CVE-2019-25603

March 23, 2026, 2:31 p.m.

8.6
High

Description

TuneClone 2.20 contains a structured exception handler (SEH) buffer overflow vulnerability that allows local attackers to execute arbitrary code by supplying a malicious license code string. Attackers can craft a payload with a controlled buffer, NSEH jump instruction, and SEH handler address pointing to a ROP gadget, then paste it into the license code field to trigger code execution and establish a bind shell.

Product(s) Impacted

Vendor Product Versions
Tuneclone
  • Tuneclone
  • 2.20

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-787
Out-of-bounds Write
The product writes data past the end, or before the beginning, of the intended buffer.

*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 tuneclone tuneclone 2.20 / / / / / / /

References

http://www.tuneclone.com/
http://www.tuneclone.com/tuneclone_setup.exe
https://www.exploit-db.com/exploits/47012
https://www.vulncheck.com/advisories/tuneclone-structured-exception-handler-buffer-overflow

Tags

CWE-787
[email protected]
2026-03-22
CVE-2019-25603

CVSS Score

8.6 / 10

CVSS Data - 4.0

  • Attack Vector: LOCAL
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • Exploit Maturity: NOT_DEFINED

    • CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/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: March 22, 2026, 2:16 p.m.
Last Modified: March 23, 2026, 2:31 p.m.

Status : Awaiting Analysis

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

More info

Source

[email protected]

*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.