CVE-2025-20264

June 26, 2025, 6:57 p.m.

6.4
Medium

Description

A vulnerability in the web-based management interface of Cisco Identity Services Engine (ISE) could allow an authenticated, remote attacker to bypass the authorization mechanisms for specific administrative functions. This vulnerability is due to insufficient authorization enforcement mechanisms for users created by SAML SSO integration with an external identity provider. An attacker could exploit this vulnerability by submitting a series of specific commands to an affected device. A successful exploit could allow the attacker to modify a limited number of system settings, including some that would result in a system restart. In single-node Cisco ISE deployments, devices that are not authenticated to the network will not be able to authenticate until the Cisco ISE system comes back online. 

Product(s) Impacted

Vendor Product Versions
Cisco
  • Identity Services Engine
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-285
Improper Authorization
The product does not perform or incorrectly performs an authorization check when an actor attempts to access a resource or perform an action.

*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 cisco identity_services_engine / / / / / / / /

CVSS Score

6.4 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: June 25, 2025, 4:15 p.m.
Last Modified: June 26, 2025, 6:57 p.m.

Status : Awaiting Analysis

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

More info

Source

psirt@cisco.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.