A Novel Approach To User Agent String Parsing For Vulnerability Analysis Using Mutli-Headed Attention

• URL: http://arxiv.org/abs/2306.03733v1
• Date: Tue, 6 Jun 2023 14:49:25 GMT
• Title: A Novel Approach To User Agent String Parsing For Vulnerability Analysis Using Mutli-Headed Attention
• Authors: Dhruv Nandakumar, Sathvik Murli, Ankur Khosla, Kevin Choi, Abdul Rahman, Drew Walsh, Scott Riede, Eric Dull, Edward Bowen
• Abstract summary: A novel methodology for parsing UASs using Multi-Headed Attention Based transformers is proposed. The proposed methodology exhibits strong performance in parsing a variety of UASs with differing formats. A framework to utilize parsed UASs to estimate the vulnerability scores for large sections of publicly visible IT networks or regions is also discussed.
• Score: 3.3029515721630855
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The increasing reliance on the internet has led to the proliferation of a diverse set of web-browsers and operating systems (OSs) capable of browsing the web. User agent strings (UASs) are a component of web browsing that are transmitted with every Hypertext Transfer Protocol (HTTP) request. They contain information about the client device and software, which is used by web servers for various purposes such as content negotiation and security. However, due to the proliferation of various browsers and devices, parsing UASs is a non-trivial task due to a lack of standardization of UAS formats. Current rules-based approaches are often brittle and can fail when encountering such non-standard formats. In this work, a novel methodology for parsing UASs using Multi-Headed Attention Based transformers is proposed. The proposed methodology exhibits strong performance in parsing a variety of UASs with differing formats. Furthermore, a framework to utilize parsed UASs to estimate the vulnerability scores for large sections of publicly visible IT networks or regions is also discussed. The methodology present here can also be easily extended or deployed for real-time parsing of logs in enterprise settings.

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