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The Silent Danger in HTTP: Identifying HTTP Desync Vulnerabilities with Gray-box Testing

Authors: Mu, Keran; Chen, Jianjun; Zhuge, Jianwei; Li, Qi; Duan, Haixin; Feamster, Nick;

The Silent Danger in HTTP: Identifying HTTP Desync Vulnerabilities with Gray-box Testing

Abstract

HTTP Desync is a high-risk threat in today’s decentralized Internet, stemming from discrepancies among HTTP implementations. Current automatic detection tools, primarily dictionary-based scanners and black-box fuzzers, lack insights into internal states of implementations, leading to ineffective testing. Moreover, they focus on the request-side Desync, overlooking vulnerabilities in HTTP responses. In this paper, we present HDHunter, a novel automatic HTTP discrepancy detection framework using the gray-box coverage-directed differential testing technique. HDHunter can discover discrepancies in not only HTTP requests but also HTTP responses and CGI responses. We evaluated our HDHunter prototype against 19 state-of-the-art HTTP implementations and identified 17 new HTTP Desync vulnerabilities. We have disclosed all identified vulnerabilities to corresponding vendors and received acknowledgements and bug bounty rewards, including 9 CVEs from well-known HTTP software, including Apache, Tomcat, Squid, etc.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average