CVE-2026-25551

June 4, 2026, 7:15 p.m.

8.5
High

Description

Seagull Software BarTender 2021 R1 through 12.0.1 contains an insecure deserialization vulnerability that allows low-privileged local users to escalate privileges. The DataServiceSingleton .NET Remoting endpoint is bound to localhost on TCP port 7375 via BtSystem.Service.exe, limiting the attack surface to local access only. The endpoint is configured with BinaryServerFormatterSinkProvider and TypeFilterLevel set to Full. A low-privileged local attacker can send YSoSerial.NET-generated BinaryFormatter payloads to the localhost-bound endpoint to achieve code execution as NT AUTHORITY\\SYSTEM.

Product(s) Impacted

Vendor Product Versions
Seagull Software
  • Bartender
  • 2021_r1, 12.0.1

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-502
Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid.

*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 seagull_software bartender 2021_r1 / / / / / / /
a seagull_software bartender 12.0.1 / / / / / / /

CVSS Score

8.5 / 10

CVSS Data - 4.0

  • Attack Vector: LOCAL
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • 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:L/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: June 4, 2026, 6:16 p.m.
Last Modified: June 4, 2026, 7:15 p.m.

Status : Awaiting Analysis

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

More info

*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.