A Security Analysis of Verifiable Credential Verification Pipelines: Attack Surface Arising from JSON-LD/RDFC Canonicalization Compared with SD-JWT VC and mdoc

We evaluate, at implementation level and under an explicit threat model, the verification pipelines of three Verifiable Credential (VC) formats: SD-JWT VC; the W3C Verifiable Credentials Data Model 2.0 with the Data Integrity cryptosuite eddsa-rdfc-2022 (W3C VCDM); and mdoc (ISO/IEC 18013-5). For W3C VCDM we identify and exercise three structural attack surfaces from remote context resolution and RDFC-1.0 canonicalization: denial of service (DoS) via poison graphs, context injection through @context, and server-side request forgery (SSRF) reachable via malicious URLs, all at default settings. A poison graph, whose blank-node references are symmetric enough to force RDFC-1.0 into deep recursion, raises it to 278x the baseline from five blank nodes in 527 bytes, and to 13.5 s from eight. Every experiment ran in four environments sharing runtime and library versions; the multiple moves with the machine (251--424x for one input), not with its speed. Cost tracks that symmetry rather than the node count: an acyclic input with 1,500 blank nodes stays at 462--714x. A call limit separates the two: every attack family aborts at 16 or below, every legitimate credential completes at 1, but a shallow, wide recursion, such as the acyclic control, passes whatever the bound. DoS does not presuppose adversarial input: with production education schemas, canonicalization costs 23--34x a simple credential in one environment, 16--49x across four. Effective mitigations are a static document loader, which removes the retrieval latency and both remote-context surfaces; a context allowlist; and a call limit with a size bound. SD-JWT VC and mdoc need neither canonicalization nor external references, and our verifiers resisted every vector evaluated. These are not format-specific defects but properties of the pipeline and its configuration.

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23 pages, 2 figures, 11 tables. Companion paper: arXiv:2611.03493. Measurement kit and raw result files: https://github.com/fujie/vcbench