checksum algorithms [63].”
A Survey on Malware Detection Using Data Mining Techniques (2017, methodology): “A number of specialized analysis tools [Caballero et al. 2007; Kang et al. 2007; Yin et al. 2007] have been built on top of TEMU.”
Cracking Classifiers for Evasion: A Case Study on the Google's Phishing Pages Filter (2016, methodology): “However, it is not enough when the adversary leverages some modern analysis techniques, e.g., [11][24][51][56], to extract exploitable knowledge from binary-format software.”