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Journal of Information Security and Applications
Article . 2021 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
http://dx.doi.org/10.1016/j.ji...
Article
License: Elsevier TDM
Data sources: Sygma
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NodeXP: NOde.js server-side JavaScript injection vulnerability DEtection and eXPloitation

Authors: Ntantogian, Christoforos; Bountakas, Panagiotis; Antonaropoulos, Dimitris; Patsakis, Constantinos; Xenakis, Christos;

NodeXP: NOde.js server-side JavaScript injection vulnerability DEtection and eXPloitation

Abstract

Abstract Web applications are widely used, and new ways for easier and cost-effective methods to develop them are constantly introduced. A common omission among the new development and implementation techniques when designing them is security; Node.js is no exception, as Server-Side JavaScript Injection ( SSJI ) attacks are possible due to the use of vulnerable functions and neglecting to sanitize data input provided by untrusted sources. This specific kind of injection attack stands out because it has the potential to compromise servers, where the JavaScript code is executed. In this work, we fill a significant gap in the literature by introducing NodeXP , which, to the best of our knowledge, is the first methodology (presented as a software tool) that detects and automatically exploits SSJI vulnerabilities. Beyond the capabilities of the current state-of-the-art tools, NodeXP uses obfuscation methods, making it more stealth and adaptive to the current needs of red teaming. To this end, we provide a thorough analysis of SSJI attacks and the foundation upon which they rely on, along with concrete examples to facilitate the reader to comprehend the underlying concepts. Finally, we evaluate NodeXP , compare it to its peers, and discuss its efficacy.

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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!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
14
Top 10%
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4
127
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