CVE-2025-58586: CWE-204 Observable Response Discrepancy in SICK AG Baggage Analytics
For failed login attempts, the application returns different error messages depending on whether the login failed due to an incorrect password or a non-existing username. This allows an attacker to guess usernames until they find an existing one.
AI Analysis
Technical Summary
This vulnerability involves an observable response discrepancy (CWE-204) in the login mechanism of SICK AG's Baggage Analytics. When a login attempt fails, the system reveals whether the failure was due to a non-existent username or an incorrect password by returning different error messages. This behavior enables attackers to perform username enumeration attacks, potentially aiding further targeted attacks. The CVSS 3.1 base score is 5.3 (medium severity), reflecting that the attack vector is network-based, requires no privileges or user interaction, and impacts confidentiality with limited scope.
Potential Impact
The primary impact is information disclosure through username enumeration. Attackers can identify valid usernames, which may facilitate subsequent attacks such as password guessing or social engineering. There is no direct impact on system integrity or availability reported.
Mitigation Recommendations
No patch or official fix is currently available for this vulnerability. Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. As a mitigation, it is recommended to standardize error messages for failed login attempts so that they do not reveal whether the username or password was incorrect, thereby preventing username enumeration.
CVE-2025-58586: CWE-204 Observable Response Discrepancy in SICK AG Baggage Analytics
Description
For failed login attempts, the application returns different error messages depending on whether the login failed due to an incorrect password or a non-existing username. This allows an attacker to guess usernames until they find an existing one.
CVSS v3.1
Score 5.3medium
Affected software
Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
This vulnerability involves an observable response discrepancy (CWE-204) in the login mechanism of SICK AG's Baggage Analytics. When a login attempt fails, the system reveals whether the failure was due to a non-existent username or an incorrect password by returning different error messages. This behavior enables attackers to perform username enumeration attacks, potentially aiding further targeted attacks. The CVSS 3.1 base score is 5.3 (medium severity), reflecting that the attack vector is network-based, requires no privileges or user interaction, and impacts confidentiality with limited scope.
Potential Impact
The primary impact is information disclosure through username enumeration. Attackers can identify valid usernames, which may facilitate subsequent attacks such as password guessing or social engineering. There is no direct impact on system integrity or availability reported.
Mitigation Recommendations
No patch or official fix is currently available for this vulnerability. Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. As a mitigation, it is recommended to standardize error messages for failed login attempts so that they do not reveal whether the username or password was incorrect, thereby preventing username enumeration.
Technical Details
- Data Version
- 5.1
- Assigner Short Name
- SICK AG
- Date Reserved
- 2025-09-03T08:58:14.356Z
- Cvss Version
- 3.1
- State
- PUBLISHED
Threat ID: 68e36cef0e76680ec164d66c
Added to database: 10/06/2025, 07:17:03 UTC
Last enriched: 05/14/2026, 02:29:44 UTC
Last updated: 09/10/2026, 19:36:51 UTC
Views: 194
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