CVE-2025-65843

Dec. 4, 2025, 5:15 p.m.

7.7
High

Description

Aquarius Desktop 3.0.069 for macOS contains an insecure file handling vulnerability in its support data archive generation feature. The application follows symbolic links placed inside the ~/Library/Logs/Aquarius directory and treats them as regular files. When building the support ZIP, Aquarius recursively enumerates logs using a JUCE directory iterator configured to follow symlinks, and later writes file data without validating whether the target is a symbolic link. A local attacker can exploit this behavior by planting symlinks to arbitrary filesystem locations, resulting in unauthorized disclosure or modification of arbitrary files. When chained with the associated HelperTool privilege escalation issue, root-owned files may also be exposed.

Product(s) Impacted

Vendor Product Versions
Aquarius
  • Aquarius Desktop
  • 3.0.069

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-59
Improper Link Resolution Before File Access ('Link Following')
The product attempts to access a file based on the filename, but it does not properly prevent that filename from identifying a link or shortcut that resolves to an unintended resource.

*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 aquarius aquarius_desktop 3.0.069 / / / / / / /

CVSS Score

7.7 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: Dec. 3, 2025, 5:15 p.m.
Last Modified: Dec. 4, 2025, 5:15 p.m.

Status : Awaiting Analysis

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

More info

Source

cve@mitre.org

*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.