CVE-2026-100640 (GCVE-0-2026-100640)
Vulnerability from cvelistv5 – Published: 2026-09-26 13:23 – Updated: 2026-09-26 13:23
VLAI
EPSS
VEX
Title
SiYuan before v3.8.4 Clipboard Data Disclosure via IPC
Summary
SiYuan before v3.8.4 contains an authorization omission in the siyuan-get IPC handler that allows remote-kernel renderers to access native clipboard formats by invoking clipboardReadMathML, clipboardReadOffice, and clipboardReadWPS commands with matching plaintext. Attackers controlling remote renderer content can obtain MathML formulas, Office bytes, and WPS bytes from local clipboard during user-mediated paste operations.
Severity
CWE
- CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor
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 | CPE status | |
|---|---|---|---|---|
| siyuan-note | siyuan |
Affected:
0 , < 3.8.4
(semver)
Unaffected: 3.8.4 (semver) |
guessed |
Date Public
2026-09-10 00:00
{
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"packageURL": "pkg:npm/siyuan-note/siyuan",
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}
],
"metrics": [
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"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
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"baseSeverity": "HIGH",
"exploitMaturity": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
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"subConfidentialityImpact": "NONE",
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"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
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"baseScore": 4.7,
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"confidentialityImpact": "LOW",
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"scope": "CHANGED",
"userInteraction": "REQUIRED",
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"version": "3.1"
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"description": "Exposure of Sensitive Information to an Unauthorized Actor",
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"type": "CWE"
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],
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"orgId": "83251b91-4cc7-4094-a5c7-464a1b83ea10",
"shortName": "VulnCheck"
},
"references": [
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"name": "GitHub Security Advisory (GHSA-mjmm-hgmc-m7qf)",
"tags": [
"vendor-advisory"
],
"url": "https://github.com/siyuan-note/siyuan/security/advisories/GHSA-mjmm-hgmc-m7qf"
},
{
"name": "VulnCheck Advisory: SiYuan before v3.8.4 Clipboard Data Disclosure via IPC",
"tags": [
"third-party-advisory"
],
"url": "https://www.vulncheck.com/advisories/siyuan-before-3.8.4-clipboard-data-disclosure-via-ipc"
}
],
"title": "SiYuan before v3.8.4 Clipboard Data Disclosure via IPC",
"x_generator": {
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"cveMetadata": {
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"cveId": "CVE-2026-100640",
"datePublished": "2026-09-26T13:23:13.287Z",
"dateReserved": "2026-09-26T02:32:35.659Z",
"dateUpdated": "2026-09-26T13:23:13.287Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2",
"vulnerability-lookup:meta": {
"epss": {
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"date": "2026-09-27",
"epss": "0.00188",
"percentile": "0.07586"
},
"nvd": {
"cve": {
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"packageURL": "pkg:npm/siyuan-note/siyuan",
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"versions": [
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"cveTags": [],
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{
"lang": "en",
"value": "SiYuan before v3.8.4 contains an authorization omission in the siyuan-get IPC handler that allows remote-kernel renderers to access native clipboard formats by invoking clipboardReadMathML, clipboardReadOffice, and clipboardReadWPS commands with matching plaintext. Attackers controlling remote renderer content can obtain MathML formulas, Office bytes, and WPS bytes from local clipboard during user-mediated paste operations."
}
],
"id": "CVE-2026-100640",
"lastModified": "2026-09-26T14:16:46.020",
"metrics": {
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"attackVector": "NETWORK",
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"Recovery": "NOT_DEFINED",
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"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
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"subConfidentialityImpact": "NONE",
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"valueDensity": "NOT_DEFINED",
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"published": "2026-09-26T14:16:45.820",
"references": [
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"source": "disclosure@vulncheck.com",
"url": "https://github.com/siyuan-note/siyuan/security/advisories/GHSA-mjmm-hgmc-m7qf"
},
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"sourceIdentifier": "disclosure@vulncheck.com",
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}
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"type": "Primary"
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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.
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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