CVE-2026-40259

April 17, 2026, 3:38 p.m.

8.1
High

Description

SiYuan is an open-source personal knowledge management system. In versions 3.6.3 and below, the /api/av/removeUnusedAttributeView endpoint is protected only by generic authentication that accepts publish-service RoleReader tokens. The handler passes a caller-controlled id directly to a model function that unconditionally deletes the corresponding attribute view file from the workspace without verifying that the caller has write privileges or that the target attribute view is actually unused. An authenticated publish-service reader can permanently delete arbitrary attribute view definitions by extracting publicly exposed data-av-id values from published content, causing breakage of database views and workspace rendering until manually restored. This issue has been fixed in version 3.6.4.

Product(s) Impacted

Vendor Product Versions
Siyuan
  • Siyuan
  • <=3.6.3, 3.6.4

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-285
Improper Authorization
The product does not perform or incorrectly performs an authorization check when an actor attempts to access a resource or perform an action.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a siyuan siyuan <=3.6.3 / / / / / / /
a siyuan siyuan 3.6.4 / / / / / / /

CVSS Score

8.1 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: UNCHANGED
  • Confidentiality Impact: NONE
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H

    View Vector String

Timeline

Published: April 16, 2026, 11:16 p.m.
Last Modified: April 17, 2026, 3:38 p.m.

Status : Undergoing Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.