CVE-2026-100633 (GCVE-0-2026-100633)
Vulnerability from cvelistv5 – Published: 2026-09-26 13:23 – Updated: 2026-09-26 13:23
VLAI
EPSS
VEX
Title
SiYuan 3.8.0 through 3.8.3 Path Traversal via MCP File Operations
Summary
SiYuan is a self-hosted personal knowledge management system. In versions 3.8.0 through 3.8.3, the MCP file tool's sensitive-path guard (util.IsForbiddenAbsPath(), invoked from resolvePath()) is applied only to the allowed root of recursive operations and not to each resolved descendant path — an incomplete fix for GHSA-c8r8-95hg-mp34. An authenticated administrator using the in-app Agent or the external MCP server can therefore bypass the protected-workspace-file denylist: file.grep can return matching lines from non-hidden protected descendants (for example conf/conf.json, TLS keys, data/snippets/conf.json, data/templates/, data/.siyuan/publishAccess.json, notebook .siyuan internals, or the kernel log), file.copy can copy protected descendants to an ordinary path where file.read can then retrieve them, and unzip can overwrite protected descendants using ordinary, lexically contained ZIP member names. Because file.grep is globally classified as a safe action, it receives no per-call confirmation, and the confirmation cards for file.copy and unzip show only the allowed root arguments. This issue is fixed in version 3.8.4. Suggested title: SiYuan 3.8.0 through 3.8.3 Sensitive-Path Guard Bypass in Recursive MCP File Operations.
Severity
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-3.8.0… | third-party-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| siyuan-note | siyuan |
Affected:
3.8.0 , < 3.8.4
(semver)
Unaffected: 3.8.4 (semver) cpe:2.3:a:b3log:siyuan:*:*:*:*:*:*:*:* |
Date Public
2026-09-11 00:00
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"url": "https://github.com/siyuan-note/siyuan/security/advisories/GHSA-9g6v-r3xf-673q"
},
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}
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"lastModified": "2026-09-26T14:16:44.800",
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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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