No work limit on normalize() in any released version (RDFC-1.0 §4.4.3), and data for choosing the 4.0.0 maxPermutations default
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@mielvds ya está trabajando en esto.
Desde el 9/11/2026.
Evaluación
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Aptitud para principiantes
- 35/100
Línea de trabajo
Start by reviewing the unreleased 4.0.0 maxPermutations implementation and the RDFC-1.0 §4.4.3 requirement. Compare candidate defaults against the specification test suite and the poison-graph and acyclic-control measurements linked in the issue; done means the default is supported by evidence that it stops the cyclic attacks without rejecting legitimate inputs, with a release decision addressed.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
Hello — we benchmarked RDFC-1.0 canonicalization across several implementations
for a paper we are about to post to arXiv, and we would rather give you the
numbers before it goes out than after.
What we measured
In PyLD 3.3.0 — the current PyPI release — jsonld.normalize() places no bound
on the Hash N-Degree Quads recursion. RDFC-1.0 §4.4.3 states that implementations
MUST defend against denial-of-service by raising an exception and terminating
early, and the note there suggests a call limit derived from the blank node count.
The cost of not having one is small to trigger. A complete graph K_5 — five
mutually referencing blank nodes in 527 bytes of JSON-LD — costs about
278x a plain credential. K_8, at 1,196 bytes, runs for seconds. The cost
follows the symmetry of the blank-node references rather than the document size,
so a request-size cap is not a defence: the attack fits inside any limit a
verifier would plausibly set.
We also measured what a caller can do about it today. A timeout imposed from
outside the call returns to the caller on schedule but does not stop the work —
canonicalization keeps a core busy afterwards. In Python, the only control we
found that actually interrupts the computation is a SIGALRM delivered to the
main thread, which is not available to a library consumer running in a worker
thread or under an async framework.
What we found in master
While writing this up we found that the unreleased 4.0.0 already adds
maxPermutations (default 10000) and raises
maximum canonicalization work exceeded. That addresses the issue, and we have
corrected our paper to say that no released version exposes a limit rather
than that PyLD exposes none.
Two things we think are still worth raising:
-
There is no release that has it.
pip install pyldtoday gives 3.3.0.
If 4.0.0 is close, cutting it would do more for users than anything we could
suggest here. -
Choosing the default is the harder half, and we have data on it. On the
JavaScript side,rdf-canonize5.0.0 shipsmaxWorkFactor=1, which stops
every cyclic family we tried — but it also aborts acyclic inputs with 16
and 20 blank nodes, and 18 cases of the RDFC-1.0 specification test suite.
The clean separation we measured — every cyclic attack family stopped, every
legitimate input admitted — appears one step looser than that. In other words
a default tight enough to feel safe can reject well-formed credentials that
merely have many structurally similar blank nodes, and the threshold deserves
to be picked against measurements rather than intuition. We are happy to run
a sweep ofmaxPermutationsover your own corpus or test suite if that would
be useful.
Reproducing
The poison-graph generators and the measurement harness are at
https://github.com/fujie/vcbench — the families are complete graphs K_n, rings
C_n, cubic circulants, and an acyclic forest control, so false positives are
visible as well as true positives.
On disclosure
We are not reporting this as an embargoed vulnerability and are not asking for
one. RDFC-1.0 documents dataset poisoning in §7.1 and requires a defence in
§4.4.3, so there is nothing here an attacker could not derive from the
specification; what the paper contributes is the price of the missing default,
in bytes and milliseconds on commodity hardware. We expect to post it in the
coming weeks and are glad to cite a 4.0.0 release if one lands first.
Thank you for PyLD — and for FrozenDocumentLoader, which is the other half of
what we end up recommending to verifiers.
Naohiro Fujie and Shigeya Suzuki
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Preparar el entorno
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- Leer la guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
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