CVE-2026-81633 (GCVE-0-2026-81633)
Vulnerability from cvelistv5 – Published: 2026-08-30 18:22 – Updated: 2026-08-30 18:22
VLAI
EPSS
VEX
Title
Unhandled KeyError in AshGraphql relay node resolution crashes queries via an unknown type segment
Summary
Improper Input Validation vulnerability in ash-project ash_graphql allows an unauthenticated client to crash a relay node(id: ...) query with an unhandled KeyError.
AshGraphql.Graphql.Resolver.resolve_node/2 decodes the client-supplied global ID with decode_relay_id/1, which only base64-decodes the string and splits it on : without validating the type segment. The decoded type is passed straight to Map.fetch!(type_to_domain_and_resource_map, type). Because fetch! raises on a missing key, a relay ID whose type segment is a valid atom that is not a relay-exposed type aborts the resolver before its resolve/2 clauses and their rescue handlers run, so the error never becomes a GraphQL error and may expose a stacktrace. Common resource names are easy to guess. The fix uses Map.fetch/2 and returns an Invalid node id error for unknown types.
This issue affects ash_graphql: from 0.27.0 before 1.11.0.
Severity
CWE
- CWE-20 - Improper Input Validation
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/ash-project/ash_graphql/securi… | vendor-advisoryrelated |
| https://cna.erlef.org/cves/CVE-2026-81633.html | related |
| https://osv.dev/vulnerability/EEF-CVE-2026-81633 | related |
| https://github.com/ash-project/ash_graphql/commit… | patch |
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| ash-project | ash_graphql |
Affected:
0.27.0 , < 1.11.0
(semver)
cpe:2.3:a:ash-project:ash_graphql:*:*:*:*:*:*:*:* |
||
| ash-project | ash_graphql |
Affected:
365b3aedc6b36f020e6a2c7dce63fa569243bc4e , < c8863ed8e5c21f1bfb6125f1d24e78443dfc6351
(git)
cpe:2.3:a:ash-project:ash_graphql:*:*:*:*:*:*:*:* |
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}
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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