Haya Schulmann

Oliver Jacobsen, Tobias Kirsch, Haya Schulmann et al.

The Resource Public Key Infrastructure (RPKI) secures the Internet's routing system by defining a complex trust and validation framework for certificates, Route Origin Authorizations (ROAs), manifests, and Certificate Revocation Lists (CRLs). These mechanisms are specified across dozens of RFCs. This paper presents the first comprehensive analysis of the causal link between flaws in RPKI Requests for Comments (RFCs) and vulnerabilities in implementations and real-world deployments. We reveal how vague, conflicting, or underspecified requirements in 50 RPKI RFCs propagate into inconsistent implementation behavior and operational failures. We conduct the first large-scale, impact-driven evaluation of RPKI specifications. Our methodology combines differential fuzzing of major RPKI implementations with Internet-wide crawling and validation log analysis, enabling us to trace practical vulnerabilities back to flawed RFC requirements. We uncover 61 previously undocumented inconsistencies in validation behavior, trace 23 directly to RFC flaws, and identify two novel vulnerabilities that were assigned CVEs. Our findings reveal that these are not isolated coding errors but rather systemic issues inherent in how RPKI standards are written, interpreted, and implemented. To mitigate these threats, we propose concrete recommendations and introduce a novel alerting service that monitors and reports live inconsistencies in RPKI deployments. Our open-source datasets, code, and tools support reproducibility and further research.

Haya Schulmann, Niklas Vogel

The Resource Public Key Infrastructure (RPKI) has become essential to secure inter-domain routing. Despite its critical role, RPKI software remains largely untested beyond shallow parsing. Existing fuzzers, like AFL++ or libFuzzer, do not work well for RPKI as they assume a single, self-contained input per execution, while RPKI repositories contain hundreds of interdependent cryptographically linked objects. Existing fuzzers fail to handle this complexity and lack the ability for precise coverage attribution in multi-object repositories, breaking feedback-based exploration and thereby missing most severe vulnerabilities in RPKI validation. In this paper, we overcome these limitations through novel fuzzing techniques, including continuous sampling and using functions as side-channels for per-object coverage attribution in large input repositories. We further show how parsing inputs to a labeled tree allows structural and semantic mutations while preserving cryptographic validity in mutated repositories. We implement our new techniques into a powerful fuzzing tool called CAT, combining non-sequential fuzzing with our template-agnostic ASN.1 mutation engine to achieve 66x throughput improvement over sequential fuzzing and exploring 24 - 47% more unique code paths compared to libFuzzer and previous work. Evaluating CAT on RPKI validators uncovered 21 previously unknown vulnerabilities with 8 CVEs already assigned (CVSS 7.5 - 9.8). These include a buffer overflow, Denial-of-Service (DoS), and exploitable repository-poisoning logic flaws. We open-source CAT to enable reproducibility, further research, and adaptation of our methods to other complex cryptography-based protocols such as DNSSEC and TLS.