CVE-2025-9310

Aug. 21, 2025, 6:15 p.m.

5.5
Medium

Description

A vulnerability was determined in yeqifu carRental up to 3fabb7eae93d209426638863980301d6f99866b3. Affected by this vulnerability is an unknown functionality of the file /carRental_war/druid/login.html of the component Druid. Executing manipulation can lead to hard-coded credentials. The attack may be launched remotely. The exploit has been publicly disclosed and may be utilized. This product operates on a rolling release basis, ensuring continuous delivery. Consequently, there are no version details for either affected or updated releases.

Product(s) Impacted

Vendor Product Versions
Yeqifu
  • Carrental
  • *
Unknown
  • Druid
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-259
Use of Hard-coded Password
The product contains a hard-coded password, which it uses for its own inbound authentication or for outbound communication to external components.

*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 yeqifu carRental / / / / / / / /
a unknown Druid / / / / / / / /

CVSS Score

5.5 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: LOW
  • Integrity Impact: NONE
  • Availability Impact: NONE
  • Exploit Maturity: PROOF_OF_CONCEPT
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:P/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: Aug. 21, 2025, 5:15 p.m.
Last Modified: Aug. 21, 2025, 6:15 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.