CVE-2025-5148

May 25, 2025, 12:15 p.m.

4.8
Medium

Description

A vulnerability was found in FunAudioLLM InspireMusic up to bf32364bcb0d136497ca69f9db622e9216b029dd. It has been classified as critical. Affected is the function load_state_dict of the file inspiremusic/cli/model.py of the component Pickle Data Handler. The manipulation leads to deserialization. An attack has to be approached locally. This product is using a rolling release to provide continious delivery. Therefore, no version details for affected nor updated releases are available. The name of the patch is 784cbf8dde2cf1456ff808aeba23177e1810e7a9. It is recommended to apply a patch to fix this issue.

Product(s) Impacted

Vendor Product Versions
Funaudiollm
  • Inspiremusic
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-20
Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.

*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 funaudiollm inspiremusic / / / / / / / /

CVSS Score

4.8 / 10

CVSS Data - 4.0

  • Attack Vector: LOCAL
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: LOW
  • Integrity Impact: LOW
  • Availability Impact: LOW
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: May 25, 2025, 12:15 p.m.
Last Modified: May 25, 2025, 12:15 p.m.

Status : Received

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

More info

Source

cna@vuldb.com

*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.