CVE-2026-7372

May 4, 2026, 3:21 p.m.

9.0
Critical

Description

A stack overflow vulnerability exists in the WebCam Server Login functionality of GeoVision GV-VMS V20 20.0.2. A specially crafted HTTP request can lead to an arbitrary code execution. An attacker can make an unauthenticated HTTP request to trigger this vulnerability. #### Stack-overflow via unconstrained sscanf The call to `sscanf` at [1] to split the `Buffer` variable into the `username` and `password` variables doesn't limit the size of the extracted content to match the destination buffers' sizes. In this case, if either the username or password decoded from the authorization string exceeds `40` characters (the size the stack variables `username` and `password`) then a stack overflow will occur. The data is controlled by an attacker, but sronger constraints (e.g. no null bytes) may make exploitation harder. A successful attack could lead to full code execution as SYSTEM on the machine running the service.

Product(s) Impacted

Vendor Product Versions
Geovision
  • Gv-vms
  • 20.0.2

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 geovision gv-vms 20.0.2 / / / / / / /

CVSS Score

9.0 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: May 4, 2026, 1:16 a.m.
Last Modified: May 4, 2026, 3:21 p.m.

Status : Undergoing Analysis

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

More info

Source

0df08a0e-a200-4957-9bb0-084f562506f9

*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.