CVE-2023-20154
Nov. 18, 2024, 5:11 p.m.
9.1
Critical
Description
A vulnerability in the external authentication mechanism of Cisco Modeling Labs could allow an unauthenticated, remote attacker to access the web interface with administrative privileges.
This vulnerability is due to the improper handling of certain messages that are returned by the associated external authentication server. An attacker could exploit this vulnerability by logging in to the web interface of an affected server. Under certain conditions, the authentication mechanism would be bypassed and the attacker would be logged in as an administrator. A successful exploit could allow the attacker to obtain administrative privileges on the web interface of an affected server, including the ability to access and modify every simulation and all user-created data. To exploit this vulnerability, the attacker would need valid user credentials that are stored on the associated external authentication server.
Cisco has released software updates that address this vulnerability. There are workarounds that address this vulnerability.
Product(s) Impacted
| Product | Versions |
|---|---|
| Cisco Modeling Labs |
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-305
Authentication Bypass by Primary Weakness
The authentication algorithm is sound, but the implemented mechanism can be bypassed as the result of a separate weakness that is primary to the authentication error.
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: UNCHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: HIGH
- Availability Impact: NONE
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
Timeline
Published: Nov. 15, 2024, 3:15 p.m.
Last Modified: Nov. 18, 2024, 5:11 p.m.
Last Modified: Nov. 18, 2024, 5:11 p.m.
Status : Awaiting Analysis
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
ykramarz@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.