CVE-2026-73049 (GCVE-0-2026-73049)
Vulnerability from cvelistv5 – Published: 2026-08-14 11:35 – Updated: 2026-08-14 16:52
VLAI
EPSS
VEX
Title
SiYuan before v3.7.4 Information Disclosure via getAttributeViewBacklinks
Summary
SiYuan versions before v3.7.4 contain an information disclosure vulnerability in the getAttributeViewBacklinks endpoint that consults the forbidden access list instead of the visibility list when filtering backlinks. Anonymous readers can supply a publicly visible database row identifier to discover hidden-tier documents that reference it, receiving the database name, row title, and document path of hidden documents.
Severity
5.8 (Medium)
CWE
- CWE-863 - Incorrect Authorization
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/siyuan-note/siyuan/security/ad… | vendor-advisory |
| https://www.vulncheck.com/advisories/siyuan-befor… | third-party-advisory |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| siyuan-note | siyuan |
Affected:
0 , < 3.7.4
(semver)
Unaffected: 3.7.4 (semver) |
Date Public
2026-07-30 00:00
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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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