CVE-2026-40887 (GCVE-0-2026-40887)
Vulnerability from cvelistv5 – Published: 2026-04-21 19:24 – Updated: 2026-04-22 13:41
VLAI
EPSS
VEX
Title
@vendure/core has a SQL Injection vulnerability
Summary
Vendure is an open-source headless commerce platform. Starting in version 1.7.4 and prior to versions 2.3.4, 3.5.7, and 3.6.2, an unauthenticated SQL injection vulnerability exists in the Vendure Shop API. A user-controlled query string parameter is interpolated directly into a raw SQL expression without parameterization or validation, allowing an attacker to execute arbitrary SQL against the database. This affects all supported database backends (PostgreSQL, MySQL/MariaDB, SQLite). The Admin API is also affected, though exploitation there requires authentication. Versions 2.3.4, 3.5.7, and 3.6.2 contain a patch. For those who are unable to upgrade immediately, Vendure has made a hotfix available that uses `RequestContextService.getLanguageCode` to validate the `languageCode` input at the boundary. This blocks injection payloads before they can reach any query. The hotfix replaces the existing `getLanguageCode` method in `packages/core/src/service/helpers/request-context/request-context.service.ts`. Invalid values are silently dropped and the channel's default language is used instead. The patched versions additionally convert the vulnerable SQL interpolation to a parameterized query as defense in depth.
Severity
9.1 (Critical)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-22 13:40 UTC
CWE
- CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/vendurehq/vendure/security/adv… | x_refsource_CONFIRM |
Impacted products
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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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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