CVE-2025-58589: CWE-200 Exposure of Sensitive Information to an Unauthorized Actor in SICK AG Baggage Analytics
When an error occurs in the application a full stacktrace is provided to the user. The stacktrace lists class and method names as well as other internal information. An attacker thus receives information about the technology used and the structure of the application.
AI Analysis
Technical Summary
CVE-2025-58589 is an information disclosure vulnerability classified under CWE-200, affecting all versions of SICK AG's Baggage Analytics software. The vulnerability arises because the application, upon encountering an error, returns a detailed stacktrace to the user interface. This stacktrace includes class names, method names, and other internal implementation details that reveal the underlying technology stack and application structure. Such exposure can provide attackers with valuable intelligence to facilitate further attacks, such as identifying exploitable components or crafting targeted exploits. The vulnerability requires the attacker to have authenticated access (PR:H) but does not require user interaction (UI:N). The CVSS 3.1 base score is 2.7, reflecting a low severity primarily due to the limited confidentiality impact (C:L), no impact on integrity or availability, and the need for privileges to exploit. No patches or known exploits are currently available. The issue is a result of improper error handling and information leakage in the software's error reporting mechanism. Proper error handling best practices recommend suppressing detailed stacktraces from end users and logging them securely for developers. This vulnerability does not directly compromise system integrity or availability but can aid attackers in reconnaissance and planning of subsequent attacks.
Potential Impact
For European organizations, especially those operating airports or handling baggage analytics, this vulnerability could expose internal application details to authenticated users, potentially including malicious insiders or compromised accounts. The leaked information may facilitate more effective attacks by revealing software architecture and technology stacks, increasing the risk of targeted exploitation. While the direct impact on confidentiality is low and there is no impact on integrity or availability, the vulnerability could serve as an enabler for more severe attacks if combined with other vulnerabilities. Organizations relying on SICK AG Baggage Analytics should consider this a risk to operational security and information confidentiality. The exposure of internal details may also have compliance implications under data protection regulations if it leads to further breaches. However, since exploitation requires authenticated access, the threat is somewhat contained within the organization's perimeter or user base.
Mitigation Recommendations
To mitigate CVE-2025-58589, organizations should immediately configure the Baggage Analytics application to disable detailed error messages and stacktraces from being displayed to end users. Instead, errors should be logged securely and access to these logs should be strictly controlled and monitored. Implement role-based access controls to limit who can authenticate and access the system, reducing the risk of unauthorized users obtaining sensitive error information. Conduct regular audits of application error handling configurations and ensure that development and production environments do not expose stacktraces. Additionally, monitor authentication logs for suspicious activity that could indicate attempts to exploit this vulnerability. If possible, engage with SICK AG for updates or patches addressing this issue. Finally, incorporate this vulnerability into threat modeling and penetration testing exercises to assess the risk in the context of the organization's environment.
Affected Countries
Germany, France, United Kingdom, Netherlands, Italy, Spain, Belgium, Switzerland
CVE-2025-58589: CWE-200 Exposure of Sensitive Information to an Unauthorized Actor in SICK AG Baggage Analytics
Description
When an error occurs in the application a full stacktrace is provided to the user. The stacktrace lists class and method names as well as other internal information. An attacker thus receives information about the technology used and the structure of the application.
AI-Powered Analysis
Technical Analysis
CVE-2025-58589 is an information disclosure vulnerability classified under CWE-200, affecting all versions of SICK AG's Baggage Analytics software. The vulnerability arises because the application, upon encountering an error, returns a detailed stacktrace to the user interface. This stacktrace includes class names, method names, and other internal implementation details that reveal the underlying technology stack and application structure. Such exposure can provide attackers with valuable intelligence to facilitate further attacks, such as identifying exploitable components or crafting targeted exploits. The vulnerability requires the attacker to have authenticated access (PR:H) but does not require user interaction (UI:N). The CVSS 3.1 base score is 2.7, reflecting a low severity primarily due to the limited confidentiality impact (C:L), no impact on integrity or availability, and the need for privileges to exploit. No patches or known exploits are currently available. The issue is a result of improper error handling and information leakage in the software's error reporting mechanism. Proper error handling best practices recommend suppressing detailed stacktraces from end users and logging them securely for developers. This vulnerability does not directly compromise system integrity or availability but can aid attackers in reconnaissance and planning of subsequent attacks.
Potential Impact
For European organizations, especially those operating airports or handling baggage analytics, this vulnerability could expose internal application details to authenticated users, potentially including malicious insiders or compromised accounts. The leaked information may facilitate more effective attacks by revealing software architecture and technology stacks, increasing the risk of targeted exploitation. While the direct impact on confidentiality is low and there is no impact on integrity or availability, the vulnerability could serve as an enabler for more severe attacks if combined with other vulnerabilities. Organizations relying on SICK AG Baggage Analytics should consider this a risk to operational security and information confidentiality. The exposure of internal details may also have compliance implications under data protection regulations if it leads to further breaches. However, since exploitation requires authenticated access, the threat is somewhat contained within the organization's perimeter or user base.
Mitigation Recommendations
To mitigate CVE-2025-58589, organizations should immediately configure the Baggage Analytics application to disable detailed error messages and stacktraces from being displayed to end users. Instead, errors should be logged securely and access to these logs should be strictly controlled and monitored. Implement role-based access controls to limit who can authenticate and access the system, reducing the risk of unauthorized users obtaining sensitive error information. Conduct regular audits of application error handling configurations and ensure that development and production environments do not expose stacktraces. Additionally, monitor authentication logs for suspicious activity that could indicate attempts to exploit this vulnerability. If possible, engage with SICK AG for updates or patches addressing this issue. Finally, incorporate this vulnerability into threat modeling and penetration testing exercises to assess the risk in the context of the organization's environment.
Affected Countries
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Technical Details
- Data Version
- 5.1
- Assigner Short Name
- SICK AG
- Date Reserved
- 2025-09-03T08:58:53.142Z
- Cvss Version
- 3.1
- State
- PUBLISHED
Threat ID: 68e36cef0e76680ec164d67c
Added to database: 10/6/2025, 7:17:03 AM
Last enriched: 10/6/2025, 7:18:39 AM
Last updated: 10/7/2025, 4:25:11 AM
Views: 11
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