The Grant Negotiation and Authorization Protocol: Attacking, Fixing, and Verifying an Emerging Standard

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Abstract

The Grant Negotiation and Authorization Protocol (GNAP) is an emerging authorization and authentication protocol which aims to consolidate and unify several use-cases of OAuth 2.0 and many of its common extensions while providing a higher degree of security. OAuth 2.0 is an essential cornerstone of the security of authorization and authentication for the Web, IoT, and beyond, and is used, among others, by many global players, like Google, Facebook, and Microsoft. Historical limitations of OAuth 2.0 and its extensions have led prominent members of the OAuth community to create GNAP, a newly designed protocol for authorization and authentication. Given GNAP’s advantages over OAuth 2.0 and its support within the OAuth community, GNAP is expected to become at least as important as OAuth 2.0. In this work, we present the first formal security analysis of GNAP. We build a detailed formal model of GNAP, based on the Web Infrastructure Model (WIM) of Fett, Küsters, and Schmitz, and provide formal statements of the key security properties of GNAP, namely authorization, authentication, and session integrity. We discovered several attacks on GNAP in the process of trying to prove these properties. We present these attacks, as well as changes to the protocol that prevent them. These modifications have been incorporated into the GNAP specification after discussion with the GNAP working group. We give the first formal security guarantees for GNAP, by proving that GNAP, with our modifications applied, satisfies the mentioned security properties. GNAP was still an early draft when we began our analysis, but is now on track to be adopted as an IETF standard. Hence, our analysis is just in time to help ensure the security of this important emerging standard.

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APA

Helmschmidt, F., Hosseyni, P., Küsters, R., Pruiksma, K., Waldmann, C., & Würtele, T. (2024). The Grant Negotiation and Authorization Protocol: Attacking, Fixing, and Verifying an Emerging Standard. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14346 LNCS, pp. 222–242). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-51479-1_12

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